Improve startup sequence

Support older task hyper-parameter migration on pre-population

.gitignore

@@ -1,11 +1,10 @@
+syntax: glob
 .idea
 apierrors/errors
 static/build.json
 static/dashboard/node_modules
 static/webapp/node_modules
 static/webapp/.git
-scripts/
-generators/
 *.pyc
 __pycache__
 .ropeproject
@@ -20,3 +19,4 @@ build
 dist
 code.tar.gz
 server/schema/services/_cache.json
+server/apierrors/errors/*

README.md

@@ -1,33 +1,38 @@
-# TRAINS Server
+# Trains Server
 
-##  Auto-Magical Experiment Manager & Version Control for AI
+##  Auto-Magical Experiment Manager & Version Control for AI - ε Devops Included!
 
 [![GitHub license](https://img.shields.io/badge/license-SSPL-green.svg)](https://img.shields.io/badge/license-SSPL-green.svg)
 [![Python versions](https://img.shields.io/badge/python-3.6%20%7C%203.7-blue.svg)](https://img.shields.io/badge/python-3.6%20%7C%203.7-blue.svg)
 [![GitHub version](https://img.shields.io/github/release-pre/allegroai/trains-server.svg)](https://img.shields.io/github/release-pre/allegroai/trains-server.svg)
 [![PyPI status](https://img.shields.io/badge/status-beta-yellow.svg)](https://img.shields.io/badge/status-beta-yellow.svg)
 
+### Help improve Trains by filling our 2-min [user survey](https://allegro.ai/lp/trains-user-survey/)
+
+## :rocket: Trains-Agent Services is now included, for more information see [services](https://github.com/allegroai/trains-server#services)
+
+## v0.16 Upgrade Notice
+
+In v0.16, the Elasticsearch subsystem of Trains Server has been upgraded from version 5.6 to version 7.6. This change necessitates the migration of the database contents to accommodate the change in index structure across the different versions.  
+
+Follow [this procedure](https://allegro.ai/docs/deploying_trains/trains_server_es7_migration/) to migrate existing data.
+
 ## Introduction
 
-The **trains-server** is the backend service infrastructure for [TRAINS](https://github.com/allegroai/trains).
+The **trains-server** is the backend service infrastructure for [Trains](https://github.com/allegroai/trains).
 It allows multiple users to collaborate and manage their experiments.
-By default, TRAINS is set up to work with the TRAINS demo server, which is open to anyone and resets periodically.
-In order to host your own server, you will need to install **trains-server** and point TRAINS to it.
+By default, **Trains** is set up to work with the **Trains** demo server, which is open to anyone and resets periodically.
+In order to host your own server, you will need to launch **trains-server** and point **Trains** to it.
 
 **trains-server** contains the following components:
 
-* The TRAINS Web-App, a single-page UI for experiment management and browsing
+* The **Trains** Web-App, a single-page UI for experiment management and browsing
 * RESTful API for:
     * Documenting and logging experiment information, statistics and results
     * Querying experiments history, logs and results
 * Locally-hosted file server for storing images and models making them easily accessible using the Web-App
 
-You can quickly setup your **trains-server** using:
- - [Docker Installation](#installation)
- - Pre-built Amazon [AWS image](#aws)
- - [Kubernetes Helm](https://github.com/allegroai/trains-server-helm#trains-server-for-kubernetes-clusters-using-helm)
- or manual [Kubernetes installation](https://github.com/allegroai/trains-server-k8s#trains-server-for-kubernetes-clusters)
-
+You can quickly [deploy](#launching-trains-server)  your **trains-server** using Docker, AWS EC2 AMI, or Kubernetes. 
 
 ## System design
 
@@ -44,155 +49,43 @@ You can quickly setup your **trains-server** using:
     - Web application on sub-domain: app.\*.\*
     - API service on sub-domain: api.\*.\*
     - File storage service on sub-domain: files.\*.\*
+    
+## Launching trains-server
 
-## Install / Upgrade - AWS <a name="aws"></a>
+### Prerequisites
 
-Use one of our pre-installed Amazon Machine Images for easy deployment in AWS.
+The ports 8080/8081/8008 must be available for the **trains-server** services.
+   
+For example, to see if port `8080` is in use:
 
-For details and instructions, see [TRAINS-server: AWS pre-installed images](docs/install_aws.md).
+* Linux or macOS: 
+   
+        sudo lsof -Pn -i4 | grep :8080 | grep LISTEN
 
-## Docker Installation - Linux, Mac OS X <a name="installation"></a>
+* Windows:
 
-Use our pre-built Docker image for easy deployment in Linux and Mac OS X.
-For Windows, we recommend installing our pre-built Docker image on a Linux virtual machine.
-Latest docker images can be found [here](https://hub.docker.com/r/allegroai/trains).
+        netstat -an |find /i "8080"
+   
+### Launching   
+    
+Launch **trains-server** in any of the following formats:
 
-1. Setup Docker ([docker-compose Ubuntu](docs/faq.md#ubuntu), [docker-compose OS X](docs/faq.md#mac-osx), [Setup Docker Service Manually](docs/docker_setup.md#setup-docker))
+- Pre-built [AWS EC2 AMI](https://allegro.ai/docs/deploying_trains/trains_server_aws_ec2_ami/)
+- Pre-built [GCP Custom Image](https://allegro.ai/docs/deploying_trains/trains_server_gcp/)
+- Pre-built Docker Image
+    - [Linux](https://allegro.ai/docs/deploying_trains/trains_server_linux_mac/)
+    - [macOS](https://allegro.ai/docs/deploying_trains/trains_server_linux_mac/)
+    - [Windows 10](https://allegro.ai/docs/deploying_trains/trains_server_win/)
+- Kubernetes    
+    - [Kubernetes Helm](https://allegro.ai/docs/deploying_trains/trains_server_kubernetes_helm/)
+    - Manual [Kubernetes installation](https://allegro.ai/docs/deploying_trains/trains_server_kubernetes/)
 
-    Make sure port 8080/8081/8008 are available for the `trains-server` services
+## Connecting Trains to your trains-server
 
-    Increase vm.max_map_count for `ElasticSearch` docker
-
-    ```bash
-    echo "vm.max_map_count=262144" > /tmp/99-trains.conf
-    sudo mv /tmp/99-trains.conf /etc/sysctl.d/99-trains.conf
-    sudo sysctl -w vm.max_map_count=262144
-
-    sudo service docker restart
-    ```
-
-1. Create local directories for the databases and storage.
-
-    ```bash
-    sudo mkdir -p /opt/trains/data/elastic
-    sudo mkdir -p /opt/trains/data/mongo/db
-    sudo mkdir -p /opt/trains/data/mongo/configdb
-    sudo mkdir -p /opt/trains/data/redis
-    sudo mkdir -p /opt/trains/logs
-    sudo mkdir -p /opt/trains/data/fileserver
-    sudo mkdir -p /opt/trains/config
-    ```
-
-    Linux
-    ```bash
-    $ sudo chown -R 1000:1000 /opt/trains
-    ```
-    Mac OS X
-    ```bash
-    $ sudo chown -R $(whoami):staff /opt/trains
-    ```
-
-1. Clone the [trains-server](https://github.com/allegroai/trains-server) repository and change directories to the new **trains-server** directory.
-
-    ```bash
-    $ git clone https://github.com/allegroai/trains-server.git
-    $ cd trains-server
-    ```
-
-1. Launch the Docker containers <a name="launch-docker"></a>
-
-    * Automatically with docker-compose (details: [Linux/Ubuntu](docs/faq.md#ubuntu), [OS X](docs/faq.md#mac-osx))
-
-    ```bash
-    $ docker-compose up
-    ```
-
-    * Manually, see [Launching Docker Containers Manually](docs/docker_setup.md#launch) for instructions.
-
-1. Your server is now running on [http://localhost:8080](http://localhost:8080) and the following ports are available:
-
-    * Web server on port `8080`
-    * API server on port `8008`
-    * File server on port `8081`
-
-## Optional Configuration
-
-The **trains-server** default configuration can be easily overridden using external configuration files. By default, the server will look for these files in `/opt/trains/config`.
-
-In order to apply the new configuration, you must restart the server (see [Restarting trains-server](#restart-server)).
-
-### Adding Web Login Authentication
-
-By default anyone can login to the **trains-server** Web-App.
-You can configure the **trains-server** to allow only a specific set of users to access the system.
-
-Enable this feature by placing `apiserver.conf` file under `/opt/trains/config`.
-
-
-Sample fixed user configuration file `/opt/trains/config/apiserver.conf`:
-
-    auth {
-        # Fixed users login credetials
-        # No other user will be able to login
-        fixed_users {
-            enabled: true
-            users: [
-                {
-                    username: "jane"
-                    password: "12345678"
-                    name: "Jane Doe"
-                },
-                {
-                    username: "john"
-                    password: "12345678"
-                    name: "John Doe"
-                },
-            ]
-        }
-    }
-
-To apply the `apiserver.conf` changes, you must restart the *trains-apiserver* (docker) (see [Restarting trains-server](#restart-server)).
-
-### Configuring the Non-Responsive Experiments Watchdog
-
-The non-responsive experiment watchdog, monitors experiments that were not updated for a given period of time,
-and marks them as `aborted`. The watchdog is always active with a default of 7200 seconds (2 hours) of inactivity threshold.
-
-To change the watchdog's timeouts, place a `services.conf` file under `/opt/trains/config`.
-
-Sample watchdog configuration file `/opt/trains/config/services.conf`:
-
-    tasks {
-        non_responsive_tasks_watchdog {
-            # In-progress tasks that haven't been updated for at least 'value' seconds will be stopped by the watchdog
-            threshold_sec: 7200
-
-            # Watchdog will sleep for this number of seconds after each cycle
-            watch_interval_sec: 900
-        }
-    }
-
-To apply the `services.conf` changes, you must restart the *trains-apiserver* (docker) (see [Restarting trains-server](#restart-server)).
-
-### Restarting trains-server <a name="restart-server"></a>
-
-To restart the **trains-server**, you must first stop and remove the containers, and then restart.
-
-1. Restarting docker-compose containers.
-
-        $ docker-compose down
-        $ docker-compose up
-
-1. Manually restarting dockers [instructions](docs/docker_setup.md#launch).
-
-## Configuring **TRAINS** client
-
-Once you have installed the **trains-server**, make sure to configure **TRAINS** [client](https://github.com/allegroai/trains)
-to use your locally installed server (and not the demo server).
-
-- Run the `trains-init` command for an interactive setup
-
-- Or manually edit `~/trains.conf` file, making sure the `api_server` value is configured correctly, for example:
+By default, the **Trains** client is set up to work with the [**Trains** demo server](https://demoapp.trains.allegro.ai/).  
+To have the **Trains** client use your **trains-server** instead:
+- Run the `trains-init` command for an interactive setup.
+- Or manually edit `~/trains.conf` file, making sure the server settings (`api_server`, `web_server`, `file_server`) are configured correctly, for example:
 
         api {
             # API server on port 8008
@@ -205,93 +98,111 @@ to use your locally installed server (and not the demo server).
             files_server: "http://localhost:8081"
         }
 
-* Notice that if you setup **trains-server** in a sub-domain configuration, there is no need to specify a port number,
+**Note**: If you have set up **trains-server** in a sub-domain configuration, then there is no need to specify a port number,
 it will be inferred from the http/s scheme.
 
-See [Installing and Configuring TRAINS](https://github.com/allegroai/trains#configuration) for more details.
+After launching the **trains-server** and configuring the **Trains** client to use the **trains-server**,
+you can [use](https://github.com/allegroai/trains#using-trains) **Trains** in your experiments and view them in your **trains-server** web server,
+for example http://localhost:8080.  
+For more information about the Trains client, see [**Trains**](https://github.com/allegroai/trains).
 
-## What next?
+## Trains-Agent Services  <a name="services"></a> 
 
-Now that the **trains-server** is installed, and TRAINS is configured to use it,
-you can [use](https://github.com/allegroai/trains#using-trains) TRAINS in your experiments and view them in the web server,
-for example http://localhost:8080
+As of version 0.15 of **trains-server**, dockerized deployment includes a **Trains-Agent Services** container running as 
+part of the docker container collection.
+
+Trains-Agent Services is an extension of Trains-Agent that provides the ability to launch long-lasting jobs 
+that previously had to be executed on local / dedicated machines. It allows a single agent to 
+launch multiple dockers (Tasks) for different use cases. To name a few use cases, auto-scaler service (spinning instances 
+when the need arises and the budget allows), Controllers (Implementing pipelines and more sophisticated DevOps logic),
+Optimizer (such as Hyper-parameter Optimization or sweeping), and Application (such as interactive Bokeh apps for 
+increased data transparency)
+
+Trains-Agent Services container will spin **any** task enqueued into the dedicated `services` queue. 
+Every task launched by Trains-Agent Services  will be registered as a new node in the system, 
+providing tracking and transparency capabilities.  
+You can also run the Trains-Agent Services manually, see details in [trains-agent services mode](https://github.com/allegroai/trains-agent#trains-agent-services-mode-)
+
+**Note**: It is the user's responsibility to make sure the proper tasks are pushed into the `services` queue. 
+Do not enqueue training / inference tasks into the `services` queue, as it will put unnecessary load on the server.
+
+## Advanced Functionality
+
+**trains-server** provides a few additional useful features, which can be manually enabled:
+ 
+* [Web login authentication](https://allegro.ai/docs/faq/faq/#web-auth)
+* [Non-responsive experiments watchdog](https://allegro.ai/docs/faq/faq/#watchdog)  
+
+## Restarting trains-server
+
+To restart the **trains-server**, you must first stop the containers, and then restart them.
+
+   ```bash
+   docker-compose down
+   docker-compose -f docker-compose.yml up
+   ```
 
 ## Upgrading <a name="upgrade"></a>
 
-We are constantly updating, improving and adding to the **trains-server**.
-New releases will include new pre-built Docker images.
-When we release a new version and include a new pre-built Docker image for it, upgrade as follows:
+**trains-server** releases are also reflected in the [docker compose configuration file](https://github.com/allegroai/trains-server/blob/master/docker-compose.yml).  
+We strongly encourage you to keep your **trains-server** up to date, by keeping up with the current release.
 
-* Upgrading your docker-compose installation
+**Note**: The following upgrade instructions use the Linux OS as an example.
 
-    * Shut down the docker containers
-    ```bash
-    $ docker-compose down
-    ```
-  
-    * We highly recommend backing up your data directory before upgrading     
-    (see **Step ii** in the Manual Docker upgrade)
+To upgrade your existing **trains-server** deployment:
 
-    * Spin up the docker containers, it will automatically pull the latest trains-server build    
-    ```bash
-    $ docker-compose up
-    ```
+1. Shut down the docker containers
+   ```bash
+   docker-compose down
+   ```
 
-    * In case of a docker error: "... The container name "/trains-???" is already in use by ..."      
-      Try removing deprecated images with:
-      ```bash
-      $ docker rm -f $(docker ps -a -q)
-      ```
+1. We highly recommend backing up your data directory before upgrading.
 
-* Manual Docker upgrade
-    1. Shut down and remove each of your Docker instances using the following commands:
-    
-        ```bash
-        $ sudo docker stop <docker-name>
-        $ sudo docker rm -v <docker-name>
-        ```
-    
-        The Docker names are (see [Launching Docker Containers](#launch-docker)):
-    
-        * `trains-elastic`
-        * `trains-mongo`
-        * `trains-redis`
-        * `trains-fileserver`
-        * `trains-apiserver`
-        * `trains-webserver`
-    
-    2. We highly recommend backing up your data directory!. A simple way to do that is using `tar`:
-    
-        For example, if your data directory is `/opt/trains`, use the following command:
-    
-        ```bash
-        $ sudo tar czvf ~/trains_backup.tgz /opt/trains/data
-        ```
-        This backups all data to an archive in your home directory.
-    
-        To restore this example backup, use the following command:
-        ```bash
-        $ sudo rm -R /opt/trains/data
-        $ sudo tar -xzf ~/trains_backup.tgz -C /opt/trains/data
-        ```
-    
-    3. Pull the new **trains-server** docker image using the following command:
-    
-        ```bash
-        $ sudo docker pull allegroai/trains:latest
-        ```
-    
-        If you wish to pull a different version, replace `latest` with the required version number, for example:
-        ```bash
-        $ sudo docker pull allegroai/trains:0.11.0
-         ```
-    
-    4. Launch the newly released Docker image (see [Launching Docker Containers](#launch-docker)).
+   Assuming your data directory is `/opt/trains`, to archive all data into `~/trains_backup.tgz` execute:
+
+   ```bash
+   sudo tar czvf ~/trains_backup.tgz /opt/trains/data
+   ```    
+
+   <details>
+   <summary>Restore instructions:</summary>
+
+   To restore this example backup, execute:
+   ```bash
+   sudo rm -R /opt/trains/data
+   sudo tar -xzf ~/trains_backup.tgz -C /opt/trains/data
+   ```
+   </details>
+
+1. Download the latest `docker-compose.yml` file.
+
+   ```bash
+   curl https://raw.githubusercontent.com/allegroai/trains-server/master/docker-compose.yml -o docker-compose.yml 
+   ```
+
+1. Configure the Trains-Agent Services (not supported on Windows installation). 
+   If `TRAINS_HOST_IP` is not provided, Trains-Agent Services will use the external 
+   public address of the **trains-server**. If `TRAINS_AGENT_GIT_USER` / `TRAINS_AGENT_GIT_PASS` are not provided, 
+   the Trains-Agent Services will not be able to access any private repositories for running service tasks.
+   
+   ```bash
+   export TRAINS_HOST_IP=server_host_ip_here
+   export TRAINS_AGENT_GIT_USER=git_username_here
+   export TRAINS_AGENT_GIT_PASS=git_password_here
+   ```
+
+1. Spin up the docker containers, it will automatically pull the latest **trains-server** build    
+   ```bash
+   docker-compose -f docker-compose.yml pull
+   docker-compose -f docker-compose.yml up
+   ```
+
+**\* If something went wrong along the way, check our FAQ: [Common Docker Upgrade Errors](https://allegro.ai/docs/faq/faq/#common-docker-upgrade-errors).**
 
 
 ## Community & Support
 
-If you have any questions, look to the TRAINS-server [FAQ](https://github.com/allegroai/trains-server/blob/master/docs/faq.md), or
+If you have any questions, look to the Trains [FAQ](https://allegro.ai/docs/faq/faq/), or
 tag your questions on [stackoverflow](https://stackoverflow.com/questions/tagged/trains) with '**trains**' tag.
 
 For feature requests or bug reports, please use [GitHub issues](https://github.com/allegroai/trains-server/issues).

docker-compose-unified.yml

@@ -15,14 +15,19 @@ services:
     volumes:
     - /opt/trains/logs:/var/log/trains
     - /opt/trains/data/fileserver:/mnt/fileserver
+    - /opt/trains/config:/opt/trains/config
+
     depends_on:
       - redis
       - mongo
       - elasticsearch
     environment:
-      ELASTIC_SERVICE_HOST: elasticsearch
-      MONGODB_SERVICE_HOST: mongo
-      REDIS_SERVICE_HOST: redis
+      TRAINS_ELASTIC_SERVICE_HOST: elasticsearch
+      TRAINS_ELASTIC_SERVICE_PORT: 9200
+      TRAINS_MONGODB_SERVICE_HOST: mongo
+      TRAINS_MONGODB_SERVICE_PORT: 27017
+      TRAINS_REDIS_SERVICE_HOST: redis
+      TRAINS_REDIS_SERVICE_PORT: 6379
     networks:
       - backend
   elasticsearch:
@@ -35,15 +40,11 @@ services:
       cluster.name: trains
       cluster.routing.allocation.node_initial_primaries_recoveries: "500"
       discovery.zen.minimum_master_nodes: "1"
+      discovery.type: "single-node"
       http.compression_level: "7"
       node.ingest: "true"
       node.name: trains
       reindex.remote.whitelist: '*.*'
-      script.inline: "true"
-      script.painless.regex.enabled: "true"
-      script.update: "true"
-      thread_pool.bulk.queue_size: "2000"
-      thread_pool.search.queue_size: "10000"
       xpack.monitoring.enabled: "false"
       xpack.security.enabled: "false"
     ulimits:
@@ -53,10 +54,10 @@ services:
       nofile:
         soft: 65536
         hard: 65536
-    image: docker.elastic.co/elasticsearch/elasticsearch:5.6.16
+    image: docker.elastic.co/elasticsearch/elasticsearch:7.6.2
     restart: unless-stopped
     volumes:
-    - /opt/trains/data/elastic:/usr/share/elasticsearch/data
+    - /opt/trains/data/elastic_7:/usr/share/elasticsearch/data
     ports:
     - "9200:9200"
   mongo:

docker-compose-win10.yml

@@ -0,0 +1,119 @@
+version: "3.6"
+services:
+
+  apiserver:
+    command:
+    - apiserver
+    container_name: trains-apiserver
+    image: allegroai/trains:latest
+    restart: unless-stopped
+    volumes:
+    - c:/opt/trains/logs:/var/log/trains
+    - c:/opt/trains/config:/opt/trains/config
+    depends_on:
+      - redis
+      - mongo
+      - elasticsearch
+      - fileserver
+    environment:
+      TRAINS_ELASTIC_SERVICE_HOST: elasticsearch
+      TRAINS_ELASTIC_SERVICE_PORT: 9200
+      TRAINS_MONGODB_SERVICE_HOST: mongo
+      TRAINS_MONGODB_SERVICE_PORT: 27017
+      TRAINS_REDIS_SERVICE_HOST: redis
+      TRAINS_REDIS_SERVICE_PORT: 6379
+      TRAINS_SERVER_DEPLOYMENT_TYPE: ${TRAINS_SERVER_DEPLOYMENT_TYPE:-win10}
+      TRAINS__apiserver__mongo__pre_populate__enabled: "true"
+      TRAINS__apiserver__mongo__pre_populate__zip_file: "/opt/trains/db-pre-populate/export.zip"
+    ports:
+    - "8008:8008"
+    networks:
+      - backend
+
+  elasticsearch:
+    networks:
+      - backend
+    container_name: trains-elastic
+    environment:
+      ES_JAVA_OPTS: -Xms2g -Xmx2g
+      bootstrap.memory_lock: "true"
+      cluster.name: trains
+      cluster.routing.allocation.node_initial_primaries_recoveries: "500"
+      discovery.zen.minimum_master_nodes: "1"
+      discovery.type: "single-node"
+      http.compression_level: "7"
+      node.ingest: "true"
+      node.name: trains
+      reindex.remote.whitelist: '*.*'
+      xpack.monitoring.enabled: "false"
+      xpack.security.enabled: "false"
+    ulimits:
+      memlock:
+        soft: -1
+        hard: -1
+      nofile:
+        soft: 65536
+        hard: 65536
+    image: docker.elastic.co/elasticsearch/elasticsearch:7.6.2
+    restart: unless-stopped
+    volumes:
+    - c:/opt/trains/data/elastic_7:/usr/share/elasticsearch/data
+    ports:
+    - "9200:9200"
+
+  fileserver:
+    networks:
+      - backend
+    command:
+    - fileserver
+    container_name: trains-fileserver
+    image: allegroai/trains:latest
+    restart: unless-stopped
+    volumes:
+    - c:/opt/trains/logs:/var/log/trains
+    - c:/opt/trains/data/fileserver:/mnt/fileserver
+    - c:/opt/trains/config:/opt/trains/config
+
+    ports:
+    - "8081:8081"
+
+  mongo:
+    networks:
+      - backend
+    container_name: trains-mongo
+    image: mongo:3.6.5
+    restart: unless-stopped
+    command: --setParameter internalQueryExecMaxBlockingSortBytes=196100200
+    volumes:
+    - c:/opt/trains/data/mongo/db:/data/db
+    - c:/opt/trains/data/mongo/configdb:/data/configdb
+    ports:
+    - "27017:27017"
+
+  redis:
+    networks:
+      - backend
+    container_name: trains-redis
+    image: redis:5.0
+    restart: unless-stopped
+    volumes:
+    - c:/opt/trains/data/redis:/data
+    ports:
+    - "6379:6379"
+
+  webserver:
+    command:
+    - webserver
+    container_name: trains-webserver
+    image: allegroai/trains:latest
+    restart: unless-stopped
+    volumes:
+    - c:/trains/logs:/var/log/trains
+    depends_on:
+      - apiserver
+    ports:
+    - "8080:80"
+
+networks:
+  backend:
+    driver: bridge

docker-compose.yml

@@ -10,15 +10,23 @@ services:
     volumes:
     - /opt/trains/logs:/var/log/trains
     - /opt/trains/config:/opt/trains/config
+    - /opt/trains/data/fileserver:/mnt/fileserver
     depends_on:
       - redis
       - mongo
       - elasticsearch
       - fileserver
     environment:
-      ELASTIC_SERVICE_HOST: elasticsearch
-      MONGODB_SERVICE_HOST: mongo
-      REDIS_SERVICE_HOST: redis
+      TRAINS_ELASTIC_SERVICE_HOST: elasticsearch
+      TRAINS_ELASTIC_SERVICE_PORT: 9200
+      TRAINS_MONGODB_SERVICE_HOST: mongo
+      TRAINS_MONGODB_SERVICE_PORT: 27017
+      TRAINS_REDIS_SERVICE_HOST: redis
+      TRAINS_REDIS_SERVICE_PORT: 6379
+      TRAINS_SERVER_DEPLOYMENT_TYPE: ${TRAINS_SERVER_DEPLOYMENT_TYPE:-linux}
+      TRAINS__apiserver__pre_populate__enabled: "true"
+      TRAINS__apiserver__pre_populate__zip_files: "/opt/trains/db-pre-populate"
+      TRAINS__apiserver__pre_populate__artifacts_path: "/mnt/fileserver"
     ports:
     - "8008:8008"
     networks:
@@ -34,15 +42,11 @@ services:
       cluster.name: trains
       cluster.routing.allocation.node_initial_primaries_recoveries: "500"
       discovery.zen.minimum_master_nodes: "1"
+      discovery.type: "single-node"
       http.compression_level: "7"
       node.ingest: "true"
       node.name: trains
       reindex.remote.whitelist: '*.*'
-      script.inline: "true"
-      script.painless.regex.enabled: "true"
-      script.update: "true"
-      thread_pool.bulk.queue_size: "2000"
-      thread_pool.search.queue_size: "10000"
       xpack.monitoring.enabled: "false"
       xpack.security.enabled: "false"
     ulimits:
@@ -52,10 +56,10 @@ services:
       nofile:
         soft: 65536
         hard: 65536
-    image: docker.elastic.co/elasticsearch/elasticsearch:5.6.16
+    image: docker.elastic.co/elasticsearch/elasticsearch:7.6.2
     restart: unless-stopped
     volumes:
-    - /opt/trains/data/elastic:/usr/share/elasticsearch/data
+    - /opt/trains/data/elastic_7:/usr/share/elasticsearch/data
     ports:
     - "9200:9200"
 
@@ -70,6 +74,7 @@ services:
     volumes:
     - /opt/trains/logs:/var/log/trains
     - /opt/trains/data/fileserver:/mnt/fileserver
+    - /opt/trains/config:/opt/trains/config
     ports:
     - "8081:8081"
 
@@ -103,13 +108,43 @@ services:
     container_name: trains-webserver
     image: allegroai/trains:latest
     restart: unless-stopped
-    volumes:
-    - /opt/trains/logs:/var/log/trains
     depends_on:
       - apiserver
     ports:
     - "8080:80"
 
+  agent-services:
+    networks:
+      - backend
+    container_name: trains-agent-services
+    image: allegroai/trains-agent-services:latest
+    restart: unless-stopped
+    privileged: true
+    environment:
+      TRAINS_HOST_IP: ${TRAINS_HOST_IP}
+      TRAINS_WEB_HOST: ${TRAINS_WEB_HOST:-}
+      TRAINS_API_HOST: http://apiserver:8008
+      TRAINS_FILES_HOST: ${TRAINS_FILES_HOST:-}
+      TRAINS_API_ACCESS_KEY: ${TRAINS_API_ACCESS_KEY:-}
+      TRAINS_API_SECRET_KEY: ${TRAINS_API_SECRET_KEY:-}
+      TRAINS_AGENT_GIT_USER: ${TRAINS_AGENT_GIT_USER}
+      TRAINS_AGENT_GIT_PASS: ${TRAINS_AGENT_GIT_PASS}
+      TRAINS_AGENT_UPDATE_VERSION: ${TRAINS_AGENT_UPDATE_VERSION:->=0.15.0}
+      TRAINS_AGENT_DEFAULT_BASE_DOCKER: "ubuntu:18.04"
+      AWS_ACCESS_KEY_ID: ${AWS_ACCESS_KEY_ID:-}
+      AWS_SECRET_ACCESS_KEY: ${AWS_SECRET_ACCESS_KEY:-}
+      AWS_DEFAULT_REGION: ${AWS_DEFAULT_REGION:-}
+      AZURE_STORAGE_ACCOUNT: ${AZURE_STORAGE_ACCOUNT:-}
+      AZURE_STORAGE_KEY: ${AZURE_STORAGE_KEY:-}
+      GOOGLE_APPLICATION_CREDENTIALS: ${GOOGLE_APPLICATION_CREDENTIALS:-}
+      TRAINS_WORKER_ID: "trains-services"
+      TRAINS_AGENT_DOCKER_HOST_MOUNT: "/opt/trains/agent:/root/.trains"
+    volumes:
+      - /var/run/docker.sock:/var/run/docker.sock
+      - /opt/trains/agent:/root/.trains
+    depends_on:
+      - apiserver
+
 networks:
   backend:
     driver: bridge

docs/apiserver.conf

@@ -0,0 +1,19 @@
+auth {
+    # Fixed users login credentials
+    # No other user will be able to login
+    fixed_users {
+        enabled: true
+        users: [
+            {
+                username: "jane"
+                password: "12345678"
+                name: "Jane Doe"
+            },
+            {
+                username: "john"
+                password: "12345678"
+                name: "John Doe"
+            },
+        ]
+    }
+}

docs/docker_setup.md

@@ -1,106 +0,0 @@
-# TRAINS-server: Using Docker Pre-Built Images
-
-The pre-built Docker image for the **trains-server** is the quickest way to get started with your own **TRAINS** server.
-
-You can also build the entire **trains-server** architecture using the code available in the [trains-server](https://github.com/allegroai/trains-server) repository.
-
-**Note**: We tested this pre-built Docker image with Linux, only. For Windows users, we recommend installing the pre-built image on a Linux virtual machine.
-
-## Prerequisites
-
-* You must be logged in as a user with sudo privileges
-* Use `bash` for all command-line instructions in this installation
-
-## Setup Docker
-
-### Step 1: Install Docker CE
-
-You must first install Docker. For instructions about installing Docker, see [Supported platforms](https://docs.docker.com/install//#support) in the Docker documentation.
-
-For example, to [install in Ubuntu](https://docs.docker.com/install/linux/docker-ce/ubuntu/) / Mint (x86_64/amd64):
-
-```bash
-sudo apt-get install -y apt-transport-https ca-certificates curl software-properties-common
-curl -fsSL https://download.docker.com/linux/ubuntu/gpg | sudo apt-key add -
-. /etc/os-release
-sudo add-apt-repository "deb [arch=amd64] https://download.docker.com/linux/ubuntu $UBUNTU_CODENAME stable"
-sudo apt-get update
-sudo apt-get install -y docker-ce
-```
-
-### Step 2: Set the Maximum Number of Memory Map Areas
-
-Elastic requires that the `vm.max_map_count` kernel setting, which is the maximum number of memory map areas a process can use, is set to at least 262144.
-
-For CentOS 7, Ubuntu 16.04, Mint 18.3, Ubuntu 18.04 and Mint 19.x, we tested the following commands to set `vm.max_map_count`:
-
-```bash
-echo "vm.max_map_count=262144" > /tmp/99-trains.conf
-sudo mv /tmp/99-trains.conf /etc/sysctl.d/99-trains.conf
-sudo sysctl -w vm.max_map_count=262144
-```
-
-For information about setting this parameter on other systems, see the [elastic](https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html#docker-cli-run-prod-mode) documentation.
-
-### Step 3: Restart the Docker daemon
-
-Restart the Docker daemon.
-
-```bash
-sudo service docker restart
-```
-
-### Step 4: Choose a Data Directory
-
-Choose a directory on your system in which all data maintained by the **trains-server** is stored.
-Create this directory, and set its owner and group to `uid` 1000. The data stored in this directory includes the database, uploaded files and logs.
-
-For example, if your data directory is `/opt/trains`, then use the following command:
-
-```bash
-    sudo mkdir -p /opt/trains/data/elastic
-    sudo mkdir -p /opt/trains/data/mongo/db
-    sudo mkdir -p /opt/trains/data/mongo/configdb
-    sudo mkdir -p /opt/trains/data/redis
-    sudo mkdir -p /opt/trains/logs
-    sudo mkdir -p /opt/trains/data/fileserver
-    sudo mkdir -p /opt/trains/config
-
-    sudo chown -R 1000:1000 /opt/trains
-```
-
-## TRAINS-server: Manually Launching Docker Containers <a name="launch"></a>
-
-You can manually launch the Docker containers using the following commands.
-
-If your data directory is not `/opt/trains`, then in the five `docker run` commands below, you must replace all occurrences of `/opt/trains` with your data directory path.
-
-1. Launch the **trains-elastic** Docker container.
-
-        sudo docker run -d --restart="always" --name="trains-elastic" -e "bootstrap.memory_lock=true" --ulimit memlock=-1:-1 -e "ES_JAVA_OPTS=-Xms2g -Xmx2g" -e "bootstrap.memory_lock=true" -e "cluster.name=trains" -e "discovery.zen.minimum_master_nodes=1" -e "node.name=trains" -e "script.inline=true" -e "script.update=true" -e "thread_pool.bulk.queue_size=2000" -e "thread_pool.search.queue_size=10000" -e "xpack.security.enabled=false" -e "xpack.monitoring.enabled=false" -e "cluster.routing.allocation.node_initial_primaries_recoveries=500" -e "node.ingest=true" -e "http.compression_level=7" -e "reindex.remote.whitelist=*.*" -e "script.painless.regex.enabled=true" --network="host" -v /opt/trains/data/elastic:/usr/share/elasticsearch/data docker.elastic.co/elasticsearch/elasticsearch:5.6.16
-
-1. Launch the **trains-mongo** Docker container.
-
-        sudo docker run -d --restart="always" --name="trains-mongo" -v /opt/trains/data/mongo/db:/data/db -v /opt/trains/data/mongo/configdb:/data/configdb --network="host" mongo:3.6.5
-
-1. Launch the **trains-redis** Docker container.
-
-        sudo docker run -d --restart="always" --name="trains-redis" -v /opt/trains/data/redis:/data --network="host" redis:5.0
-
-1. Launch the **trains-fileserver** Docker container.
-
-        sudo docker run -d --restart="always" --name="trains-fileserver" --network="host" -v /opt/trains/logs:/var/log/trains -v /opt/trains/data/fileserver:/mnt/fileserver allegroai/trains:latest fileserver
-
-1. Launch the **trains-apiserver** Docker container.
-
-        sudo docker run -d --restart="always" --name="trains-apiserver" --network="host" -v /opt/trains/logs:/var/log/trains -v /opt/trains/config:/opt/trains/config allegroai/trains:latest apiserver
-
-1. Launch the **trains-webserver** Docker container.
-
-        sudo docker run -d --restart="always" --name="trains-webserver" -p 8080:80 allegroai/trains:latest webserver
-
-1. Your server is now running on [http://localhost:8080](http://localhost:8080) and the following ports are available:
-
-    * API server on port `8008`
-    * Web server on port `8080`
-    * File server on port `8081`

docs/faq.md

@@ -1,66 +1,42 @@
-# TRAINS-server FAQ
+# trains-server FAQ
 
-* [Deploying trains-server on Kubernetes clusters](#kubernetes)
+Launching **trains-server**
 
-* [Creating a Helm Chart for trains-server Kubernetes deployment](#helm)
+* How do I launch **trains-server** on:
 
-* [Running trains-server on Mac OS X](#mac-osx)
+    * [Stand alone Linux Ubuntu systems?](#ubuntu)
+    
+    * [macOS?](#mac-osx)
+    
+    * [Windows 10?](#docker_compose_win10)
 
-* [Installing trains-server on stand alone Linux Ubuntu  systems ](#ubuntu)
+* [How do I restart trains-server?](#restart)
 
-* [Resolving port conflicts preventing fixed users mode authentication and login](#port-conflict)
+Kubernetes
 
-* [Configuring trains-server for sub-domains and load balancers](#sub-domains)
+* [Can I deploy trains-server on Kubernetes clusters?](#kubernetes)
 
-### Deploying trains-server on Kubernetes clusters <a name="kubernetes"></a>
+* [Can I create a Helm Chart for trains-server Kubernetes deployment?](#helm)
 
-**trains-server** supports Kubernetes. See [trains-server-k8s](https://github.com/allegroai/trains-server-k8s)
-which contains the YAML files describing the required services and detailed instructions for deploying
-**trains-server** to a Kubernetes clusters.
+Configuration
 
-### Creating a Helm Chart for trains-server Kubernetes deployment <a name="helm"></a>
+* [How do I configure trains-server for sub-domains and load balancers?](#sub-domains)
 
-**trains-server** supports creating a Helm chart for Kubernetes deployment. See [trains-server-helm](https://github.com/allegroai/trains-server-helm)
-which you can use to create a Helm chart for **trains-server** and contains detailed instructions for deploying
-**trains-server** to a Kubernetes clusters using Helm.
+* [Can I add web login authentication to trains-server?](#web-auth)
 
-### Running trains-server on Mac OS X <a name="mac-osx"></a>
+* [Can I modify the non-responsive experiment watchdog settings?](#watchdog)
 
-To install and configure **trains-server** on Mac OS X, follow the steps below.
+Troubleshooting
 
-1. Install [docker for OS X](https://docs.docker.com/docker-for-mac/install/).
+* [How do I fix Docker upgrade errors?](#common-docker-upgrade-errors)
 
-1. Configure [Docker](https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html#docker-cli-run-prod-mode).
+* [Why is web login authentication not working?](#port-conflict)
 
-        $ screen ~/Library/Containers/com.docker.docker/Data/vms/0/tty
-        sysctl -w vm.max_map_count=262144
+## Launching **trains-server**
 
-1. Create local directories for the databases and storage.
+### How do I launch trains-server on stand alone Linux Ubuntu systems? <a name="ubuntu"></a>
 
-        $ sudo mkdir -p /opt/trains/data/elastic
-        $ sudo mkdir -p /opt/trains/data/mongo/db
-        $ sudo mkdir -p /opt/trains/data/mongo/configdb
-        $ sudo mkdir -p /opt/trains/logs
-        $ sudo mkdir -p /opt/trains/config
-        $ sudo mkdir -p /opt/trains/data/fileserver
-        $ sudo chown -R $(whoami):staff /opt/trains
-
-1. Open the Docker app, select **Preferences**, and then on the **File Sharing** tab, add `/opt/trains`.
-
-1. Clone the [trains-server](https://github.com/allegroai/trains-server) repository and change directories to the new **trains-server** directory.
-
-        $ git clone https://github.com/allegroai/trains-server.git
-        $ cd trains-server
-
-1. Run `docker-compose` with the unified docker image.
-
-        $ docker-compose -f docker-compose-unified.yml up
-
-    Your server is now running on [http://localhost:8080](http://localhost:8080)
-
-### Installing trains-server on stand alone Linux Ubuntu systems <a name="ubuntu"></a>
-
-To install **trains-server** on a stand alone Linux Ubuntu, follow the steps belows.
+To launch **trains-server** on a stand alone Linux Ubuntu:
 
 1. Install [docker for Ubuntu](https://docs.docker.com/install/linux/docker-ce/ubuntu/).
 
@@ -71,81 +47,127 @@ To install **trains-server** on a stand alone Linux Ubuntu, follow the steps bel
 
 1. Remove the previous installation of **trains-server**.
 
-    **WARNING**: This clears all existing **TRAINS** databases.
+    **WARNING**: This clears all existing **Trains** databases.
 
-        $ sudo rm -R /opt/trains/
+        sudo rm -R /opt/trains/
 
 1. Create local directories for the databases and storage.
 
-        $ sudo mkdir -p /opt/trains/data/elastic
-        $ sudo mkdir -p /opt/trains/data/mongo/db
-        $ sudo mkdir -p /opt/trains/data/mongo/configdb
-        $ sudo mkdir -p /opt/trains/logs
-        $ sudo mkdir -p /opt/trains/config
-        $ sudo mkdir -p /opt/trains/data/fileserver
-        $ sudo chown -R 1000:1000 /opt/trains
+        sudo mkdir -p /opt/trains/data/elastic
+        sudo mkdir -p /opt/trains/data/mongo/db
+        sudo mkdir -p /opt/trains/data/mongo/configdb
+        sudo mkdir -p /opt/trains/logs
+        sudo mkdir -p /opt/trains/config
+        sudo mkdir -p /opt/trains/data/fileserver
+        sudo chown -R 1000:1000 /opt/trains
 
 1. Clone the [trains-server](https://github.com/allegroai/trains-server) repository and change directories to the new **trains-server** directory.
 
-        $ git clone https://github.com/allegroai/trains-server.git
-        $ cd trains-server
+        git clone https://github.com/allegroai/trains-server.git
+        cd trains-server
 
 1. Run `docker-compose`
 
-        $ /usr/local/bin/docker-compose -f docker-compose.yml up
+        /usr/local/bin/docker-compose -f docker-compose.yml up
+
+    Your server is now running on [http://localhost:8080](http://localhost:8080)
+    
+### How do I launch trains-server on macOS? <a name="mac-osx"></a>
+
+To launch **trains-server** on macOS:
+
+1. Install [docker for macOS](https://docs.docker.com/docker-for-mac/install/).
+
+1. Configure [Docker](https://www.elastic.co/guide/en/elasticsearch/reference/current/docker.html#docker-cli-run-prod-mode).
+
+        screen ~/Library/Containers/com.docker.docker/Data/vms/0/tty
+        sysctl -w vm.max_map_count=262144
+
+1. Create local directories for the databases and storage.
+
+        sudo mkdir -p /opt/trains/data/elastic
+        sudo mkdir -p /opt/trains/data/mongo/db
+        sudo mkdir -p /opt/trains/data/mongo/configdb
+        sudo mkdir -p /opt/trains/data/redis
+        sudo mkdir -p /opt/trains/logs
+        sudo mkdir -p /opt/trains/config
+        sudo mkdir -p /opt/trains/data/fileserver
+        sudo chown -R $(whoami):staff /opt/trains
+
+1. Open the Docker app, select **Preferences**, and then on the **File Sharing** tab, add `/opt/trains`.
+
+1. Clone the [trains-server](https://github.com/allegroai/trains-server) repository and change directories to the new **trains-server** directory.
+
+        git clone https://github.com/allegroai/trains-server.git
+        cd trains-server
+
+1. Run `docker-compose` with the docker compose file.
+
+        docker-compose -f docker-compose.yml up
 
     Your server is now running on [http://localhost:8080](http://localhost:8080)
 
-### Resolving port conflicts preventing fixed users mode authentication and login <a name="port-conflict"></a>
+### How do I launch trains-server on Windows 10? <a name="docker_compose_win10"></a>
 
-A port conflict may occur between the **trains-server** MongoDB and Elastic instances and other
-instances running on your system. **trains-server** uses the following default ports which may be in conflict with other instances:
+You can run **trains-server** on Windows 10 using Docker Desktop for Windows (see the Docker [System Requirements](https://docs.docker.com/docker-for-windows/install/#system-requirements)).
 
-* MongoDB port `27017`
-* Elastic port `9200`
+To launch **trains-server** on Windows 10:
 
-You can check for port conflicts in the logs in `/opt/trains/log`.
+1. Install the Docker Desktop for Windows application by either:
 
-If a port conflict occurs, first change the port in your **trains-server** `/opt/trains/server/config/default/hosts.conf` file to the new port and then
-run the `docker run` command with the `port` option specifying the new port to restart the **trains-server** instance.
+    * following the [Install Docker Desktop on Windows](https://docs.docker.com/docker-for-windows/install/) instructions.
+    * running the Docker installation [wizard](https://hub.docker.com/?overlay=onboarding).
 
-For example, to resolve a MongoDB port conflict change port `27017` to `27018`:
+1. Increase the memory allocation in Docker Desktop to `4GB`.
 
-1. Modify `/opt/trains/server/config/default/hosts.conf` changing the ports in the `mongo` section:
+    1. In your Windows notification area (system tray), right click the Docker icon.
+    
+    1. Click *Settings*, *Advanced*, and then set the memory to at least `4096`. 
+    
+    1. Click *Apply*.
 
-        elastic {
-          events {
-            hosts: [{host: "127.0.0.1", port: 9200}]
-            args {
-              timeout: 60
-              dead_timeout: 10
-              max_retries: 5
-              retry_on_timeout: true
-            }
-            index_version: "1"
-          }
-        }
+1. Create local directories for data and logs. Open PowerShell and execute the following commands:
 
-        mongo {
-          backend {
-            host: "mongodb://127.0.0.1:27018/backend"
-          }
-          auth {
-            host: "mongodb://127.0.0.1:27018/auth"
-          }
-        }
+        cd c:
+        mkdir c:\opt\trains\data
+        mkdir c:\opt\trains\logs
 
-2. Start the **trains-server** MongoDB container using `--port 27018`.
+1. Download the **trains-server** docker-compose YAML file [docker-compose-win10.yml](https://raw.githubusercontent.com/allegroai/trains-server/master/docker-compose-win10.yml) as `c:\opt\trains\docker-compose.yml`.
 
-        sudo docker run -d --restart="always" --name="trains-mongo" -v /opt/trains/data/mongo/db:/data/db -v /opt/trains/data/mongo/configdb:/data/configdb --network="host" mongo:3.6.5 mongod --port 27018
+1. Run `docker-compose`. In PowerShell, execute the following commands:
 
-In a future version of **trains-server**, to start the API server, environment variables will be available to use instead of modifying the configuration file (instead of Step 1 above).
-The environment variables will be available to set different ports for both MongoDB and Elastic instances:
+        docker-compose -f up docker-compose-win10.yml
 
-* `MONGODB_SERVICE_PORT` (e.g., `MONGODB_SERVICE_PORT=27018`)
-* `ELASTIC_SERVICE_POST` (e.g., `ELASTIC_SERVICE_POST=9201`)
+    Your server is now running on [http://localhost:8080](http://localhost:8080)
 
-### Configuring trains-server for sub-domains and load balancers <a name="sub-domains"></a>
+### How do I restart trains-server? <a name="restart"></a>
+
+Restart *trains-server* by first stopping the Docker containers and then restarting them.
+
+   ```bash
+   docker-compose down
+   docker-compose up -f docker-compose.yml
+   ```
+   
+   **Note**: If you are using a different docker-compose YAML file, specify that file.
+
+## Kubernetes
+
+### Can I deploy trains-server on Kubernetes clusters? <a name="kubernetes"></a>
+
+**trains-server** supports Kubernetes. See [trains-server-k8s](https://github.com/allegroai/trains-server-k8s)
+which contains the YAML files describing the required services and detailed instructions for deploying
+**trains-server** to a Kubernetes clusters.
+
+### Can I create a Helm Chart for trains-server Kubernetes deployment? <a name="helm"></a>
+
+**trains-server** supports creating a Helm chart for Kubernetes deployment. See [trains-server-helm](https://github.com/allegroai/trains-server-helm)
+which you can use to create a Helm chart for **trains-server** and contains detailed instructions for deploying
+**trains-server** to a Kubernetes clusters using Helm.
+
+## Configuration
+
+### How do I configure trains-server for sub-domains and load balancers? <a name="sub-domains"></a>
 
 You can configure **trains-server** for sub-domains and a load balancer.
 
@@ -181,3 +203,126 @@ For example, if your domain is `trains.mydomain.com` and your sub-domains are `a
 
 1. Run the Docker containers with our updated `docker run` commands (see [Launching Docker Containers](#https://github.com/allegroai/trains-server#launching-docker-containers)).
 
+### Can I add web login authentication to trains-server? <a name="web-auth"></a>
+
+By default, anyone can login to the **trains-server** Web-App.
+You can configure the **trains-server** to allow only a specific set of users to access the system.
+
+To add web login authentication to **trains-server**:
+
+1. If you are not using the current **trains-server** version, then [upgrade](https://github.com/allegroai/trains-server#upgrade).
+
+1. In `/opt/trains/config/apiserver.conf`, add the `auth` section and in it specify the users, for example:
+
+    **Note**: A sample `apiserver.conf` configuration file is also available [here](https://github.com/allegroai/trains-server/blob/master/docs/apiserver.conf).
+
+        auth {
+            # Fixed users login credentials
+            # No other user will be able to login
+            fixed_users {
+                enabled: true
+                users: [
+                    {
+                        username: "jane"
+                        password: "12345678"
+                        name: "Jane Doe"
+                    },
+                    {
+                        username: "john"
+                        password: "12345678"
+                        name: "John Doe"
+                    },
+                ]
+            }
+        }
+
+1. Restart **trains-server** (see the [Restarting trains-server](#restart) FAQ).
+
+### Can I modify the experiment watchdog settings? <a name="watchdog"></a>
+
+The non-responsive experiment watchdog monitors experiments that were not updated for a specified period of time
+and marks them as `aborted`. The watchdog is always active. 
+
+You can modify the following settings for the watchdog:
+ 
+* the time threshold (in seconds) of experiment inactivity (default value is 7200 seconds (2 hours))
+* the time interval (in seconds) between watchdog cycles
+
+To change the watchdog's settings:
+
+1. In `/opt/trains/config`, add the `services.conf` file and in it specify the watchdog settings, for example:
+
+    **Note**: A sample watchdog `services.conf` configuration file is also available [here](https://github.com/allegroai/trains-server/blob/master/docs/services.conf).
+
+        tasks {
+            non_responsive_tasks_watchdog {
+                # In-progress tasks that haven't been updated for at least 'value' seconds will be stopped by the watchdog
+                threshold_sec: 7200
+        
+                # Watchdog will sleep for this number of seconds after each cycle
+                watch_interval_sec: 900
+            }
+        }
+
+1. Restart **trains-server** (see the [Restarting trains-server](#restart) FAQ).
+
+## Troubleshooting
+
+### How do I fix Docker upgrade errors? <a name="common-docker-upgrade-errors"></a>
+
+To resolve the Docker error "... The container name "/trains-???" is already in use by ...", try removing deprecated images:
+
+    docker rm -f $(docker ps -a -q)
+
+### Why is web login authentication not working?
+
+A port conflict between the **trains-server** MongoDB and / or Elastic instances, and other
+instances running on your system may prevent web login authentication
+from working correctly. 
+
+**trains-server** uses the following default ports which may be in conflict with other instances:
+
+* MongoDB port `27017`
+* Elastic port `9200`
+
+You can check for port conflicts in the logs in `/opt/trains/log`.
+
+If a port conflict occurs, change the MongoDB and / or Elastic ports in the `docker-compose.yml`,
+and then run the Docker compose commands to restart the **trains-server** instance.
+
+To change the MongoDB and / or Elastic ports for **trains-server**:
+
+1. Edit the `docker-compose.yml` file.
+
+1. In the `services/trainsserver/environment` section, add the following environment variable(s):
+
+    * For MongoDB:
+    
+            MONGODB_SERVICE_PORT: <new-mongodb-port>
+        
+    * For Elastic:
+            
+            ELASTIC_SERVICE_PORT: <new-elasticsearch-port> 
+        
+    For example:
+    
+        MONGODB_SERVICE_PORT: 27018
+        ELASTIC_SERVICE_PORT: 9201
+            
+1. For MongoDB, in the `services/mongo/ports` section, expose the new MongoDB port:
+
+        <new-mongodb-port>:27017
+        
+    For example:
+    
+        20718:27017
+        
+1. For Elastic, in the `services/elasticsearch/ports` section, expose the new Elastic port:
+
+        <new-elsticsearch-port>:9200
+            
+    For example:
+
+        9201:9200
+    
+2. Restart **trains-server** (see the [Restarting trains-server](#restart) FAQ).

docs/install_aws.md

@@ -1,32 +1,36 @@
-# **TRAINS-server**: AWS pre-installed images
+# Deploying **trains-server** on AWS
 
-In order to easily deploy **trains-server** on AWS, we created the following Amazon Machine Images (AMIs).
+To easily deploy **trains-server** on AWS, use one of our pre-built Amazon Machine Images (AMIs).  
+We provide AMIs per region for each released version of **trains-server**, see [Released versions](#released-versions) below. 
 
-Service port numbers on these AMIs are:
- - Web: 8080
- - API: 8008
- - File Server: 8081
+Once the AMI is up and running, [configure the Trains client](https://github.com/allegroai/trains/blob/master/README.md#configuration) to use your **trains-server**.  
+The service port numbers on our **trains-server** AMIs:
 
-Persistent storage configuration:
- - MongoDB: /opt/trains/data/mongo/
- - ElasticSearch: /opt/trains/data/elastic/
- - File Server: /mnt/fileserver/
+- Web application: `8080`
+- API Server: `8008`
+- File Server: `8081`
 
-Instructions on launching a custom AMI from the EC2 console can be found [here](https://aws.amazon.com/premiumsupport/knowledge-center/launch-instance-custom-ami/)
-and a detailed version [here](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/launching-instance.html).
+The persistent storage configuration:
 
-The minimum recommended instance type is **t3a.large**
+- MongoDB: `/opt/trains/data/mongo/`
+- ElasticSearch: `/opt/trains/data/elastic/`
+- File Server: `/mnt/fileserver/`
+
+For examples and use cases, check the [Trains usage examples](https://github.com/allegroai/trains/blob/master/docs/trains_examples.md).
+
+For instructions on launching a custom AMI from the EC2 console, see the [AWS Knowledge Center](https://aws.amazon.com/premiumsupport/knowledge-center/launch-instance-custom-ami/) or detailed instructions in the [AWS Documentation](https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/launching-instance.html).
+
+The minimum recommended amount of RAM is 8GB. For example, **t3.large** or **t3a.large** would have the minimum recommended amount of resources.
 
 ## Upgrading
 
-In order to upgrade **trains-server** on an existing EC2 instance based on one of these AMIs, SSH into the instance and follow the [upgrade instructions](../README.md#upgrade) for **trains-server**.
+To upgrade **trains-server** on an existing EC2 instance based on one of these AMIs, SSH into the instance and follow the [upgrade instructions](../README.md#upgrade) for **trains-server**.
 
-### Upgrading AMI's to v0.12 
-**Including the automatically updated AMI**
+### Note on upgrading AMIs to v0.12 
 
-Version 0.12 introduced an additional REDIS docker to the trains-server setup.
+This upgrade includes the automatically updated AMI in Version 0.12. It also includes an additional REDIS docker to the **trains-server** setup.
 
-AMI upgrading instructions:
+To upgrade the AMI:
 
 1. SSH to the EC2 machine running one of the `Latest Version AMI's`
 2. Execute the following bash commands
@@ -44,47 +48,180 @@ AMI upgrading instructions:
 
 ## Released versions
 
-The following sections provide a list containing AMI Image ID per region for each released **trains-server** version.
+The following sections contain lists of AMI Image IDs, per region, for each released **trains-server** version.
 
-### Latest Version AMI <a name="autoupdate"></a>
-**For easier upgrades: The following AMI automatically update to the latest release every reboot**
+### Latest version AMI - v0.15.1 (auto update)<a name="autoupdate"></a>
 
-* **eu-north-1** : ami-072aef14041e70651
-* **ap-south-1** : ami-08032d881daca4de1
-* **eu-west-3** : ami-0b39c123d4343d408
-* **eu-west-2** : ami-0e0fe6fd14b2e9029
-* **eu-west-1** : ami-087c81e06d722e938
-* **ap-northeast-2** : ami-0caf74f03322b994c
-* **ap-northeast-1** : ami-0f723b3d49c0f2749
-* **sa-east-1** : ami-0ac5595ad0e106502
-* **ca-central-1** : ami-053049b463869469a
-* **ap-southeast-1** : ami-0b440ec389d6ff541
-* **ap-southeast-2** : ami-02af978ddc2c15b71
-* **eu-central-1** : ami-09ef364aa8df29760
-* **us-east-2** : ami-02e33f8ab77071509
-* **us-west-1** : ami-0ff33f256907fd460
-* **us-west-2** : ami-0387728fb09c8cda7
-* **us-east-1** : ami-02c47c5233eed7f88
+For easier upgrades, the following AMIs automatically update to the latest release every reboot:
 
-### v0.12.0
-* **eu-north-1** : ami-0ebb4bb8637d0da65
-* **ap-south-1** : ami-0fb3c89eb8a8fc294
-* **eu-west-3** : ami-0b55ea4a6698d5875
-* **eu-west-2** : ami-02979b6d77856b842
-* **eu-west-1** : ami-07f4c17a636489574
-* **ap-northeast-2** : ami-06071092427dd5ab4
-* **ap-northeast-1** : ami-0fbacddfc0e8d2651
-* **sa-east-1** : ami-073590d3b3e6f4cfd
-* **ca-central-1** : ami-0839610fc0101e41c
-* **ap-southeast-1** : ami-0ff0adeef7f9fa879
-* **ap-southeast-2** : ami-03ed15d31bfc2844c
-* **eu-central-1** : ami-0813c06d8b2462c39
-* **us-east-2** : ami-07c593425f988b054
-* **us-west-1** : ami-0eb0e13b1f06c03c0
-* **us-west-2** : ami-000568ca142798412
-* **us-east-1** : ami-062d9da44f96c8a87
+* **eu-north-1** : ami-0f30c84b905d354b9 
+* **ap-south-1** : ami-050e7acec52c8c74e 
+* **eu-west-3** : ami-03911c5b5bc77ef75 
+* **eu-west-2** : ami-0a5ed8aa2573ccc70 
+* **eu-west-1** : ami-0a53c65e922ec0611 
+* **ap-northeast-2** : ami-08cd017a37b8e8aab 
+* **ap-northeast-1** : ami-056b3ca1ad5af9322 
+* **sa-east-1** : ami-01ddc9325bafb400c 
+* **ca-central-1** : ami-0fc3cbbd982b18b45 
+* **ap-southeast-1** : ami-04c7a358df7002ef5 
+* **ap-southeast-2** : ami-0eeaf54231b4ae22a 
+* **eu-central-1** : ami-00b8e44041f8175fd 
+* **us-east-2** : ami-0ac7deebb3f738f6d 
+* **us-west-1** : ami-06bc07deb8b8c44d6 
+* **us-west-2** : ami-01ba85ffe79a422f1 
+* **us-east-1** : ami-04cf5a66cb4928ac3 
+
+### v0.15.1 (static update)
+
+* **eu-north-1** : ami-0cd314e267426d1b7 
+* **ap-south-1** : ami-086182cbe29151f96 
+* **eu-west-3** : ami-0062366012182815b 
+* **eu-west-2** : ami-022b8f2e32a9d18d0 
+* **eu-west-1** : ami-0d8cf60446e09aa3d 
+* **ap-northeast-2** : ami-0d4c168a815b56889 
+* **ap-northeast-1** : ami-0daf7887db1053ae4 
+* **sa-east-1** : ami-020a759a3ba4ff22b 
+* **ca-central-1** : ami-0c10b5e04b707f3e3 
+* **ap-southeast-1** : ami-0f61bb3529a165fcd 
+* **ap-southeast-2** : ami-032dcdc82749c66c5 
+* **eu-central-1** : ami-08f364f32d2eb3bae 
+* **us-east-2** : ami-0b7efc3591803eba4 
+* **us-west-1** : ami-08b2df27b0ada6faf 
+* **us-west-2** : ami-0693029c4bad28816 
+* **us-east-1** : ami-0200954fa9c2819ff 
+
+### v0.15.0 (static update)
+
+* **eu-north-1** : ami-0bef15c03eab64c0c 
+* **ap-south-1** : ami-06ac6248e583e2cd2 
+* **eu-west-3** : ami-0541d86ef47a5714e 
+* **eu-west-2** : ami-01381ef4c4ed22482 
+* **eu-west-1** : ami-064626a0dd38b21f1 
+* **ap-northeast-2** : ami-0a2490a7a3a8aa675 
+* **ap-northeast-1** : ami-063f1de819a2524b8 
+* **sa-east-1** : ami-07980486741b94987 
+* **ca-central-1** : ami-0ced3b8b21ded839e 
+* **ap-southeast-1** : ami-0c493c5093fde8741 
+* **ap-southeast-2** : ami-0320a727eccb8dc6c 
+* **eu-central-1** : ami-0aa85cfc78674c526 
+* **us-east-2** : ami-01791485051e1880c 
+* **us-west-1** : ami-0d8eade4d5888ea73 
+* **us-west-2** : ami-02ceaef72cdf60f7e 
+* **us-east-1** : ami-0fc3f9d1d0eba1d62 
+
+### v0.14.2 (static update)
+
+* **eu-north-1** : ami-006d491e9e8869248 
+* **ap-south-1** : ami-0e55ec221687f98e7 
+* **eu-west-3** : ami-06ad9cf3c05c83e91 
+* **eu-west-2** : ami-0d05839268e748cff 
+* **eu-west-1** : ami-0d14c297789ce0d7a 
+* **ap-northeast-2** : ami-0d7fd775f0e76cc6f 
+* **ap-northeast-1** : ami-0c0a6e1daeb3f7a9c 
+* **sa-east-1** : ami-01e0c5e30e94ec887 
+* **ca-central-1** : ami-07a31896832734897 
+* **ap-southeast-1** : ami-0886d5b2d4b7fccd5 
+* **ap-southeast-2** : ami-0397d5a2db3c356fe 
+* **eu-central-1** : ami-0629f26eea22f5c17 
+* **us-east-2** : ami-0499c3d7bb45a1a6e 
+* **us-west-1** : ami-02fa8a961a4daf9f0 
+* **us-west-2** : ami-05c711cfab4342468 
+* **us-east-1** : ami-0b97d99a08012c726 
+
+### v0.14.1 (static update)
+
+* **eu-north-1** : ami-036defe1885dced2e 
+* **ap-south-1** : ami-0b403aa1da6a5dc17 
+* **eu-west-3** : ami-0d30c2d330d1255c4 
+* **eu-west-2** : ami-06f0e8d075e50a029 
+* **eu-west-1** : ami-0da721d874f282b6d 
+* **ap-northeast-2** : ami-03bffe94675dd5f8c 
+* **ap-northeast-1** : ami-0f96520d646423673 
+* **sa-east-1** : ami-0c2f706a3b7d97282 
+* **ca-central-1** : ami-0da74525dcfd74e32 
+* **ap-southeast-1** : ami-066368a21cf6d232b 
+* **ap-southeast-2** : ami-0bfd09170067f7318 
+* **eu-central-1** : ami-06aa99b1c41492986 
+* **us-east-2** : ami-065c1880f59d03272 
+* **us-west-1** : ami-0b7f6b896f5058eba 
+* **us-west-2** : ami-0041e10ca68eef29a 
+* **us-east-1** : ami-0b7125e4305bbd7eb 
+
+### v0.14.0 (static update)
+* **eu-north-1** : ami-02de71586ec496e38 
+* **ap-south-1** : ami-074b03849b51852e5 
+* **eu-west-3** : ami-022c388835e0eeb03 
+* **eu-west-2** : ami-0a151c236c6b27707 
+* **eu-west-1** : ami-06de69b06b4e73312 
+* **ap-northeast-2** : ami-0ee821b72d9f669b1 
+* **ap-northeast-1** : ami-03687ae215e64e100 
+* **sa-east-1** : ami-01eb83364b7f667af 
+* **ca-central-1** : ami-02e9b35f9c90377e6 
+* **ap-southeast-1** : ami-0d3ab5ab0048fea51 
+* **ap-southeast-2** : ami-0bd39d908fe3a9e06 
+* **eu-central-1** : ami-0b8638701311b35c4 
+* **us-east-2** : ami-02ff039693fc3a614 
+* **us-west-1** : ami-08634f7dfb608a9a7 
+* **us-west-2** : ami-034d693ef742b9333 
+* **us-east-1** : ami-0b828b05c323dde7f
+
+### v0.13.0 (static update)
+* **eu-north-1** : ami-0d9c74a015e7510d8 
+* **ap-south-1** : ami-02acd6dd0659bb5c1 
+* **eu-west-3** : ami-0f0cc5cb6d9afd194 
+* **eu-west-2** : ami-0298fdc0860206ed9 
+* **eu-west-1** : ami-0cdc072e528401d5e 
+* **ap-northeast-2** : ami-0055579cc95b0e53e 
+* **ap-northeast-1** : ami-0ced7becb9b83b5d0 
+* **sa-east-1** : ami-033345d0f16a1b5e4 
+* **ca-central-1** : ami-06c63b05aed47ae67 
+* **ap-southeast-1** : ami-09f0355f367f30602 
+* **ap-southeast-2** : ami-0bd2314163ce0fba0 
+* **eu-central-1** : ami-05fbae957df63e366 
+* **us-east-2** : ami-050c51b5b4074d3fc 
+* **us-west-1** : ami-06ad513073d4e5a19 
+* **us-west-2** : ami-0c96e1361d1d4ca94 
+* **us-east-1** : ami-07b669040d1eea213 
+
+### v0.12.1 (static update)
+* **eu-north-1** : ami-003118a8103286d84 
+* **ap-south-1** : ami-02dfe86baa48e096f 
+* **eu-west-3** : ami-0cc1f01267d2a780d 
+* **eu-west-2** : ami-0e4c8332e5ce09585 
+* **eu-west-1** : ami-03459a2f0b0a3b1ab 
+* **ap-northeast-2** : ami-08f6c2aed3a53f24c 
+* **ap-northeast-1** : ami-0b798eab95a7c5435 
+* **sa-east-1** : ami-0d3ee166c09f0d1b2 
+* **ca-central-1** : ami-00a758c56bd63acd5 
+* **ap-southeast-1** : ami-0be64d4988cd03fbb 
+* **ap-southeast-2** : ami-02087310d43a63f31 
+* **eu-central-1** : ami-097bbefeac0c74225 
+* **us-east-2** : ami-07eda256712b90f4d 
+* **us-west-1** : ami-02ef2b55cbd01c7df 
+* **us-west-2** : ami-037c6176ef4735360 
+* **us-east-1** : ami-08715c20c0e3f1c15 
+
+### v0.12.0 (static update)
+
+* **eu-north-1** : ami-03ff8ab48cd43e77e
+* **ap-south-1** : ami-079c1a41ff836487c
+* **eu-west-3** : ami-0121ef0398ae87ab0
+* **eu-west-2** : ami-09f0f97654d8c79de
+* **eu-west-1** : ami-0b7ba303f757bfcd9
+* **ap-northeast-2** : ami-053f416517b5f40a6
+* **ap-northeast-1** : ami-056dff06c698c2d9d
+* **sa-east-1** : ami-017ab655119258639
+* **ca-central-1** : ami-03bf5fa1d86ac97f6
+* **ap-southeast-1** : ami-0e667958002b0360c
+* **ap-southeast-2** : ami-091f1b69cb43b1933
+* **eu-central-1** : ami-068ec2f0e98c26541
+* **us-east-2** : ami-0524bbdc1b64ff83f
+* **us-west-1** : ami-0b4facd7534e393c9
+* **us-west-2** : ami-0018d5a7e58966848
+* **us-east-1** : ami-08f24178fc14a84d2
+
+### v0.11.0 (static update)
 
-### v0.11.0
 * **eu-north-1** : ami-0cbe338f058018c97
 * **ap-south-1** : ami-06d72ff894f7a5e5d
 * **eu-west-3** : ami-00f2a45d67df2d2f3
@@ -102,7 +239,8 @@ The following sections provide a list containing AMI Image ID per region for eac
 * **us-west-2** : ami-0e384b6f78bf96ebe
 * **us-east-1** : ami-0a7b46f907d5d9c4a
 
-### v0.10.1
+### v0.10.1 (static update)
+
 * **eu-north-1** : ami-09937ec4d18350c32
 * **ap-south-1** : ami-089d6ba7541ec4c7f
 * **eu-west-3** : ami-0accb1a94bdd5c5c1
@@ -120,7 +258,8 @@ The following sections provide a list containing AMI Image ID per region for eac
 * **us-west-2** : ami-0d1cb8ba7de246ff0
 * **us-east-1** : ami-049ccba6abdb40cba
 
-### v0.10.0
+### v0.10.0 (static update)
+
 * **eu-north-1** : ami-05ba33c763877e54e
 * **ap-south-1** : ami-0529eec569161cae5
 * **eu-west-3** : ami-03cb9396f63e26ff6
@@ -139,7 +278,7 @@ The following sections provide a list containing AMI Image ID per region for eac
 * **us-west-2** : ami-04a522ecb2250fb44
 * **us-east-1** : ami-0a66ddbd50959f91e
 
-### v0.9.0
+### v0.9.0 (static update)
 
 * **us-east-1** : ami-0991ad536ecbacdac
 * **eu-north-1** : ami-07cbcdff501b14afe
@@ -157,3 +296,4 @@ The following sections provide a list containing AMI Image ID per region for eac
 * **us-east-2** : ami-03b01914b07428488
 * **us-west-1** : ami-0cf4768e9d47ed076
 * **us-west-2** : ami-0b145f37da31eb9fb
+

docs/install_gcp.md

@@ -0,0 +1,76 @@
+# Deploying Trains Server on Google Cloud Platform
+
+To easily deploy Trains Server on GCP, use one of our pre-built GCP Custom Images.  
+We provide Custom Images for each released version of Trains Server, see [Released versions](#released-versions) below. 
+
+Once your GCP instance is up and running using our Custom Image, [configure the Trains client](https://github.com/allegroai/trains/blob/master/README.md#configuration) to use your **trains-server**.
+  
+#### Default Trains Server Service ports
+The service port numbers on our Trains Server GCP Custom Image are:
+
+- Web application: `8080`
+- API Server: `8008`
+- File Server: `8081`
+
+#### Default Trains Server Storage paths
+The persistent storage configuration:
+
+- MongoDB: `/opt/trains/data/mongo/`
+- ElasticSearch: `/opt/trains/data/elastic/`
+- File Server: `/mnt/fileserver/`
+
+For examples and use cases, check the [Trains usage examples](https://github.com/allegroai/trains/blob/master/docs/trains_examples.md).
+
+## Importing the Custom Image to your GCP account
+
+In order to launch an instance using the Trains Server GCP Custom Image, you'll need to import the image to your custom images list.
+
+**Note:** there's **no need** to upload the image file to Google Cloud Storage - we already provide links to image files stored in Google Storage
+
+To import the image to your custom images list:
+1. In the Cloud Console, go to the [Images](https://console.cloud.google.com/compute/images) page.
+1. At the top of the page, click **Create image**.
+1. In the **Name** field, specify a unique name for the image.
+1. Optionally, specify an image family for your new image, or configure specific encryption settings for the image.
+1. Click the **Source** menu and select **Cloud Storage file**.
+1. Enter the Trains Server image bucket path (see [Trains Server GCP Custom Image](#released-versions)), for example:
+    `allegro-files/trains-server/trains-server.tar.gz`
+1. Click the **Create** button to import the image. The process can take several minutes depending on the size of the boot disk image.
+
+For more information see [Import the image to your custom images list](https://cloud.google.com/compute/docs/import/import-existing-image#import_image) in the [Compute Engine Documentation](https://cloud.google.com/compute/docs).
+
+## Launching an instance with a Custom Image
+
+For instructions on launching an instance using a GCP Custom Image, see the [Manually importing virtual disks](https://cloud.google.com/compute/docs/import/import-existing-image#overview) in the [Compute Engine Documentation](https://cloud.google.com/compute/docs).
+For more information on Custom Images, see [Custom Images](https://cloud.google.com/compute/docs/images#custom_images) in the Compute Engine Documentation.
+
+The minimum recommended requirements for Trains Server are:
+- 2 vCPUs
+- 7.5GB RAM
+
+## Upgrading
+
+To upgrade **trains-server** on an existing GCP instance based on one of these Custom Images, SSH into the instance and follow the [upgrade instructions](../README.md#upgrade) for **trains-server**.
+
+## Network and Security
+
+Please make sure your instance is properly secured. 
+
+If not specifically set, a GCP instance will use default firewall rules that allow public access to various ports. 
+If your instance is open for public access, we recommend you follow best practices for access management, including:
+- Allow access only to the specific ports used by Trains Server (see [Default Trains Server Service ports](#default-trains-server-service-ports)). Remember to allow access to port `443` if `https` access is configured for your instance.
+- Configure Trains Server to use fixed user names and passwords (see [Can I add web login authentication to trains-server?](./faq.md#web-auth))    
+
+## Released versions
+
+The following sections contain lists of Custom Image URLs (exported in different formats) for each released **trains-server** version.
+
+### Latest version image
+
+- https://storage.googleapis.com/allegro-files/trains-server/trains-server.tar.gz
+
+### All released images 
+
+- v0.15.1 - https://storage.googleapis.com/allegro-files/trains-server/trains-server-0-15-1.tar.gz
+- v0.15.0 - https://storage.googleapis.com/allegro-files/trains-server/trains-server-0-15-0.tar.gz
+- v0.14.1 - https://storage.googleapis.com/allegro-files/trains-server/trains-server-0-14-1.tar.gz

docs/install_linux_mac.md

@@ -0,0 +1,97 @@
+# Launching the **trains-server** Docker in Linux or macOS
+
+For Linux or macOS, use our pre-built Docker image for easy deployment. The latest Docker images can be found [here](https://hub.docker.com/r/allegroai/trains).
+
+For Linux users:
+
+* You must be logged in as a user with sudo privileges.
+* Use `bash` for all command-line instructions in this installation.
+
+To launch **trains-server** on Linux or macOS:
+
+1. Install Docker.
+
+    * Linux - see [Docker for Ubuntu](https://docs.docker.com/install/linux/docker-ce/ubuntu/).
+    * macOS - see [Docker for macOS](https://docs.docker.com/docker-for-mac/install/).
+
+1. Verify the Docker CE installation. Execute the command:
+
+        docker run hello-world
+
+    The expected is output is:
+
+        Hello from Docker!
+        This message shows that your installation appears to be working correctly.
+        To generate this message, Docker took the following steps:
+
+        1. The Docker client contacted the Docker daemon.
+        2. The Docker daemon pulled the "hello-world" image from the Docker Hub. (amd64)
+        3. The Docker daemon created a new container from that image which runs the executable that produces the output you are currently reading.
+        4. The Docker daemon streamed that output to the Docker client, which sent it to your terminal.
+
+1. For Linux only, install `docker-compose`. Execute the following commands (for more information, see [Install Docker Compose](https://docs.docker.com/compose/install/) in the Docker documentation):
+
+        sudo curl -L "https://github.com/docker/compose/releases/download/1.24.1/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
+        sudo chmod +x /usr/local/bin/docker-compose
+
+1. Increase `vm.max_map_count` for ElasticSearch docker.
+
+    Linux:
+
+        echo "vm.max_map_count=262144" > /tmp/99-trains.conf
+        sudo mv /tmp/99-trains.conf /etc/sysctl.d/99-trains.conf
+        sudo sysctl -w vm.max_map_count=262144
+        sudo service docker restart
+
+    macOS:
+
+        screen ~/Library/Containers/com.docker.docker/Data/vms/0/tty
+        sysctl -w vm.max_map_count=262144
+
+
+1. Remove any previous installation of **trains-server**.
+
+    **WARNING**: This clears all existing **Trains** databases.
+
+        sudo rm -R /opt/trains/
+
+1. Create local directories for the databases and storage.
+
+        sudo mkdir -p /opt/trains/data/elastic
+        sudo mkdir -p /opt/trains/data/mongo/db
+        sudo mkdir -p /opt/trains/data/mongo/configdb
+        sudo mkdir -p /opt/trains/data/redis
+        sudo mkdir -p /opt/trains/logs
+        sudo mkdir -p /opt/trains/config
+        sudo mkdir -p /opt/trains/data/fileserver
+
+1. For macOS only, open the Docker app, select **Preferences**, and then on the **File Sharing** tab, add `/opt/trains`.
+
+1. Grant access to the Dockers.
+
+    Linux:
+
+        sudo chown -R 1000:1000 /opt/trains
+
+    macOS:
+
+        sudo chown -R $(whoami):staff /opt/trains
+
+1. Download the **trains-server** docker-compose YAML file.
+
+        cd /opt/trains
+        curl https://raw.githubusercontent.com/allegroai/trains-server/master/docker-compose.yml -o docker-compose.yml
+
+1. Run `docker-compose` with the downloaded configuration file.
+
+        docker-compose -f docker-compose.yml up
+
+    Your server is now running on [http://localhost:8080](http://localhost:8080) and the following ports are available:
+
+    * Web server on port `8080`
+    * API server on port `8008`
+    * File server on port `8081`
+
+## Next Step
+
+Configure the [Trains client for trains-server](https://github.com/allegroai/trains/blob/master/README.md#configuration).

docs/install_win.md

@@ -0,0 +1,50 @@
+# Launching the **trains-server** Docker in Windows 10
+
+For Windows, we recommend launching our pre-built Docker image on a Linux virtual machine. 
+However, you can launch **trains-server** on Windows 10 using Docker Desktop for Windows (see the Docker [System Requirements](https://docs.docker.com/docker-for-windows/install/#system-requirements)).
+
+To launch **trains-server** on Windows 10:
+
+1. Install the Docker Desktop for Windows application by either:
+
+    * Following the [Install Docker Desktop on Windows](https://docs.docker.com/docker-for-windows/install/) instructions.
+    * Running the Docker installation [wizard](https://hub.docker.com/?overlay=onboarding).
+
+1. Increase the memory allocation in Docker Desktop to `4GB`.
+
+    1. In your Windows notification area (system tray), right click the Docker icon.
+    
+    1. Click *Settings*, *Advanced*, and then set the memory to at least `4096`. 
+    
+    1. Click *Apply*.
+    
+1. Remove any previous installation of **trains-server**.
+
+    **WARNING**: This clears all existing **Trains** databases.
+
+        rmdir c:\opt\trains /s
+
+1. Create local directories for data and logs. Open PowerShell and execute the following commands:
+
+        cd c:
+        mkdir c:\opt\trains\data
+        mkdir c:\opt\trains\logs
+
+1. Save the **trains-server** docker-compose YAML file.
+ 
+        cd c:\opt\trains
+        curl https://raw.githubusercontent.com/allegroai/trains-server/master/docker-compose-win10.yml -o docker-compose-win10.yml 
+ 
+1. Run `docker-compose`. In PowerShell, execute the following commands:
+
+        docker-compose -f docker-compose-win10.yml up
+   
+    Your server is now running on [http://localhost:8080](http://localhost:8080) and the following ports are available:
+
+    * Web server on port `8080`
+    * API server on port `8008`
+    * File server on port `8081`
+
+## Next Step
+
+Configure the [Trains client for trains-server](https://github.com/allegroai/trains/blob/master/README.md#configuration).

docs/services.conf

@@ -0,0 +1,9 @@
+tasks {
+    non_responsive_tasks_watchdog {
+        # In-progress tasks that haven't been updated for at least 'value' seconds will be stopped by the watchdog
+        threshold_sec: 7200
+
+        # Watchdog will sleep for this number of seconds after each cycle
+        watch_interval_sec: 900
+    }
+}

fileserver/config/basic.py

@@ -1,4 +1,5 @@
 import logging
+import os
 from functools import reduce
 from os import getenv
 from os.path import expandvars
@@ -16,6 +17,9 @@ DEFAULT_EXTRA_CONFIG_PATH = "/opt/trains/config"
 EXTRA_CONFIG_PATH_ENV_KEY = "TRAINS_CONFIG_DIR"
 EXTRA_CONFIG_PATH_SEP = ":"
 
+EXTRA_CONFIG_VALUES_ENV_KEY_SEP = "__"
+EXTRA_CONFIG_VALUES_ENV_KEY_PREFIX = f"TRAINS{EXTRA_CONFIG_VALUES_ENV_KEY_SEP}"
+
 
 class BasicConfig:
     NotSet = object()
@@ -46,7 +50,23 @@ class BasicConfig:
         path = ".".join((self.prefix, Path(name).stem))
         return logging.getLogger(path)
 
-    def _read_env_paths(self, key):
+    @staticmethod
+    def _read_extra_env_config_values():
+        """ Loads extra configuration from environment-injected values """
+        result = ConfigTree()
+        prefix = EXTRA_CONFIG_VALUES_ENV_KEY_PREFIX
+
+        keys = sorted(k for k in os.environ if k.startswith(prefix))
+        for key in keys:
+            path = key[len(prefix) :].replace(EXTRA_CONFIG_VALUES_ENV_KEY_SEP, ".").lower()
+            result = ConfigTree.merge_configs(
+                result, ConfigFactory.parse_string(f"{path}: {os.environ[key]}")
+            )
+
+        return result
+
+    @staticmethod
+    def _read_env_paths(key):
         value = getenv(EXTRA_CONFIG_PATH_ENV_KEY, DEFAULT_EXTRA_CONFIG_PATH)
         if value is None:
             return
@@ -64,12 +84,17 @@ class BasicConfig:
 
     def _load(self, verbose=True):
         extra_config_paths = self._read_env_paths(EXTRA_CONFIG_PATH_ENV_KEY) or []
+        extra_config_values = self._read_extra_env_config_values()
+        configs = [
+            self._read_recursive(path, verbose=verbose)
+            for path in [self.folder] + extra_config_paths
+        ]
 
         self._config = reduce(
-            lambda config, path: ConfigTree.merge_configs(
-                config, self._read_recursive(path, verbose=verbose), copy_trees=True
+            lambda last, config: ConfigTree.merge_configs(
+                last, config, copy_trees=True
             ),
-            [self.folder] + extra_config_paths,
+            configs + [extra_config_values],
             ConfigTree(),
         )
 

fileserver/config/default/fileserver.conf

@@ -1,6 +1,9 @@
 download {
     # Add response headers requesting no caching for served files
     disable_browser_caching: false
+
+    # Cache timeout to be set for downloaded files
+    cache_timeout_sec: 300
 }
 
 cors {

fileserver/fileserver.py

@@ -10,10 +10,15 @@ from flask_cors import CORS
 
 from config import config
 
+DEFAULT_UPLOAD_FOLDER = "/mnt/fileserver"
+
 app = Flask(__name__)
 CORS(app, **config.get("fileserver.cors"))
 Compress(app)
 
+app.config["UPLOAD_FOLDER"] = os.environ.get("TRAINS_UPLOAD_FOLDER") or DEFAULT_UPLOAD_FOLDER
+app.config["SEND_FILE_MAX_AGE_DEFAULT"] = config.get("fileserver.download.cache_timeout_sec", 5 * 60)
+
 
 @app.route("/", methods=["POST"])
 def upload():
@@ -54,12 +59,13 @@ def main():
     parser.add_argument(
         "--upload-folder",
         "-u",
-        default="/mnt/fileserver",
+        default=DEFAULT_UPLOAD_FOLDER,
         help="Upload folder (default %(default)s)",
     )
     args = parser.parse_args()
 
-    app.config["UPLOAD_FOLDER"] = args.upload_folder
+    if app.config.get("UPLOAD_FOLDER") is None:
+        app.config["UPLOAD_FOLDER"] = args.upload_folder
 
     app.run(debug=args.debug, host=args.ip, port=args.port, threaded=True)
 

server/api_version.py

@@ -0,0 +1 @@
+__version__ = "2.9.0"

server/apierrors/__init__.py

@@ -47,6 +47,7 @@ _error_codes = {
         128: ('invalid_task_output', 'invalid task output'),
         129: ('task_publish_in_progress', 'Task publish in progress'),
         130: ('task_not_found', 'task not found'),
+        131: ('events_not_added', 'events not added'),
 
         # Models
         200: ('model_error', 'general task error'),
@@ -89,6 +90,8 @@ _error_codes = {
         1003: ('worker_registered', 'worker is already registered'),
         1004: ('worker_not_registered', 'worker is not registered'),
         1005: ('worker_stats_not_found', 'worker stats not found'),
+
+        1104: ('invalid_scroll_id', 'Invalid scroll id'),
     },
 
     (401, 'unauthorized'): {
@@ -105,7 +108,6 @@ _error_codes = {
 
     (403, 'forbidden'): {
         10: ('routing_error', 'forbidden (routing error)'),
-        11: ('missing_routing_header', 'forbidden (missing routing header)'),
         12: ('blocked_internal_endpoint', 'forbidden (blocked internal endpoint)'),
         20: ('role_not_allowed', 'forbidden (not allowed for role)'),
         21: ('no_write_permission', 'forbidden (modification not allowed)'),
@@ -121,6 +123,7 @@ _error_codes = {
         100: ('data_error', 'general data error'),
         101: ('inconsistent_data', 'inconsistent data encountered in document'),
         102: ('database_unavailable', 'database is temporarily unavailable'),
+        110: ('update_failed', 'update failed'),
 
         # Index-related issues
         201: ('missing_index', 'missing internal index'),

server/apimodels/__init__.py

@@ -5,14 +5,15 @@ from typing import Union, Type, Iterable
 
 import jsonmodels.errors
 import six
-import validators
 from jsonmodels import fields
 from jsonmodels.fields import _LazyType, NotSet
 from jsonmodels.models import Base as ModelBase
 from jsonmodels.validators import Enum as EnumValidator
 from luqum.parser import parser, ParseError
+from validators import email as email_validator, domain as domain_validator
 
 from apierrors import errors
+from utilities.json import loads, dumps
 
 
 def make_default(field_cls, default_value):
@@ -66,9 +67,7 @@ class DictField(fields.BaseField):
             value_types = tuple()
 
         return tuple(
-            _LazyType(type_)
-            if isinstance(type_, six.string_types)
-            else type_
+            _LazyType(type_) if isinstance(type_, six.string_types) else type_
             for type_ in value_types
         )
 
@@ -78,6 +77,9 @@ class DictField(fields.BaseField):
         if not self.value_types:
             return
 
+        if not value:
+            return
+
         for item in value.values():
             self.validate_single_value(item)
 
@@ -104,7 +106,7 @@ class IntField(fields.IntField):
 
 
 def validate_lucene_query(value):
-    if value == '':
+    if value == "":
         return
     try:
         parser.parse(value)
@@ -122,6 +124,7 @@ class LuceneQueryField(fields.StringField):
 
 class NullableEnumValidator(EnumValidator):
     """Validator for enums that allows a None value."""
+
     def validate(self, value):
         if value is not None:
             super(NullableEnumValidator, self).validate(value)
@@ -150,10 +153,6 @@ class EnumField(fields.StringField):
 
 
 class ActualEnumField(fields.StringField):
-    @property
-    def types(self):
-        return (self.__enum,)
-
     def __init__(
         self,
         enum_class: Type[Enum],
@@ -164,12 +163,13 @@ class ActualEnumField(fields.StringField):
         **kwargs
     ):
         self.__enum = enum_class
+        self.types = (enum_class,)
         # noinspection PyTypeChecker
         choices = list(enum_class)
         validator_cls = EnumValidator if required else NullableEnumValidator
         validators = [*(validators or []), validator_cls(*choices)]
         super().__init__(
-            default=default and self.parse_value(default),
+            default=self.parse_value(default) if default else NotSet,
             *args,
             required=required,
             validators=validators,
@@ -194,7 +194,7 @@ class EmailField(fields.StringField):
         super().validate(value)
         if value is None:
             return
-        if validators.email(value) is not True:
+        if email_validator(value) is not True:
             raise errors.bad_request.InvalidEmailAddress()
 
 
@@ -203,14 +203,14 @@ class DomainField(fields.StringField):
         super().validate(value)
         if value is None:
             return
-        if validators.domain(value) is not True:
+        if domain_validator(value) is not True:
             raise errors.bad_request.InvalidDomainName()
 
 
-class StringEnum(Enum):
-    def __str__(self):
-        return self.value
+class JsonSerializableMixin:
+    def to_json(self: ModelBase):
+        return dumps(self.to_struct())
 
-    # noinspection PyMethodParameters
-    def _generate_next_value_(name, start, count, last_values):
-        return name
+    @classmethod
+    def from_json(cls: Type[ModelBase], s):
+        return cls(**loads(s))

server/apimodels/base.py

@@ -1,7 +1,8 @@
 from jsonmodels import models, fields
+from jsonmodels.validators import Length
 from mongoengine.base import BaseDocument
 
-from apimodels import DictField
+from apimodels import DictField, ListField
 
 
 class MongoengineFieldsDict(DictField):
@@ -12,14 +13,14 @@ class MongoengineFieldsDict(DictField):
     """
 
     mongoengine_update_operators = (
-        'inc',
-        'dec',
-        'push',
-        'push_all',
-        'pop',
-        'pull',
-        'pull_all',
-        'add_to_set',
+        "inc",
+        "dec",
+        "push",
+        "push_all",
+        "pop",
+        "pull",
+        "pull_all",
+        "add_to_set",
     )
 
     @staticmethod
@@ -30,16 +31,16 @@ class MongoengineFieldsDict(DictField):
 
     @classmethod
     def _normalize_mongo_field_path(cls, path, value):
-        parts = path.split('__')
+        parts = path.split("__")
         if len(parts) > 1:
-            if parts[0] == 'set':
+            if parts[0] == "set":
                 parts = parts[1:]
-            elif parts[0] == 'unset':
+            elif parts[0] == "unset":
                 parts = parts[1:]
                 value = None
             elif parts[0] in cls.mongoengine_update_operators:
                 return None, None
-        return '.'.join(parts), cls._normalize_mongo_value(value)
+        return ".".join(parts), cls._normalize_mongo_value(value)
 
     def parse_value(self, value):
         value = super(MongoengineFieldsDict, self).parse_value(value)
@@ -58,3 +59,11 @@ class UpdateResponse(models.Base):
 class PagedRequest(models.Base):
     page = fields.IntField()
     page_size = fields.IntField()
+
+
+class IdResponse(models.Base):
+    id = fields.StringField(required=True)
+
+
+class MakePublicRequest(models.Base):
+    ids = ListField(items_types=str, validators=[Length(minimum_value=1)])

server/apimodels/events.py

@@ -1,14 +1,20 @@
-from typing import Sequence
+from enum import auto
+from typing import Sequence, Optional
 
-from jsonmodels.fields import StringField
+from jsonmodels import validators
+from jsonmodels.fields import StringField, BoolField
 from jsonmodels.models import Base
+from jsonmodels.validators import Length, Min, Max
 
 from apimodels import ListField, IntField, ActualEnumField
+from bll.event.event_metrics import EventType
 from bll.event.scalar_key import ScalarKeyEnum
+from config import config
+from utilities.stringenum import StringEnum
 
 
 class HistogramRequestBase(Base):
-    samples: int = IntField(default=10000)
+    samples: int = IntField(default=6000, validators=[Min(1), Max(6000)])
     key: ScalarKeyEnum = ActualEnumField(ScalarKeyEnum, default=ScalarKeyEnum.iter)
 
 
@@ -17,4 +23,65 @@ class ScalarMetricsIterHistogramRequest(HistogramRequestBase):
 
 
 class MultiTaskScalarMetricsIterHistogramRequest(HistogramRequestBase):
-    tasks: Sequence[str] = ListField(items_types=str)
+    tasks: Sequence[str] = ListField(
+        items_types=str,
+        validators=[
+            Length(
+                minimum_value=1,
+                maximum_value=config.get(
+                    "services.tasks.multi_task_histogram_limit", 10
+                ),
+            )
+        ],
+    )
+
+
+class TaskMetric(Base):
+    task: str = StringField(required=True)
+    metric: str = StringField(required=True)
+
+
+class DebugImagesRequest(Base):
+    metrics: Sequence[TaskMetric] = ListField(
+        items_types=TaskMetric, validators=[Length(minimum_value=1)]
+    )
+    iters: int = IntField(default=1, validators=validators.Min(1))
+    navigate_earlier: bool = BoolField(default=True)
+    refresh: bool = BoolField(default=False)
+    scroll_id: str = StringField()
+
+
+class LogOrderEnum(StringEnum):
+    asc = auto()
+    desc = auto()
+
+
+class LogEventsRequest(Base):
+    task: str = StringField(required=True)
+    batch_size: int = IntField(default=500)
+    navigate_earlier: bool = BoolField(default=True)
+    from_timestamp: Optional[int] = IntField()
+    order: Optional[str] = ActualEnumField(LogOrderEnum)
+
+
+class IterationEvents(Base):
+    iter: int = IntField()
+    events: Sequence[dict] = ListField(items_types=dict)
+
+
+class MetricEvents(Base):
+    task: str = StringField()
+    metric: str = StringField()
+    iterations: Sequence[IterationEvents] = ListField(items_types=IterationEvents)
+
+
+class DebugImageResponse(Base):
+    metrics: Sequence[MetricEvents] = ListField(items_types=MetricEvents)
+    scroll_id: str = StringField()
+
+
+class TaskMetricsRequest(Base):
+    tasks: Sequence[str] = ListField(
+        items_types=str, validators=[Length(minimum_value=1)]
+    )
+    event_type: EventType = ActualEnumField(EventType, required=True)

server/apimodels/models.py

@@ -6,10 +6,14 @@ from apimodels.base import UpdateResponse
 from apimodels.tasks import PublishResponse as TaskPublishResponse
 
 
+class GetFrameworksRequest(models.Base):
+    projects = fields.ListField(items_types=[str])
+
+
 class CreateModelRequest(models.Base):
     name = fields.StringField(required=True)
     uri = fields.StringField(required=True)
-    labels = DictField(value_types=string_types+(int,), required=True)
+    labels = DictField(value_types=string_types+(int,))
     tags = ListField(items_types=string_types)
     system_tags = ListField(items_types=string_types)
     comment = fields.StringField()

server/apimodels/organization.py

@@ -0,0 +1,11 @@
+from jsonmodels import fields, models
+
+
+class Filter(models.Base):
+    tags = fields.ListField([str])
+    system_tags = fields.ListField([str])
+
+
+class TagsRequest(models.Base):
+    include_system = fields.BoolField(default=False)
+    filter = fields.EmbeddedField(Filter)

server/apimodels/projects.py

@@ -1,5 +1,8 @@
 from jsonmodels import models, fields
 
+from apimodels import ListField
+from apimodels.organization import TagsRequest
+
 
 class ProjectReq(models.Base):
     project = fields.StringField()
@@ -10,7 +13,5 @@ class GetHyperParamReq(ProjectReq):
     page_size = fields.IntField(default=500)
 
 
-class GetHyperParamResp(models.Base):
-    parameters = fields.ListField(str)
-    remaining = fields.IntField()
-    total = fields.IntField()
+class ProjectTagsRequest(TagsRequest):
+    projects = ListField(str)

server/apimodels/server.py

@@ -0,0 +1,15 @@
+from jsonmodels.fields import BoolField, DateTimeField, StringField
+from jsonmodels.models import Base
+
+
+class ReportStatsOptionRequest(Base):
+    enabled = BoolField(default=None, nullable=True)
+
+
+class ReportStatsOptionResponse(Base):
+    supported = BoolField(default=True)
+    enabled = BoolField()
+    enabled_time = DateTimeField(nullable=True)
+    enabled_version = StringField(nullable=True)
+    enabled_user = StringField(nullable=True)
+    current_version = StringField()

server/apimodels/tasks.py

@@ -1,7 +1,9 @@
+from typing import Sequence
+
 import six
 from jsonmodels import models
-from jsonmodels.fields import StringField, BoolField, IntField
-from jsonmodels.validators import Enum
+from jsonmodels.fields import StringField, BoolField, IntField, EmbeddedField
+from jsonmodels.validators import Enum, Length
 
 from apimodels import DictField, ListField
 from apimodels.base import UpdateResponse
@@ -9,6 +11,24 @@ from database.model.task.task import TaskType
 from database.utils import get_options
 
 
+class ArtifactTypeData(models.Base):
+    preview = StringField()
+    content_type = StringField()
+    data_hash = StringField()
+
+
+class Artifact(models.Base):
+    key = StringField(required=True)
+    type = StringField(required=True)
+    mode = StringField(validators=Enum("input", "output"), default="output")
+    uri = StringField()
+    hash = StringField()
+    content_size = IntField()
+    timestamp = IntField()
+    type_data = EmbeddedField(ArtifactTypeData)
+    display_data = ListField([list])
+
+
 class StartedResponse(UpdateResponse):
     started = IntField()
 
@@ -72,3 +92,102 @@ class CreateRequest(TaskData):
 
 class PingRequest(TaskRequest):
     pass
+
+
+class GetTypesRequest(models.Base):
+    projects = ListField(items_types=[str])
+
+
+class CloneRequest(TaskRequest):
+    new_task_name = StringField()
+    new_task_comment = StringField()
+    new_task_tags = ListField([str])
+    new_task_system_tags = ListField([str])
+    new_task_parent = StringField()
+    new_task_project = StringField()
+    new_hyperparams = DictField()
+    new_configuration = DictField()
+    execution_overrides = DictField()
+    validate_references = BoolField(default=False)
+
+
+class AddOrUpdateArtifactsRequest(TaskRequest):
+    artifacts = ListField([Artifact], required=True)
+
+
+class AddOrUpdateArtifactsResponse(models.Base):
+    added = ListField([str])
+    updated = ListField([str])
+
+
+class ResetRequest(UpdateRequest):
+    clear_all = BoolField(default=False)
+
+
+class MultiTaskRequest(models.Base):
+    tasks = ListField([str], validators=Length(minimum_value=1))
+
+
+class GetHyperParamsRequest(MultiTaskRequest):
+    pass
+
+
+class HyperParamItem(models.Base):
+    section = StringField(required=True, validators=Length(minimum_value=1))
+    name = StringField(required=True, validators=Length(minimum_value=1))
+    value = StringField(required=True)
+    type = StringField()
+    description = StringField()
+
+
+class ReplaceHyperparams(object):
+    none = "none"
+    section = "section"
+    all = "all"
+
+
+class EditHyperParamsRequest(TaskRequest):
+    hyperparams: Sequence[HyperParamItem] = ListField(
+        [HyperParamItem], validators=Length(minimum_value=1)
+    )
+    replace_hyperparams = StringField(
+        validators=Enum(*get_options(ReplaceHyperparams)),
+        default=ReplaceHyperparams.none,
+    )
+
+
+class HyperParamKey(models.Base):
+    section = StringField(required=True, validators=Length(minimum_value=1))
+    name = StringField(nullable=True)
+
+
+class DeleteHyperParamsRequest(TaskRequest):
+    hyperparams: Sequence[HyperParamKey] = ListField(
+        [HyperParamKey], validators=Length(minimum_value=1)
+    )
+
+
+class GetConfigurationsRequest(MultiTaskRequest):
+    names = ListField([str])
+
+
+class GetConfigurationNamesRequest(MultiTaskRequest):
+    pass
+
+
+class Configuration(models.Base):
+    name = StringField(required=True, validators=Length(minimum_value=1))
+    value = StringField(required=True)
+    type = StringField()
+    description = StringField()
+
+
+class EditConfigurationRequest(TaskRequest):
+    configuration: Sequence[Configuration] = ListField(
+        [Configuration], validators=Length(minimum_value=1)
+    )
+    replace_configuration = BoolField(default=False)
+
+
+class DeleteConfigurationRequest(TaskRequest):
+    configuration: Sequence[str] = ListField([str], validators=Length(minimum_value=1))

server/apimodels/workers.py

@@ -1,4 +1,3 @@
-import json
 from enum import Enum
 
 import six
@@ -13,13 +12,14 @@ from jsonmodels.fields import (
 )
 from jsonmodels.models import Base
 
-from apimodels import make_default, ListField, EnumField
+from apimodels import make_default, ListField, EnumField, JsonSerializableMixin
 
 DEFAULT_TIMEOUT = 10 * 60
 
 
 class WorkerRequest(Base):
     worker = StringField(required=True)
+    tags = ListField(str)
 
 
 class RegisterRequest(WorkerRequest):
@@ -61,26 +61,21 @@ class IdNameEntry(Base):
     name = StringField()
 
 
-class WorkerEntry(Base):
+class WorkerEntry(Base, JsonSerializableMixin):
     key = StringField()  # not required due to migration issues
     id = StringField(required=True)
     user = EmbeddedField(IdNameEntry)
     company = EmbeddedField(IdNameEntry)
     ip = StringField()
     task = EmbeddedField(IdNameEntry)
+    project = EmbeddedField(IdNameEntry)
     queue = StringField()  # queue from which current task was taken
     queues = ListField(str)  # list of queues this worker listens to
     register_time = DateTimeField(required=True)
     register_timeout = IntField(required=True)
     last_activity_time = DateTimeField(required=True)
     last_report_time = DateTimeField()
-
-    def to_json(self):
-        return json.dumps(self.to_struct())
-
-    @classmethod
-    def from_json(cls, s):
-        return cls(**json.loads(s))
+    tags = ListField(str)
 
 
 class CurrentTaskEntry(IdNameEntry):

server/bll/event/debug_images_iterator.py

@@ -0,0 +1,467 @@
+from collections import defaultdict
+from concurrent.futures.thread import ThreadPoolExecutor
+from functools import partial
+from itertools import chain
+from operator import attrgetter, itemgetter
+from typing import Sequence, Tuple, Optional, Mapping
+
+import attr
+import dpath
+from boltons.iterutils import bucketize
+from elasticsearch import Elasticsearch
+from jsonmodels.fields import StringField, ListField, IntField
+from jsonmodels.models import Base
+from redis import StrictRedis
+
+from apierrors import errors
+from apimodels import JsonSerializableMixin
+from bll.event.event_metrics import EventMetrics
+from bll.redis_cache_manager import RedisCacheManager
+from config import config
+from database.errors import translate_errors_context
+from database.model.task.metrics import MetricEventStats
+from database.model.task.task import Task
+from timing_context import TimingContext
+
+
+class VariantScrollState(Base):
+    name: str = StringField(required=True)
+    recycle_url_marker: str = StringField()
+    last_invalid_iteration: int = IntField()
+
+
+class MetricScrollState(Base):
+    task: str = StringField(required=True)
+    name: str = StringField(required=True)
+    last_min_iter: Optional[int] = IntField()
+    last_max_iter: Optional[int] = IntField()
+    timestamp: int = IntField(default=0)
+    variants: Sequence[VariantScrollState] = ListField([VariantScrollState])
+
+    def reset(self):
+        """Reset the scrolling state for the metric"""
+        self.last_min_iter = self.last_max_iter = None
+
+
+class DebugImageEventsScrollState(Base, JsonSerializableMixin):
+    id: str = StringField(required=True)
+    metrics: Sequence[MetricScrollState] = ListField([MetricScrollState])
+
+
+@attr.s(auto_attribs=True)
+class DebugImagesResult(object):
+    metric_events: Sequence[tuple] = []
+    next_scroll_id: str = None
+
+
+class DebugImagesIterator:
+    EVENT_TYPE = "training_debug_image"
+
+    @property
+    def state_expiration_sec(self):
+        return config.get(
+            f"services.events.events_retrieval.state_expiration_sec", 3600
+        )
+
+    @property
+    def _max_workers(self):
+        return config.get("services.events.max_metrics_concurrency", 4)
+
+    def __init__(self, redis: StrictRedis, es: Elasticsearch):
+        self.es = es
+        self.cache_manager = RedisCacheManager(
+            state_class=DebugImageEventsScrollState,
+            redis=redis,
+            expiration_interval=self.state_expiration_sec,
+        )
+
+    def get_task_events(
+        self,
+        company_id: str,
+        metrics: Sequence[Tuple[str, str]],
+        iter_count: int,
+        navigate_earlier: bool = True,
+        refresh: bool = False,
+        state_id: str = None,
+    ) -> DebugImagesResult:
+        es_index = EventMetrics.get_index_name(company_id, self.EVENT_TYPE)
+        if not self.es.indices.exists(es_index):
+            return DebugImagesResult()
+
+        def init_state(state_: DebugImageEventsScrollState):
+            unique_metrics = set(metrics)
+            state_.metrics = self._init_metric_states(es_index, list(unique_metrics))
+
+        def validate_state(state_: DebugImageEventsScrollState):
+            """
+            Validate that the metrics stored in the state are the same
+            as requested in the current call.
+            Refresh the state if requested
+            """
+            state_metrics = set((m.task, m.name) for m in state_.metrics)
+            if state_metrics != set(metrics):
+                raise errors.bad_request.InvalidScrollId(
+                    "Task metrics stored in the state do not match the passed ones",
+                    scroll_id=state_.id,
+                )
+            if refresh:
+                self._reinit_outdated_metric_states(company_id, es_index, state_)
+                for metric_state in state_.metrics:
+                    metric_state.reset()
+
+        with self.cache_manager.get_or_create_state(
+            state_id=state_id, init_state=init_state, validate_state=validate_state
+        ) as state:
+            res = DebugImagesResult(next_scroll_id=state.id)
+            with ThreadPoolExecutor(self._max_workers) as pool:
+                res.metric_events = list(
+                    pool.map(
+                        partial(
+                            self._get_task_metric_events,
+                            es_index=es_index,
+                            iter_count=iter_count,
+                            navigate_earlier=navigate_earlier,
+                        ),
+                        state.metrics,
+                    )
+                )
+
+            return res
+
+    def _reinit_outdated_metric_states(
+        self, company_id, es_index, state: DebugImageEventsScrollState
+    ):
+        """
+        Determines the metrics for which new debug image events were added
+        since their states were initialized and reinits these states
+        """
+        task_ids = set(metric.task for metric in state.metrics)
+        tasks = Task.objects(id__in=list(task_ids), company=company_id).only(
+            "id", "metric_stats"
+        )
+
+        def get_last_update_times_for_task_metrics(task: Task) -> Sequence[Tuple]:
+            """For metrics that reported debug image events get tuples of task_id/metric_name and last update times"""
+            metric_stats: Mapping[str, MetricEventStats] = task.metric_stats
+            if not metric_stats:
+                return []
+
+            return [
+                (
+                    (task.id, stats.metric),
+                    stats.event_stats_by_type[self.EVENT_TYPE].last_update,
+                )
+                for stats in metric_stats.values()
+                if self.EVENT_TYPE in stats.event_stats_by_type
+            ]
+
+        update_times = dict(
+            chain.from_iterable(
+                get_last_update_times_for_task_metrics(task) for task in tasks
+            )
+        )
+        outdated_metrics = [
+            metric
+            for metric in state.metrics
+            if (metric.task, metric.name) in update_times
+            and update_times[metric.task, metric.name] > metric.timestamp
+        ]
+        state.metrics = [
+            *(metric for metric in state.metrics if metric not in outdated_metrics),
+            *(
+                self._init_metric_states(
+                    es_index,
+                    [(metric.task, metric.name) for metric in outdated_metrics],
+                )
+            ),
+        ]
+
+    def _init_metric_states(
+        self, es_index, metrics: Sequence[Tuple[str, str]]
+    ) -> Sequence[MetricScrollState]:
+        """
+        Returned initialized metric scroll stated for the requested task metrics
+        """
+        tasks = defaultdict(list)
+        for (task, metric) in metrics:
+            tasks[task].append(metric)
+
+        with ThreadPoolExecutor(self._max_workers) as pool:
+            return list(
+                chain.from_iterable(
+                    pool.map(
+                        partial(self._init_metric_states_for_task, es_index=es_index),
+                        tasks.items(),
+                    )
+                )
+            )
+
+    def _init_metric_states_for_task(
+        self, task_metrics: Tuple[str, Sequence[str]], es_index
+    ) -> Sequence[MetricScrollState]:
+        """
+        Return metric scroll states for the task filled with the variant states
+        for the variants that reported any debug images
+        """
+        task, metrics = task_metrics
+        es_req: dict = {
+            "size": 0,
+            "query": {
+                "bool": {
+                    "must": [
+                        {"term": {"task": task}},
+                        {"terms": {"metric": metrics}},
+                        {"exists": {"field": "url"}},
+                    ]
+                }
+            },
+            "aggs": {
+                "metrics": {
+                    "terms": {
+                        "field": "metric",
+                        "size": EventMetrics.MAX_METRICS_COUNT,
+                    },
+                    "aggs": {
+                        "last_event_timestamp": {"max": {"field": "timestamp"}},
+                        "variants": {
+                            "terms": {
+                                "field": "variant",
+                                "size": EventMetrics.MAX_VARIANTS_COUNT,
+                            },
+                            "aggs": {
+                                "urls": {
+                                    "terms": {
+                                        "field": "url",
+                                        "order": {"max_iter": "desc"},
+                                        "size": 1,  # we need only one url from the most recent iteration
+                                    },
+                                    "aggs": {
+                                        "max_iter": {"max": {"field": "iter"}},
+                                        "iters": {
+                                            "top_hits": {
+                                                "sort": {"iter": {"order": "desc"}},
+                                                "size": 2,  # need two last iterations so that we can take
+                                                # the second one as invalid
+                                                "_source": "iter",
+                                            }
+                                        },
+                                    },
+                                }
+                            },
+                        },
+                    },
+                }
+            },
+        }
+
+        with translate_errors_context(), TimingContext("es", "_init_metric_states"):
+            es_res = self.es.search(index=es_index, body=es_req)
+        if "aggregations" not in es_res:
+            return []
+
+        def init_variant_scroll_state(variant: dict):
+            """
+            Return new variant scroll state for the passed variant bucket
+            If the image urls get recycled then fill the last_invalid_iteration field
+            """
+            state = VariantScrollState(name=variant["key"])
+            top_iter_url = dpath.get(variant, "urls/buckets")[0]
+            iters = dpath.get(top_iter_url, "iters/hits/hits")
+            if len(iters) > 1:
+                state.last_invalid_iteration = dpath.get(iters[1], "_source/iter")
+            return state
+
+        return [
+            MetricScrollState(
+                task=task,
+                name=metric["key"],
+                variants=[
+                    init_variant_scroll_state(variant)
+                    for variant in dpath.get(metric, "variants/buckets")
+                ],
+                timestamp=dpath.get(metric, "last_event_timestamp/value"),
+            )
+            for metric in dpath.get(es_res, "aggregations/metrics/buckets")
+        ]
+
+    def _get_task_metric_events(
+        self,
+        metric: MetricScrollState,
+        es_index: str,
+        iter_count: int,
+        navigate_earlier: bool,
+    ) -> Tuple:
+        """
+        Return task metric events grouped by iterations
+        Update metric scroll state
+        """
+        if metric.last_max_iter is None:
+            # the first fetch is always from the latest iteration to the earlier ones
+            navigate_earlier = True
+
+        must_conditions = [
+            {"term": {"task": metric.task}},
+            {"term": {"metric": metric.name}},
+            {"exists": {"field": "url"}},
+        ]
+        must_not_conditions = []
+
+        range_condition = None
+        if navigate_earlier and metric.last_min_iter is not None:
+            range_condition = {"lt": metric.last_min_iter}
+        elif not navigate_earlier and metric.last_max_iter is not None:
+            range_condition = {"gt": metric.last_max_iter}
+        if range_condition:
+            must_conditions.append({"range": {"iter": range_condition}})
+
+        if navigate_earlier:
+            """
+            When navigating to earlier iterations consider only
+            variants whose invalid iterations border is lower than
+            our starting iteration. For these variants make sure
+            that only events from the valid iterations are returned 
+            """
+            if not metric.last_min_iter:
+                variants = metric.variants
+            else:
+                variants = list(
+                    v
+                    for v in metric.variants
+                    if v.last_invalid_iteration is None
+                    or v.last_invalid_iteration < metric.last_min_iter
+                )
+                if not variants:
+                    return metric.task, metric.name, []
+                must_conditions.append(
+                    {"terms": {"variant": list(v.name for v in variants)}}
+                )
+        else:
+            """
+            When navigating to later iterations all variants may be relevant.
+            For the variants whose invalid border is higher than our starting 
+            iteration make sure that only events from valid iterations are returned 
+            """
+            variants = list(
+                v
+                for v in metric.variants
+                if v.last_invalid_iteration is not None
+                and v.last_invalid_iteration > metric.last_max_iter
+            )
+
+        variants_conditions = [
+            {
+                "bool": {
+                    "must": [
+                        {"term": {"variant": v.name}},
+                        {"range": {"iter": {"lte": v.last_invalid_iteration}}},
+                    ]
+                }
+            }
+            for v in variants
+            if v.last_invalid_iteration is not None
+        ]
+        if variants_conditions:
+            must_not_conditions.append({"bool": {"should": variants_conditions}})
+
+        es_req = {
+            "size": 0,
+            "query": {
+                "bool": {"must": must_conditions, "must_not": must_not_conditions}
+            },
+            "aggs": {
+                "iters": {
+                    "terms": {
+                        "field": "iter",
+                        "size": iter_count,
+                        "order": {"_key": "desc" if navigate_earlier else "asc"},
+                    },
+                    "aggs": {
+                        "variants": {
+                            "terms": {
+                                "field": "variant",
+                                "size": EventMetrics.MAX_VARIANTS_COUNT,
+                            },
+                            "aggs": {
+                                "events": {
+                                    "top_hits": {"sort": {"url": {"order": "desc"}}}
+                                }
+                            },
+                        }
+                    },
+                }
+            },
+        }
+        with translate_errors_context(), TimingContext("es", "get_debug_image_events"):
+            es_res = self.es.search(index=es_index, body=es_req)
+        if "aggregations" not in es_res:
+            return metric.task, metric.name, []
+
+        def get_iteration_events(variant_buckets: Sequence[dict]) -> Sequence:
+            return [
+                ev["_source"]
+                for v in variant_buckets
+                for ev in dpath.get(v, "events/hits/hits")
+            ]
+
+        iterations = [
+            {
+                "iter": it["key"],
+                "events": get_iteration_events(dpath.get(it, "variants/buckets")),
+            }
+            for it in dpath.get(es_res, "aggregations/iters/buckets")
+        ]
+        if not navigate_earlier:
+            iterations.sort(key=itemgetter("iter"), reverse=True)
+        if iterations:
+            metric.last_max_iter = iterations[0]["iter"]
+            metric.last_min_iter = iterations[-1]["iter"]
+
+        # Commented for now since the last invalid iteration is calculated in the beginning
+        # if navigate_earlier and any(
+        #     variant.last_invalid_iteration is None for variant in variants
+        # ):
+        #     """
+        #     Variants validation flags due to recycling can
+        #     be set only on navigation to earlier frames
+        #     """
+        #     iterations = self._update_variants_invalid_iterations(variants, iterations)
+
+        return metric.task, metric.name, iterations
+
+    @staticmethod
+    def _update_variants_invalid_iterations(
+        variants: Sequence[VariantScrollState], iterations: Sequence[dict]
+    ) -> Sequence[dict]:
+        """
+        This code is currently not in used since the invalid iterations
+        are calculated during MetricState initialization
+        For variants that do not have recycle url marker set it from the
+        first event
+        For variants that do not have last_invalid_iteration set check if the
+        recycle marker was reached on a certain iteration and set it to the
+        corresponding iteration
+        For variants that have a newly set last_invalid_iteration remove
+        events from the invalid iterations
+        Return the updated iterations list
+        """
+        variants_lookup = bucketize(variants, attrgetter("name"))
+        for it in iterations:
+            iteration = it["iter"]
+            events_to_remove = []
+            for event in it["events"]:
+                variant = variants_lookup[event["variant"]][0]
+                if (
+                    variant.last_invalid_iteration
+                    and variant.last_invalid_iteration >= iteration
+                ):
+                    events_to_remove.append(event)
+                    continue
+                event_url = event.get("url")
+                if not variant.recycle_url_marker:
+                    variant.recycle_url_marker = event_url
+                elif variant.recycle_url_marker == event_url:
+                    variant.last_invalid_iteration = iteration
+                    events_to_remove.append(event)
+            if events_to_remove:
+                it["events"] = [ev for ev in it["events"] if ev not in events_to_remove]
+        return [it for it in iterations if it["events"]]

server/bll/event/event_bll.py

@@ -1,11 +1,10 @@
+import hashlib
 from collections import defaultdict
 from contextlib import closing
 from datetime import datetime
-from enum import Enum
 from operator import attrgetter
-from typing import Sequence
+from typing import Sequence, Set, Tuple, Optional
 
-import attr
 import six
 from elasticsearch import helpers
 from mongoengine import Q
@@ -14,67 +13,94 @@ from nested_dict import nested_dict
 import database.utils as dbutils
 import es_factory
 from apierrors import errors
-from bll.event.event_metrics import EventMetrics
+from bll.event.debug_images_iterator import DebugImagesIterator
+from bll.event.event_metrics import EventMetrics, EventType
+from bll.event.log_events_iterator import LogEventsIterator, TaskEventsResult
 from bll.task import TaskBLL
+from config import config
 from database.errors import translate_errors_context
 from database.model.task.task import Task, TaskStatus
+from redis_manager import redman
 from timing_context import TimingContext
+from tools import safe_get
 from utilities.dicts import flatten_nested_items
 
-
-class EventType(Enum):
-    metrics_scalar = "training_stats_scalar"
-    metrics_vector = "training_stats_vector"
-    metrics_image = "training_debug_image"
-    metrics_plot = "plot"
-    task_log = "log"
-
-
 # noinspection PyTypeChecker
 EVENT_TYPES = set(map(attrgetter("value"), EventType))
-
-
 LOCKED_TASK_STATUSES = (TaskStatus.publishing, TaskStatus.published)
 
 
-@attr.s
-class TaskEventsResult(object):
-    events = attr.ib(type=list, default=attr.Factory(list))
-    total_events = attr.ib(type=int, default=0)
-    next_scroll_id = attr.ib(type=str, default=None)
-
-
 class EventBLL(object):
-    id_fields = ["task", "iter", "metric", "variant", "key"]
+    id_fields = ("task", "iter", "metric", "variant", "key")
+    empty_scroll = "FFFF"
 
-    def __init__(self, events_es=None):
+    def __init__(self, events_es=None, redis=None):
         self.es = events_es or es_factory.connect("events")
         self._metrics = EventMetrics(self.es)
+        self._skip_iteration_for_metric = set(
+            config.get("services.events.ignore_iteration.metrics", [])
+        )
+        self.redis = redis or redman.connection("apiserver")
+        self.debug_images_iterator = DebugImagesIterator(es=self.es, redis=self.redis)
+        self.log_events_iterator = LogEventsIterator(es=self.es)
 
     @property
     def metrics(self) -> EventMetrics:
         return self._metrics
 
-    def add_events(self, company_id, events, worker, allow_locked_tasks=False):
+    @staticmethod
+    def _get_valid_tasks(company_id, task_ids: Set, allow_locked_tasks=False) -> Set:
+        """Verify that task exists and can be updated"""
+        if not task_ids:
+            return set()
+
+        with translate_errors_context(), TimingContext("mongo", "task_by_ids"):
+            query = Q(id__in=task_ids, company=company_id)
+            if not allow_locked_tasks:
+                query &= Q(status__nin=LOCKED_TASK_STATUSES)
+            res = Task.objects(query).only("id")
+            return {r.id for r in res}
+
+    def add_events(
+        self, company_id, events, worker, allow_locked_tasks=False
+    ) -> Tuple[int, int, dict]:
         actions = []
         task_ids = set()
         task_iteration = defaultdict(lambda: 0)
-        task_last_events = nested_dict(
+        task_last_scalar_events = nested_dict(
             3, dict
         )  # task_id -> metric_hash -> variant_hash -> MetricEvent
-
+        task_last_events = nested_dict(
+            3, dict
+        )  # task_id -> metric_hash -> event_type -> MetricEvent
+        errors_per_type = defaultdict(int)
+        valid_tasks = self._get_valid_tasks(
+            company_id,
+            task_ids={
+                event["task"] for event in events if event.get("task") is not None
+            },
+            allow_locked_tasks=allow_locked_tasks,
+        )
         for event in events:
             # remove spaces from event type
-            if "type" not in event:
-                raise errors.BadRequest("Event must have a 'type' field", event=event)
+            event_type = event.get("type")
+            if event_type is None:
+                errors_per_type["Event must have a 'type' field"] += 1
+                continue
 
-            event_type = event["type"].replace(" ", "_")
+            event_type = event_type.replace(" ", "_")
             if event_type not in EVENT_TYPES:
-                raise errors.BadRequest(
-                    "Invalid event type {}".format(event_type),
-                    event=event,
-                    types=EVENT_TYPES,
-                )
+                errors_per_type[f"Invalid event type {event_type}"] += 1
+                continue
+
+            task_id = event.get("task")
+            if task_id is None:
+                errors_per_type["Event must have a 'task' field"] += 1
+                continue
+
+            if task_id not in valid_tasks:
+                errors_per_type["Invalid task id"] += 1
+                continue
 
             event["type"] = event_type
 
@@ -103,11 +129,13 @@ class EventBLL(object):
                 event["value"] = event["values"]
                 del event["values"]
 
+            event["metric"] = event.get("metric") or ""
+            event["variant"] = event.get("variant") or ""
+
             index_name = EventMetrics.get_index_name(company_id, event_type)
             es_action = {
                 "_op_type": "index",  # overwrite if exists with same ID
                 "_index": index_name,
-                "_type": "event",
                 "_source": event,
             }
 
@@ -117,89 +145,81 @@ class EventBLL(object):
             else:
                 es_action["_id"] = dbutils.id()
 
-            task_id = event.get("task")
-            if task_id is not None:
-                es_action["_routing"] = task_id
-                task_ids.add(task_id)
-                if iter is not None:
-                    task_iteration[task_id] = max(iter, task_iteration[task_id])
+            task_ids.add(task_id)
+            if (
+                iter is not None
+                and event.get("metric") not in self._skip_iteration_for_metric
+            ):
+                task_iteration[task_id] = max(iter, task_iteration[task_id])
 
-                if event_type == EventType.metrics_scalar.value:
-                    self._update_last_metric_event_for_task(
-                        task_last_events=task_last_events, task_id=task_id, event=event
-                    )
-            else:
-                es_action["_routing"] = task_id
+            self._update_last_metric_events_for_task(
+                last_events=task_last_events[task_id], event=event,
+            )
+            if event_type == EventType.metrics_scalar.value:
+                self._update_last_scalar_events_for_task(
+                    last_events=task_last_scalar_events[task_id], event=event
+                )
 
             actions.append(es_action)
 
-        if task_ids:
-            # verify task_ids
-            with translate_errors_context(), TimingContext("mongo", "task_by_ids"):
-                extra_msg = None
-                query = Q(id__in=task_ids, company=company_id)
-                if not allow_locked_tasks:
-                    query &= Q(status__nin=LOCKED_TASK_STATUSES)
-                    extra_msg = "or task published"
-                res = Task.objects(query).only("id")
-                if len(res) < len(task_ids):
-                    invalid_task_ids = tuple(set(task_ids) - set(r.id for r in res))
-                    raise errors.bad_request.InvalidTaskId(
-                        extra_msg, company=company_id, ids=invalid_task_ids
+        added = 0
+        if actions:
+            chunk_size = 500
+            with translate_errors_context(), TimingContext("es", "events_add_batch"):
+                # TODO: replace it with helpers.parallel_bulk in the future once the parallel pool leak is fixed
+                with closing(
+                    helpers.streaming_bulk(
+                        self.es,
+                        actions,
+                        chunk_size=chunk_size,
+                        # thread_count=8,
+                        refresh=True,
+                    )
+                ) as it:
+                    for success, info in it:
+                        if success:
+                            added += chunk_size
+                        else:
+                            errors_per_type["Error when indexing events batch"] += 1
+
+                remaining_tasks = set()
+                now = datetime.utcnow()
+                for task_id in task_ids:
+                    # Update related tasks. For reasons of performance, we prefer to update
+                    # all of them and not only those who's events were successful
+                    updated = self._update_task(
+                        company_id=company_id,
+                        task_id=task_id,
+                        now=now,
+                        iter_max=task_iteration.get(task_id),
+                        last_scalar_events=task_last_scalar_events.get(task_id),
+                        last_events=task_last_events.get(task_id),
                     )
 
-        errors_in_bulk = []
-        added = 0
-        chunk_size = 500
-        with translate_errors_context(), TimingContext("es", "events_add_batch"):
-            # TODO: replace it with helpers.parallel_bulk in the future once the parallel pool leak is fixed
-            with closing(
-                helpers.streaming_bulk(
-                    self.es,
-                    actions,
-                    chunk_size=chunk_size,
-                    # thread_count=8,
-                    refresh=True,
-                )
-            ) as it:
-                for success, info in it:
-                    if success:
-                        added += chunk_size
-                    else:
-                        errors_in_bulk.append(info)
+                    if not updated:
+                        remaining_tasks.add(task_id)
+                        continue
 
-            remaining_tasks = set()
-            now = datetime.utcnow()
-            for task_id in task_ids:
-                # Update related tasks. For reasons of performance, we prefer to update all of them and not only those
-                #  who's events were successful
-
-                updated = self._update_task(
-                    company_id=company_id,
-                    task_id=task_id,
-                    now=now,
-                    iter_max=task_iteration.get(task_id),
-                    last_events=task_last_events.get(task_id),
-                )
-
-                if not updated:
-                    remaining_tasks.add(task_id)
-                    continue
-
-            if remaining_tasks:
-                TaskBLL.set_last_update(remaining_tasks, company_id, last_update=now)
+                if remaining_tasks:
+                    TaskBLL.set_last_update(
+                        remaining_tasks, company_id, last_update=now
+                    )
 
         # Compensate for always adding chunk_size on success (last chunk is probably smaller)
         added = min(added, len(actions))
 
-        return added, errors_in_bulk
+        if not added:
+            raise errors.bad_request.EventsNotAdded(**errors_per_type)
 
-    def _update_last_metric_event_for_task(self, task_last_events, task_id, event):
+        errors_count = sum(errors_per_type.values())
+        return added, errors_count, errors_per_type
+
+    def _update_last_scalar_events_for_task(self, last_events, event):
         """
-        Update task_last_events structure for the provided task_id with the provided event details if this event is more
+        Update last_events structure with the provided event details if this event is more
         recent than the currently stored event for its metric/variant combination.
 
-        task_last_events contains [hashed_metric_name -> hashed_variant_name -> event]. Keys are hashed to avoid mongodb
+        last_events contains [hashed_metric_name -> hashed_variant_name -> event]. Keys are hashed to avoid mongodb
         key conflicts due to invalid characters and/or long field names.
         """
         metric = event.get("metric")
@@ -210,13 +230,50 @@ class EventBLL(object):
         metric_hash = dbutils.hash_field_name(metric)
         variant_hash = dbutils.hash_field_name(variant)
 
-        last_events = task_last_events[task_id]
+        last_event = last_events[metric_hash][variant_hash]
+        event_iter = event.get("iter", 0)
+        event_timestamp = event.get("timestamp", 0)
+        value = event.get("value")
+        if value is not None and (
+            (event_iter, event_timestamp)
+            >= (
+                last_event.get("iter", event_iter),
+                last_event.get("timestamp", event_timestamp),
+            )
+        ):
+            event_data = {
+                k: event[k]
+                for k in ("value", "metric", "variant", "iter", "timestamp")
+                if k in event
+            }
+            event_data["min_value"] = min(value, last_event.get("min_value", value))
+            event_data["max_value"] = max(value, last_event.get("max_value", value))
+            last_events[metric_hash][variant_hash] = event_data
 
-        timestamp = last_events[metric_hash][variant_hash].get("timestamp", None)
+    def _update_last_metric_events_for_task(self, last_events, event):
+        """
+        Update last_events structure with the provided event details if this event is more
+        recent than the currently stored event for its metric/event_type combination.
+        last_events contains [metric_name -> event_type -> event]
+        """
+        metric = event.get("metric")
+        event_type = event.get("type")
+        if not (metric and event_type):
+            return
+
+        timestamp = last_events[metric][event_type].get("timestamp", None)
         if timestamp is None or timestamp < event["timestamp"]:
-            last_events[metric_hash][variant_hash] = event
+            last_events[metric][event_type] = event
 
-    def _update_task(self, company_id, task_id, now, iter_max=None, last_events=None):
+    def _update_task(
+        self,
+        company_id,
+        task_id,
+        now,
+        iter_max=None,
+        last_scalar_events=None,
+        last_events=None,
+    ):
         """
         Update task information in DB with aggregated results after handling event(s) related to this task.
 
@@ -229,15 +286,24 @@ class EventBLL(object):
         if iter_max is not None:
             fields["last_iteration_max"] = iter_max
 
-        if last_events:
-            fields["last_values"] = list(
+        if last_scalar_events:
+            fields["last_scalar_values"] = list(
                 flatten_nested_items(
-                    last_events,
+                    last_scalar_events,
                     nesting=2,
-                    include_leaves=["value", "metric", "variant"],
+                    include_leaves=[
+                        "value",
+                        "min_value",
+                        "max_value",
+                        "metric",
+                        "variant",
+                    ],
                 )
             )
 
+        if last_events:
+            fields["last_events"] = last_events
+
         if not fields:
             return False
 
@@ -245,7 +311,7 @@ class EventBLL(object):
 
     def _get_event_id(self, event):
         id_values = (str(event[field]) for field in self.id_fields if field in event)
-        return "-".join(id_values)
+        return hashlib.md5("-".join(id_values).encode()).hexdigest()
 
     def scroll_task_events(
         self,
@@ -256,6 +322,9 @@ class EventBLL(object):
         batch_size=10000,
         scroll_id=None,
     ):
+        if scroll_id == self.empty_scroll:
+            return [], scroll_id, 0
+
         if scroll_id:
             with translate_errors_context(), TimingContext("es", "task_log_events"):
                 es_res = self.es.scroll(scroll_id=scroll_id, scroll="1h")
@@ -278,10 +347,7 @@ class EventBLL(object):
             with translate_errors_context(), TimingContext("es", "scroll_task_events"):
                 es_res = self.es.search(index=es_index, body=es_req, scroll="1h")
 
-        events = [hit["_source"] for hit in es_res["hits"]["hits"]]
-        next_scroll_id = es_res["_scroll_id"]
-        total_events = es_res["hits"]["total"]
-
+        events, total_events, next_scroll_id = self._get_events_from_es_res(es_res)
         return events, next_scroll_id, total_events
 
     def get_last_iterations_per_event_metric_variant(
@@ -294,16 +360,22 @@ class EventBLL(object):
             "size": 0,
             "aggs": {
                 "metrics": {
-                    "terms": {"field": "metric"},
+                    "terms": {
+                        "field": "metric",
+                        "size": EventMetrics.MAX_METRICS_COUNT,
+                    },
                     "aggs": {
                         "variants": {
-                            "terms": {"field": "variant"},
+                            "terms": {
+                                "field": "variant",
+                                "size": EventMetrics.MAX_VARIANTS_COUNT,
+                            },
                             "aggs": {
                                 "iters": {
                                     "terms": {
                                         "field": "iter",
                                         "size": num_last_iterations,
-                                        "order": {"_term": "desc"},
+                                        "order": {"_key": "desc"},
                                     }
                                 }
                             },
@@ -319,7 +391,7 @@ class EventBLL(object):
         with translate_errors_context(), TimingContext(
             "es", "task_last_iter_metric_variant"
         ):
-            es_res = self.es.search(index=es_index, body=es_req, routing=task_id)
+            es_res = self.es.search(index=es_index, body=es_req)
         if "aggregations" not in es_res:
             return []
 
@@ -339,6 +411,9 @@ class EventBLL(object):
         size: int = 500,
         scroll_id: str = None,
     ):
+        if scroll_id == self.empty_scroll:
+            return [], scroll_id, 0
+
         if scroll_id:
             with translate_errors_context(), TimingContext("es", "get_task_events"):
                 es_res = self.es.scroll(scroll_id=scroll_id, scroll="1h")
@@ -348,13 +423,11 @@ class EventBLL(object):
             if not self.es.indices.exists(es_index):
                 return TaskEventsResult()
 
-            query = {"bool": defaultdict(list)}
-
+            must = []
             if last_iterations_per_plot is None:
-                must = query["bool"]["must"]
                 must.append({"terms": {"task": tasks}})
             else:
-                should = query["bool"]["should"]
+                should = []
                 for i, task_id in enumerate(tasks):
                     last_iters = self.get_last_iterations_per_event_metric_variant(
                         es_index, task_id, last_iterations_per_plot, event_type
@@ -377,32 +450,41 @@ class EventBLL(object):
                         )
                 if not should:
                     return TaskEventsResult()
+                must.append({"bool": {"should": should}})
 
             if sort is None:
                 sort = [{"timestamp": {"order": "asc"}}]
 
-            es_req = {"sort": sort, "size": min(size, 10000), "query": query}
-
-            routing = ",".join(tasks)
+            es_req = {
+                "sort": sort,
+                "size": min(size, 10000),
+                "query": {"bool": {"must": must}},
+            }
 
             with translate_errors_context(), TimingContext("es", "get_task_plots"):
                 es_res = self.es.search(
-                    index=es_index,
-                    body=es_req,
-                    ignore=404,
-                    routing=routing,
-                    scroll="1h",
+                    index=es_index, body=es_req, ignore=404, scroll="1h",
                 )
 
-        events = [doc["_source"] for doc in es_res.get("hits", {}).get("hits", [])]
-        # scroll id may be missing when queering a totally empty DB
-        next_scroll_id = es_res.get("_scroll_id")
-        total_events = es_res["hits"]["total"]
-
+        events, total_events, next_scroll_id = self._get_events_from_es_res(es_res)
         return TaskEventsResult(
             events=events, next_scroll_id=next_scroll_id, total_events=total_events
         )
 
+    def _get_events_from_es_res(self, es_res: dict) -> Tuple[list, int, Optional[str]]:
+        """
+        Return events and next scroll id from the scrolled query
+        Release the scroll once it is exhausted
+        """
+        total_events = safe_get(es_res, "hits/total/value", default=0)
+        events = [doc["_source"] for doc in safe_get(es_res, "hits/hits", default=[])]
+        next_scroll_id = es_res.get("_scroll_id")
+        if next_scroll_id and not events:
+            self.es.clear_scroll(scroll_id=next_scroll_id)
+            next_scroll_id = self.empty_scroll
+
+        return events, total_events, next_scroll_id
+
     def get_task_events(
         self,
         company_id,
@@ -415,6 +497,8 @@ class EventBLL(object):
         size=500,
         scroll_id=None,
     ):
+        if scroll_id == self.empty_scroll:
+            return [], scroll_id, 0
 
         if scroll_id:
             with translate_errors_context(), TimingContext("es", "get_task_events"):
@@ -428,20 +512,16 @@ class EventBLL(object):
             if not self.es.indices.exists(es_index):
                 return TaskEventsResult()
 
-            query = {"bool": defaultdict(list)}
-
-            if metric or variant:
-                must = query["bool"]["must"]
-                if metric:
-                    must.append({"term": {"metric": metric}})
-                if variant:
-                    must.append({"term": {"variant": variant}})
+            must = []
+            if metric:
+                must.append({"term": {"metric": metric}})
+            if variant:
+                must.append({"term": {"variant": variant}})
 
             if last_iter_count is None:
-                must = query["bool"]["must"]
                 must.append({"terms": {"task": task_ids}})
             else:
-                should = query["bool"]["should"]
+                should = []
                 for i, task_id in enumerate(task_ids):
                     last_iters = self.get_last_iters(
                         es_index, task_id, event_type, last_iter_count
@@ -460,27 +540,23 @@ class EventBLL(object):
                     )
                 if not should:
                     return TaskEventsResult()
+                must.append({"bool": {"should": should}})
 
             if sort is None:
                 sort = [{"timestamp": {"order": "asc"}}]
 
-            es_req = {"sort": sort, "size": min(size, 10000), "query": query}
-
-            routing = ",".join(task_ids)
+            es_req = {
+                "sort": sort,
+                "size": min(size, 10000),
+                "query": {"bool": {"must": must}},
+            }
 
             with translate_errors_context(), TimingContext("es", "get_task_events"):
                 es_res = self.es.search(
-                    index=es_index,
-                    body=es_req,
-                    ignore=404,
-                    routing=routing,
-                    scroll="1h",
+                    index=es_index, body=es_req, ignore=404, scroll="1h",
                 )
 
-        events = [doc["_source"] for doc in es_res.get("hits", {}).get("hits", [])]
-        next_scroll_id = es_res["_scroll_id"]
-        total_events = es_res["hits"]["total"]
-
+        events, total_events, next_scroll_id = self._get_events_from_es_res(es_res)
         return TaskEventsResult(
             events=events, next_scroll_id=next_scroll_id, total_events=total_events
         )
@@ -496,8 +572,18 @@ class EventBLL(object):
             "size": 0,
             "aggs": {
                 "metrics": {
-                    "terms": {"field": "metric", "size": 200},
-                    "aggs": {"variants": {"terms": {"field": "variant", "size": 200}}},
+                    "terms": {
+                        "field": "metric",
+                        "size": EventMetrics.MAX_METRICS_COUNT,
+                    },
+                    "aggs": {
+                        "variants": {
+                            "terms": {
+                                "field": "variant",
+                                "size": EventMetrics.MAX_VARIANTS_COUNT,
+                            }
+                        }
+                    },
                 }
             },
             "query": {"bool": {"must": [{"term": {"task": task_id}}]}},
@@ -506,7 +592,7 @@ class EventBLL(object):
         with translate_errors_context(), TimingContext(
             "es", "events_get_metrics_and_variants"
         ):
-            es_res = self.es.search(index=es_index, body=es_req, routing=task_id)
+            es_res = self.es.search(index=es_index, body=es_req)
 
         metrics = {}
         for metric_bucket in es_res["aggregations"]["metrics"].get("buckets"):
@@ -537,15 +623,15 @@ class EventBLL(object):
                 "metrics": {
                     "terms": {
                         "field": "metric",
-                        "size": 1000,
-                        "order": {"_term": "asc"},
+                        "size": EventMetrics.MAX_METRICS_COUNT,
+                        "order": {"_key": "asc"},
                     },
                     "aggs": {
                         "variants": {
                             "terms": {
                                 "field": "variant",
-                                "size": 1000,
-                                "order": {"_term": "asc"},
+                                "size": EventMetrics.MAX_VARIANTS_COUNT,
+                                "order": {"_key": "asc"},
                             },
                             "aggs": {
                                 "last_value": {
@@ -575,7 +661,7 @@ class EventBLL(object):
         with translate_errors_context(), TimingContext(
             "es", "events_get_metrics_and_variants"
         ):
-            es_res = self.es.search(index=es_index, body=es_req, routing=task_id)
+            es_res = self.es.search(index=es_index, body=es_req)
 
         metrics = []
         max_timestamp = 0
@@ -622,7 +708,7 @@ class EventBLL(object):
             "sort": ["iter"],
         }
         with translate_errors_context(), TimingContext("es", "task_stats_vector"):
-            es_res = self.es.search(index=es_index, body=es_req, routing=task_id)
+            es_res = self.es.search(index=es_index, body=es_req)
 
         vectors = []
         iterations = []
@@ -643,7 +729,7 @@ class EventBLL(object):
                     "terms": {
                         "field": "iter",
                         "size": iters,
-                        "order": {"_term": "desc"},
+                        "order": {"_key": "desc"},
                     }
                 }
             },
@@ -653,7 +739,7 @@ class EventBLL(object):
             es_req["query"]["bool"]["must"].append({"term": {"type": event_type}})
 
         with translate_errors_context(), TimingContext("es", "task_last_iter"):
-            es_res = self.es.search(index=es_index, body=es_req, routing=task_id)
+            es_res = self.es.search(index=es_index, body=es_req)
         if "aggregations" not in es_res:
             return []
 
@@ -675,8 +761,6 @@ class EventBLL(object):
         es_index = EventMetrics.get_index_name(company_id, "*")
         es_req = {"query": {"term": {"task": task_id}}}
         with translate_errors_context(), TimingContext("es", "delete_task_events"):
-            es_res = self.es.delete_by_query(
-                index=es_index, body=es_req, routing=task_id, refresh=True
-            )
+            es_res = self.es.delete_by_query(index=es_index, body=es_req, refresh=True)
 
         return es_res.get("deleted", 0)

server/bll/event/event_metrics.py

@@ -1,12 +1,13 @@
 import itertools
+import math
 from collections import defaultdict
-from concurrent.futures import ThreadPoolExecutor
+from concurrent.futures.thread import ThreadPoolExecutor
+from enum import Enum
 from functools import partial
 from operator import itemgetter
+from typing import Sequence, Tuple
 
 from elasticsearch import Elasticsearch
-from typing import Sequence, Tuple, Callable
-
 from mongoengine import Q
 
 from apierrors import errors
@@ -15,19 +16,32 @@ from config import config
 from database.errors import translate_errors_context
 from database.model.task.task import Task
 from timing_context import TimingContext
-from utilities import safe_get
+from tools import safe_get
 
 log = config.logger(__file__)
 
 
+class EventType(Enum):
+    metrics_scalar = "training_stats_scalar"
+    metrics_vector = "training_stats_vector"
+    metrics_image = "training_debug_image"
+    metrics_plot = "plot"
+    task_log = "log"
+
+
 class EventMetrics:
-    MAX_TASKS_COUNT = 100
-    MAX_METRICS_COUNT = 200
-    MAX_VARIANTS_COUNT = 500
+    MAX_METRICS_COUNT = 100
+    MAX_VARIANTS_COUNT = 100
+    MAX_AGGS_ELEMENTS_COUNT = 50
+    MAX_SAMPLE_BUCKETS = 6000
 
     def __init__(self, es: Elasticsearch):
         self.es = es
 
+    @property
+    def _max_concurrency(self):
+        return config.get("services.events.max_metrics_concurrency", 4)
+
     @staticmethod
     def get_index_name(company_id, event_type):
         event_type = event_type.lower().replace(" ", "_")
@@ -41,15 +55,48 @@ class EventMetrics:
         The amount of points in each histogram should not exceed
         the requested samples
         """
+        es_index = self.get_index_name(company_id, "training_stats_scalar")
+        if not self.es.indices.exists(es_index):
+            return {}
 
-        return self._run_get_scalar_metrics_as_parallel(
-            company_id,
-            task_ids=[task_id],
-            samples=samples,
-            key=ScalarKey.resolve(key),
-            get_func=self._get_scalar_average,
+        return self._get_scalar_average_per_iter_core(
+            task_id, es_index, samples, ScalarKey.resolve(key)
         )
 
+    def _get_scalar_average_per_iter_core(
+        self,
+        task_id: str,
+        es_index: str,
+        samples: int,
+        key: ScalarKey,
+        run_parallel: bool = True,
+    ) -> dict:
+        intervals = self._get_task_metric_intervals(
+            es_index=es_index, task_id=task_id, samples=samples, field=key.field
+        )
+        if not intervals:
+            return {}
+        interval_groups = self._group_task_metric_intervals(intervals)
+
+        get_scalar_average = partial(
+            self._get_scalar_average, task_id=task_id, es_index=es_index, key=key
+        )
+        if run_parallel:
+            with ThreadPoolExecutor(max_workers=self._max_concurrency) as pool:
+                metrics = itertools.chain.from_iterable(
+                    pool.map(get_scalar_average, interval_groups)
+                )
+        else:
+            metrics = itertools.chain.from_iterable(
+                get_scalar_average(group) for group in interval_groups
+            )
+
+        ret = defaultdict(dict)
+        for metric_key, metric_values in metrics:
+            ret[metric_key].update(metric_values)
+
+        return ret
+
     def compare_scalar_metrics_average_per_iter(
         self,
         company_id,
@@ -68,118 +115,109 @@ class EventMetrics:
                 company=company_id,
                 query=Q(id__in=task_ids),
                 allow_public=allow_public,
-                override_projection=("id", "name"),
+                override_projection=("id", "name", "company"),
                 return_dicts=False,
             )
             if len(task_objs) < len(task_ids):
                 invalid = tuple(set(task_ids) - set(r.id for r in task_objs))
                 raise errors.bad_request.InvalidTaskId(company=company_id, ids=invalid)
-
             task_name_by_id = {t.id: t.name for t in task_objs}
 
-        ret = self._run_get_scalar_metrics_as_parallel(
-            company_id,
-            task_ids=task_ids,
-            samples=samples,
-            key=ScalarKey.resolve(key),
-            get_func=self._get_scalar_average_per_task,
-        )
+        companies = {t.company for t in task_objs}
+        if len(companies) > 1:
+            raise errors.bad_request.InvalidTaskId(
+                "only tasks from the same company are supported"
+            )
 
-        for metric_data in ret.values():
-            for variant_data in metric_data.values():
-                for task_id, task_data in variant_data.items():
-                    task_data["name"] = task_name_by_id[task_id]
-
-        return ret
-
-    TaskMetric = Tuple[str, str, str]
-
-    MetricInterval = Tuple[int, Sequence[TaskMetric]]
-    MetricData = Tuple[str, dict]
-
-    def _run_get_scalar_metrics_as_parallel(
-        self,
-        company_id: str,
-        task_ids: Sequence[str],
-        samples: int,
-        key: ScalarKey,
-        get_func: Callable[
-            [MetricInterval, Sequence[str], str, ScalarKey], Sequence[MetricData]
-        ],
-    ) -> dict:
-        """
-        Group metrics per interval length and execute get_func for each group in parallel
-        :param company_id: id of the company
-        :params task_ids: ids of the tasks to collect data for
-        :param samples: maximum number of samples per metric
-        :param get_func: callable that given metric names for the same interval
-        performs histogram aggregation for the metrics and return the aggregated data
-        """
-        es_index = self.get_index_name(company_id, "training_stats_scalar")
+        es_index = self.get_index_name(next(iter(companies)), "training_stats_scalar")
         if not self.es.indices.exists(es_index):
             return {}
 
-        intervals = self._get_metric_intervals(
-            es_index=es_index, task_ids=task_ids, samples=samples, field=key.field
+        get_scalar_average_per_iter = partial(
+            self._get_scalar_average_per_iter_core,
+            es_index=es_index,
+            samples=samples,
+            key=ScalarKey.resolve(key),
+            run_parallel=False,
         )
-
-        if not intervals:
-            return {}
-
-        with ThreadPoolExecutor(len(intervals)) as pool:
-            metrics = list(
-                itertools.chain.from_iterable(
-                    pool.map(
-                        partial(
-                            get_func, task_ids=task_ids, es_index=es_index, key=key
-                        ),
-                        intervals,
-                    )
-                )
+        with ThreadPoolExecutor(max_workers=self._max_concurrency) as pool:
+            task_metrics = zip(
+                task_ids, pool.map(get_scalar_average_per_iter, task_ids)
             )
 
-        ret = defaultdict(dict)
-        for metric_key, metric_values in metrics:
-            ret[metric_key].update(metric_values)
-        return ret
+        res = defaultdict(lambda: defaultdict(dict))
+        for task_id, task_data in task_metrics:
+            task_name = task_name_by_id[task_id]
+            for metric_key, metric_data in task_data.items():
+                for variant_key, variant_data in metric_data.items():
+                    variant_data["name"] = task_name
+                    res[metric_key][variant_key][task_id] = variant_data
 
-    def _get_metric_intervals(
-        self, es_index, task_ids: Sequence[str], samples: int, field: str = "iter"
+        return res
+
+    MetricInterval = Tuple[str, str, int, int]
+    MetricIntervalGroup = Tuple[int, Sequence[Tuple[str, str]]]
+
+    @classmethod
+    def _group_task_metric_intervals(
+        cls, intervals: Sequence[MetricInterval]
+    ) -> Sequence[MetricIntervalGroup]:
+        """
+        Group task metric intervals so that the following conditions are meat:
+            - All the metrics in the same group have the same interval (with 10% rounding)
+            - The amount of metrics in the group does not exceed MAX_AGGS_ELEMENTS_COUNT
+            - The total count of samples in the group does not exceed MAX_SAMPLE_BUCKETS
+        """
+        metric_interval_groups = []
+        interval_group = []
+        group_interval_upper_bound = 0
+        group_max_interval = 0
+        group_samples = 0
+        for metric, variant, interval, size in sorted(intervals, key=itemgetter(2)):
+            if (
+                interval > group_interval_upper_bound
+                or (group_samples + size) > cls.MAX_SAMPLE_BUCKETS
+                or len(interval_group) >= cls.MAX_AGGS_ELEMENTS_COUNT
+            ):
+                if interval_group:
+                    metric_interval_groups.append((group_max_interval, interval_group))
+                    interval_group = []
+                group_max_interval = interval
+                group_interval_upper_bound = interval + int(interval * 0.1)
+                group_samples = 0
+            interval_group.append((metric, variant))
+            group_samples += size
+            group_max_interval = max(group_max_interval, interval)
+        if interval_group:
+            metric_interval_groups.append((group_max_interval, interval_group))
+
+        return metric_interval_groups
+
+    def _get_task_metric_intervals(
+        self, es_index, task_id: str, samples: int, field: str = "iter"
     ) -> Sequence[MetricInterval]:
         """
         Calculate interval per task metric variant so that the resulting
         amount of points does not exceed sample.
-        Return metric variants grouped by interval value with 10% rounding
-        For samples==0 return empty list
+        Return the list og metric variant intervals as the following tuple:
+        (metric, variant, interval, samples)
         """
-        default_intervals = [(1, [])]
-        if not samples:
-            return default_intervals
-
         es_req = {
             "size": 0,
-            "query": {"terms": {"task": task_ids}},
+            "query": {"term": {"task": task_id}},
             "aggs": {
-                "tasks": {
-                    "terms": {"field": "task", "size": self.MAX_TASKS_COUNT},
+                "metrics": {
+                    "terms": {"field": "metric", "size": self.MAX_METRICS_COUNT},
                     "aggs": {
-                        "metrics": {
+                        "variants": {
                             "terms": {
-                                "field": "metric",
-                                "size": self.MAX_METRICS_COUNT,
+                                "field": "variant",
+                                "size": self.MAX_VARIANTS_COUNT,
                             },
                             "aggs": {
-                                "variants": {
-                                    "terms": {
-                                        "field": "variant",
-                                        "size": self.MAX_VARIANTS_COUNT,
-                                    },
-                                    "aggs": {
-                                        "count": {"value_count": {"field": field}},
-                                        "min_index": {"min": {"field": field}},
-                                        "max_index": {"max": {"field": field}},
-                                    },
-                                }
+                                "count": {"value_count": {"field": field}},
+                                "min_index": {"min": {"field": field}},
+                                "max_index": {"max": {"field": field}},
                             },
                         }
                     },
@@ -188,88 +226,78 @@ class EventMetrics:
         }
 
         with translate_errors_context(), TimingContext("es", "task_stats_get_interval"):
-            es_res = self.es.search(
-                index=es_index, body=es_req, routing=",".join(task_ids)
-            )
+            es_res = self.es.search(index=es_index, body=es_req)
 
         aggs_result = es_res.get("aggregations")
         if not aggs_result:
-            return default_intervals
+            return []
 
-        intervals = [
-            (
-                task["key"],
-                metric["key"],
-                variant["key"],
-                self._calculate_metric_interval(variant, samples),
-            )
-            for task in aggs_result["tasks"]["buckets"]
-            for metric in task["metrics"]["buckets"]
+        return [
+            self._build_metric_interval(metric["key"], variant["key"], variant, samples)
+            for metric in aggs_result["metrics"]["buckets"]
             for variant in metric["variants"]["buckets"]
         ]
 
-        metric_intervals = []
-        upper_border = 0
-        interval_metrics = None
-        for task, metric, variant, interval in sorted(intervals, key=itemgetter(3)):
-            if not interval_metrics or interval > upper_border:
-                interval_metrics = []
-                metric_intervals.append((interval, interval_metrics))
-                upper_border = interval + int(interval * 0.1)
-            interval_metrics.append((task, metric, variant))
-
-        return metric_intervals
-
     @staticmethod
-    def _calculate_metric_interval(metric_variant: dict, samples: int) -> int:
+    def _build_metric_interval(
+        metric: str, variant: str, data: dict, samples: int
+    ) -> Tuple[str, str, int, int]:
         """
         Calculate index interval per metric_variant variant so that the
         total amount of intervals does not exceeds the samples
+        Return the interval and resulting amount of intervals
         """
-        count = safe_get(metric_variant, "count/value")
-        if not count or count < samples:
-            return 1
+        count = safe_get(data, "count/value", default=0)
+        if count < samples:
+            return metric, variant, 1, count
 
-        min_index = safe_get(metric_variant, "min_index/value", default=0)
-        max_index = safe_get(metric_variant, "max_index/value", default=min_index)
-        return max(1, int(max_index - min_index + 1) // samples)
+        min_index = safe_get(data, "min_index/value", default=0)
+        max_index = safe_get(data, "max_index/value", default=min_index)
+        index_range = max_index - min_index + 1
+        interval = max(1, math.ceil(float(index_range) / samples))
+        max_samples = math.ceil(float(index_range) / interval)
+        return (
+            metric,
+            variant,
+            interval,
+            max_samples,
+        )
+
+    MetricData = Tuple[str, dict]
 
     def _get_scalar_average(
         self,
-        metrics_interval: MetricInterval,
-        task_ids: Sequence[str],
+        metrics_interval: MetricIntervalGroup,
+        task_id: str,
         es_index: str,
         key: ScalarKey,
     ) -> Sequence[MetricData]:
         """
         Retrieve scalar histograms per several metric variants that share the same interval
-        Note: the function works with a single task only
         """
-
-        assert len(task_ids) == 1
-        interval, task_metrics = metrics_interval
+        interval, metrics = metrics_interval
         aggregation = self._add_aggregation_average(key.get_aggregation(interval))
         aggs = {
             "metrics": {
                 "terms": {
                     "field": "metric",
                     "size": self.MAX_METRICS_COUNT,
-                    "order": {"_term": "desc"},
+                    "order": {"_key": "desc"},
                 },
                 "aggs": {
                     "variants": {
                         "terms": {
                             "field": "variant",
                             "size": self.MAX_VARIANTS_COUNT,
-                            "order": {"_term": "desc"},
+                            "order": {"_key": "desc"},
                         },
                         "aggs": aggregation,
                     }
                 },
             }
         }
-        aggs_result = self._query_aggregation_for_metrics_and_tasks(
-            es_index, aggs=aggs, task_ids=task_ids, task_metrics=task_metrics
+        aggs_result = self._query_aggregation_for_task_metrics(
+            es_index, aggs=aggs, task_id=task_id, metrics=metrics
         )
 
         if not aggs_result:
@@ -290,55 +318,6 @@ class EventMetrics:
         ]
         return metrics
 
-    def _get_scalar_average_per_task(
-        self,
-        metrics_interval: MetricInterval,
-        task_ids: Sequence[str],
-        es_index: str,
-        key: ScalarKey,
-    ) -> Sequence[MetricData]:
-        """
-        Retrieve scalar histograms per several metric variants that share the same interval
-        """
-        interval, task_metrics = metrics_interval
-
-        aggregation = self._add_aggregation_average(key.get_aggregation(interval))
-        aggs = {
-            "metrics": {
-                "terms": {"field": "metric", "size": self.MAX_METRICS_COUNT},
-                "aggs": {
-                    "variants": {
-                        "terms": {"field": "variant", "size": self.MAX_VARIANTS_COUNT},
-                        "aggs": {
-                            "tasks": {"terms": {"field": "task"}, "aggs": aggregation}
-                        },
-                    }
-                },
-            }
-        }
-
-        aggs_result = self._query_aggregation_for_metrics_and_tasks(
-            es_index, aggs=aggs, task_ids=task_ids, task_metrics=task_metrics
-        )
-
-        if not aggs_result:
-            return {}
-
-        metrics = [
-            (
-                metric["key"],
-                {
-                    variant["key"]: {
-                        task["key"]: key.get_iterations_data(task)
-                        for task in variant["tasks"]["buckets"]
-                    }
-                    for variant in metric["variants"]["buckets"]
-                },
-            )
-            for metric in aggs_result["metrics"]["buckets"]
-        ]
-        return metrics
-
     @staticmethod
     def _add_aggregation_average(aggregation):
         average_agg = {"avg_val": {"avg": {"field": "value"}}}
@@ -347,52 +326,85 @@ class EventMetrics:
             for key, value in aggregation.items()
         }
 
-    def _query_aggregation_for_metrics_and_tasks(
+    def _query_aggregation_for_task_metrics(
         self,
         es_index: str,
         aggs: dict,
-        task_ids: Sequence[str],
-        task_metrics: Sequence[TaskMetric],
+        task_id: str,
+        metrics: Sequence[Tuple[str, str]],
     ) -> dict:
         """
         Return the result of elastic search query for the given aggregation filtered
         by the given task_ids and metrics
         """
-        if task_metrics:
-            condition = {
-                "should": [
-                    self._build_metric_terms(task, metric, variant)
-                    for task, metric, variant in task_metrics
-                ]
-            }
-        else:
-            condition = {"must": [{"terms": {"task": task_ids}}]}
+        must = [{"term": {"task": task_id}}]
+        if metrics:
+            should = [
+                {
+                    "bool": {
+                        "must": [
+                            {"term": {"metric": metric}},
+                            {"term": {"variant": variant}},
+                        ]
+                    }
+                }
+                for metric, variant in metrics
+            ]
+            must.append({"bool": {"should": should}})
+
         es_req = {
             "size": 0,
-            "_source": {"excludes": []},
-            "query": {"bool": condition},
+            "query": {"bool": {"must": must}},
             "aggs": aggs,
-            "version": True,
         }
 
         with translate_errors_context(), TimingContext("es", "task_stats_scalar"):
-            es_res = self.es.search(
-                index=es_index, body=es_req, routing=",".join(task_ids)
-            )
+            es_res = self.es.search(index=es_index, body=es_req)
 
         return es_res.get("aggregations")
 
-    @staticmethod
-    def _build_metric_terms(task: str, metric: str, variant: str) -> dict:
+    def get_tasks_metrics(
+        self, company_id, task_ids: Sequence, event_type: EventType
+    ) -> Sequence:
         """
-        Build query term for a metric + variant
+        For the requested tasks return all the metrics that
+        reported events of the requested types
         """
-        return {
-            "bool": {
-                "must": [
-                    {"term": {"task": task}},
-                    {"term": {"metric": metric}},
-                    {"term": {"variant": variant}},
-                ]
-            }
+        es_index = EventMetrics.get_index_name(company_id, event_type.value)
+        if not self.es.indices.exists(es_index):
+            return {}
+
+        with ThreadPoolExecutor(self._max_concurrency) as pool:
+            res = pool.map(
+                partial(
+                    self._get_task_metrics, es_index=es_index, event_type=event_type,
+                ),
+                task_ids,
+            )
+        return list(zip(task_ids, res))
+
+    def _get_task_metrics(self, task_id, es_index, event_type: EventType) -> Sequence:
+        es_req = {
+            "size": 0,
+            "query": {
+                "bool": {
+                    "must": [
+                        {"term": {"task": task_id}},
+                        {"term": {"type": event_type.value}},
+                    ]
+                }
+            },
+            "aggs": {
+                "metrics": {
+                    "terms": {"field": "metric", "size": self.MAX_METRICS_COUNT}
+                }
+            },
         }
+
+        with translate_errors_context(), TimingContext("es", "_get_task_metrics"):
+            es_res = self.es.search(index=es_index, body=es_req)
+
+        return [
+            metric["key"]
+            for metric in safe_get(es_res, "aggregations/metrics/buckets", default=[])
+        ]

server/bll/event/log_events_iterator.py

@@ -0,0 +1,114 @@
+from typing import Optional, Tuple, Sequence
+
+import attr
+from elasticsearch import Elasticsearch
+
+from bll.event.event_metrics import EventMetrics
+from database.errors import translate_errors_context
+from timing_context import TimingContext
+
+
+@attr.s(auto_attribs=True)
+class TaskEventsResult:
+    total_events: int = 0
+    next_scroll_id: str = None
+    events: list = attr.Factory(list)
+
+
+class LogEventsIterator:
+    EVENT_TYPE = "log"
+
+    def __init__(self, es: Elasticsearch):
+        self.es = es
+
+    def get_task_events(
+        self,
+        company_id: str,
+        task_id: str,
+        batch_size: int,
+        navigate_earlier: bool = True,
+        from_timestamp: Optional[int] = None,
+    ) -> TaskEventsResult:
+        es_index = EventMetrics.get_index_name(company_id, self.EVENT_TYPE)
+        if not self.es.indices.exists(es_index):
+            return TaskEventsResult()
+
+        res = TaskEventsResult()
+        res.events, res.total_events = self._get_events(
+            es_index=es_index,
+            task_id=task_id,
+            batch_size=batch_size,
+            navigate_earlier=navigate_earlier,
+            from_timestamp=from_timestamp,
+        )
+        return res
+
+    def _get_events(
+        self,
+        es_index,
+        task_id: str,
+        batch_size: int,
+        navigate_earlier: bool,
+        from_timestamp: Optional[int],
+    ) -> Tuple[Sequence[dict], int]:
+        """
+        Return up to 'batch size' events starting from the previous timestamp either in the
+        direction of earlier events (navigate_earlier=True) or in the direction of later events.
+        If last_min_timestamp and last_max_timestamp are not set then start either from latest or earliest.
+        For the last timestamp all the events are brought (even if the resulting size
+        exceeds batch_size) so that this timestamp events will not be lost between the calls.
+        In case any events were received update 'last_min_timestamp' and 'last_max_timestamp'
+        """
+
+        # retrieve the next batch of events
+        es_req = {
+            "size": batch_size,
+            "query": {"term": {"task": task_id}},
+            "sort": {"timestamp": "desc" if navigate_earlier else "asc"},
+        }
+
+        if from_timestamp:
+            es_req["search_after"] = [from_timestamp]
+
+        with translate_errors_context(), TimingContext("es", "get_task_events"):
+            es_result = self.es.search(index=es_index, body=es_req)
+            hits = es_result["hits"]["hits"]
+            hits_total = es_result["hits"]["total"]["value"]
+            if not hits:
+                return [], hits_total
+
+            events = [hit["_source"] for hit in hits]
+
+            # retrieve the events that match the last event timestamp
+            # but did not make it into the previous call due to batch_size limitation
+            es_req = {
+                "size": 10000,
+                "query": {
+                    "bool": {
+                        "must": [
+                            {"term": {"task": task_id}},
+                            {"term": {"timestamp": events[-1]["timestamp"]}},
+                        ]
+                    }
+                },
+            }
+            es_result = self.es.search(index=es_index, body=es_req)
+            last_second_hits = es_result["hits"]["hits"]
+            if not last_second_hits or len(last_second_hits) < 2:
+                # if only one element is returned for the last timestamp
+                # then it is already present in the events
+                return events, hits_total
+
+            already_present_ids = set(hit["_id"] for hit in hits)
+            last_second_events = [
+                hit["_source"]
+                for hit in last_second_hits
+                if hit["_id"] not in already_present_ids
+            ]
+
+            # return the list merged from original query results +
+            # leftovers from the last timestamp
+            return (
+                [*events, *last_second_events],
+                hits_total,
+            )

server/bll/event/scalar_key.py

@@ -4,7 +4,7 @@ Module for polymorphism over different types of X axes in scalar aggregations
 from abc import ABC, abstractmethod
 from enum import auto
 
-from apimodels import StringEnum
+from utilities.stringenum import StringEnum
 from bll.util import extract_properties_to_lists
 from config import config
 
@@ -111,7 +111,7 @@ class TimestampKey(ScalarKey):
             self.name: {
                 "date_histogram": {
                     "field": "timestamp",
-                    "interval": interval,
+                    "fixed_interval": f"{interval}ms",
                     "min_doc_count": 1,
                 }
             }
@@ -150,7 +150,7 @@ class ISOTimeKey(ScalarKey):
             self.name: {
                 "date_histogram": {
                     "field": "timestamp",
-                    "interval": interval,
+                    "fixed_interval": f"{interval}ms",
                     "min_doc_count": 1,
                     "format": "strict_date_time",
                 }

server/bll/model/__init__.py

@@ -0,0 +1,18 @@
+from typing import Optional, Sequence
+
+from mongoengine import Q
+
+from database.model.model import Model
+from database.utils import get_company_or_none_constraint
+
+
+class ModelBLL:
+    def get_frameworks(self, company, project_ids: Optional[Sequence]) -> Sequence:
+        """
+        Return the list of unique frameworks used by company and public models
+        If project ids passed then only models from these projects are considered
+        """
+        query = get_company_or_none_constraint(company)
+        if project_ids:
+            query &= Q(project__in=project_ids)
+        return Model.objects(query).distinct(field="framework")

server/bll/organization/__init__.py

@@ -0,0 +1,193 @@
+from collections import defaultdict
+from enum import Enum
+from itertools import chain
+from typing import Sequence, Union, Type, Dict
+
+from mongoengine import Q
+from redis import Redis
+
+from config import config
+from database.model.base import GetMixin
+from database.model.model import Model
+from database.model.task.task import Task
+from redis_manager import redman
+from utilities import json
+
+log = config.logger(__file__)
+_settings_prefix = "services.organization"
+
+
+class _TagsCache:
+    _tags_field = "tags"
+    _system_tags_field = "system_tags"
+
+    def __init__(self, db_cls: Union[Type[Model], Type[Task]], redis: Redis):
+        self.db_cls = db_cls
+        self.redis = redis
+
+    @property
+    def _tags_cache_expiration_seconds(self):
+        return config.get(f"{_settings_prefix}.tags_cache.expiration_seconds", 3600)
+
+    def _get_tags_from_db(
+        self,
+        company: str,
+        field: str,
+        project: str = None,
+        filter_: Dict[str, Sequence[str]] = None,
+    ) -> set:
+        query = Q(company=company)
+        if filter_:
+            for name, vals in filter_.items():
+                if vals:
+                    query &= GetMixin.get_list_field_query(name, vals)
+        if project:
+            query &= Q(project=project)
+
+        return self.db_cls.objects(query).distinct(field)
+
+    def _get_tags_cache_key(
+        self,
+        company: str,
+        field: str,
+        project: str = None,
+        filter_: Dict[str, Sequence[str]] = None,
+    ):
+        """
+        Project None means 'from all company projects'
+        The key is built in the way that scanning company keys for 'all company projects'
+        will not return the keys related to the particular company projects and vice versa.
+        So that we can have a fine grain control on what redis keys to invalidate
+        """
+        filter_str = None
+        if filter_:
+            filter_str = "_".join(
+                ["filter", *chain.from_iterable([f, *v] for f, v in filter_.items())]
+            )
+        key_parts = [company, project, self.db_cls.__name__, field, filter_str]
+        return "_".join(filter(None, key_parts))
+
+    def get_tags(
+        self,
+        company: str,
+        include_system: bool = False,
+        filter_: Dict[str, Sequence[str]] = None,
+        project: str = None,
+    ) -> dict:
+        """
+        Get tags and optionally system tags for the company
+        Return the dictionary of tags per tags field name
+        The function retrieves both cached values from Redis in one call
+        and re calculates any of them if missing in Redis
+        """
+        fields = [self._tags_field]
+        if include_system:
+            fields.append(self._system_tags_field)
+        redis_keys = [
+            self._get_tags_cache_key(company, field=f, project=project, filter_=filter_)
+            for f in fields
+        ]
+        cached = self.redis.mget(redis_keys)
+        ret = {}
+        for field, tag_data, key in zip(fields, cached, redis_keys):
+            if tag_data is not None:
+                tags = json.loads(tag_data)
+            else:
+                tags = list(self._get_tags_from_db(company, field, project, filter_))
+                self.redis.setex(
+                    key,
+                    time=self._tags_cache_expiration_seconds,
+                    value=json.dumps(tags),
+                )
+            ret[field] = set(tags)
+
+        return ret
+
+    def update_tags(self, company: str, project: str, tags=None, system_tags=None):
+        """
+        Updates tags. If reset is set then both tags and system_tags
+        are recalculated. Otherwise only those that are not 'None'
+        """
+        fields = [
+            field
+            for field, update in (
+                (self._tags_field, tags),
+                (self._system_tags_field, system_tags),
+            )
+            if update is not None
+        ]
+        if not fields:
+            return
+
+        self._delete_redis_keys(company, projects=[project], fields=fields)
+
+    def reset_tags(self, company: str, projects: Sequence[str]):
+        self._delete_redis_keys(
+            company,
+            projects=projects,
+            fields=(self._tags_field, self._system_tags_field),
+        )
+
+    def _delete_redis_keys(
+        self, company: str, projects: [Sequence[str]], fields: Sequence[str]
+    ):
+        redis_keys = list(
+            chain.from_iterable(
+                self.redis.keys(
+                    self._get_tags_cache_key(company, field=f, project=p) + "*"
+                )
+                for f in fields
+                for p in set(projects) | {None}
+            )
+        )
+        if redis_keys:
+            self.redis.delete(*redis_keys)
+
+
+class Tags(Enum):
+    Task = "task"
+    Model = "model"
+
+
+class OrgBLL:
+    def __init__(self, redis=None):
+        self.redis = redis or redman.connection("apiserver")
+        self._task_tags = _TagsCache(Task, self.redis)
+        self._model_tags = _TagsCache(Model, self.redis)
+
+    def get_tags(
+        self,
+        company: str,
+        entity: Tags,
+        include_system: bool = False,
+        filter_: Dict[str, Sequence[str]] = None,
+        projects: Sequence[str] = None,
+    ) -> dict:
+        tags_cache = self._get_tags_cache_for_entity(entity)
+        if not projects:
+            return tags_cache.get_tags(
+                company, include_system=include_system, filter_=filter_
+            )
+
+        ret = defaultdict(set)
+        for project in projects:
+            project_tags = tags_cache.get_tags(
+                company, include_system=include_system, filter_=filter_, project=project
+            )
+            for field, tags in project_tags.items():
+                ret[field] |= tags
+
+        return ret
+
+    def update_tags(
+        self, company: str, entity: Tags, project: str, tags=None, system_tags=None,
+    ):
+        tags_cache = self._get_tags_cache_for_entity(entity)
+        tags_cache.update_tags(company, project, tags, system_tags)
+
+    def reset_tags(self, company: str, entity: Tags, projects: Sequence[str]):
+        tags_cache = self._get_tags_cache_for_entity(entity)
+        tags_cache.reset_tags(company, projects=projects)
+
+    def _get_tags_cache_for_entity(self, entity: Tags) -> _TagsCache:
+        return self._task_tags if entity == Tags.Task else self._model_tags

server/bll/project/__init__.py

@@ -0,0 +1 @@
+from .project_bll import ProjectBLL

server/bll/project/project_bll.py

@@ -0,0 +1,33 @@
+from typing import Sequence, Optional
+
+from mongoengine import Q
+
+from config import config
+from database.model.model import Model
+from database.model.task.task import Task
+from timing_context import TimingContext
+
+log = config.logger(__file__)
+
+
+class ProjectBLL:
+    @classmethod
+    def get_active_users(
+        cls, company, project_ids: Sequence, user_ids: Optional[Sequence] = None
+    ) -> set:
+        """
+        Get the set of user ids that created tasks/models in the given projects
+        If project_ids is empty then all projects are examined
+        If user_ids are passed then only subset of these users is returned
+        """
+        with TimingContext("mongo", "active_users_in_projects"):
+            res = set()
+            query = Q(company=company)
+            if project_ids:
+                query &= Q(project__in=project_ids)
+            if user_ids:
+                query &= Q(user__in=user_ids)
+            for cls_ in (Task, Model):
+                res |= set(cls_.objects(query).distinct(field="user"))
+
+            return res

server/bll/queue/queue_bll.py

@@ -9,9 +9,12 @@ import es_factory
 from apierrors import errors
 from bll.queue.queue_metrics import QueueMetrics
 from bll.workers import WorkerBLL
+from config import config
 from database.errors import translate_errors_context
 from database.model.queue import Queue, Entry
 
+log = config.logger(__file__)
+
 
 class QueueBLL(object):
     def __init__(self, worker_bll: WorkerBLL = None, es: Elasticsearch = None):
@@ -189,9 +192,7 @@ class QueueBLL(object):
         """
         with translate_errors_context():
             query = dict(id=queue_id, company=company_id)
-            queue = Queue.objects(**query).modify(
-                pop__entries=-1, last_update=datetime.utcnow(), upsert=False
-            )
+            queue = Queue.objects(**query).modify(pop__entries=-1, upsert=False)
             if not queue:
                 raise errors.bad_request.InvalidQueueId(**query)
 
@@ -200,6 +201,11 @@ class QueueBLL(object):
             if not queue.entries:
                 return
 
+            try:
+                Queue.objects(**query).update(last_update=datetime.utcnow())
+            except Exception:
+                log.exception("Error while updating Queue.last_update")
+
             return queue.entries[0]
 
     def remove_task(self, company_id: str, queue_id: str, task_id: str) -> int:

server/bll/queue/queue_metrics.py

@@ -18,7 +18,6 @@ log = config.logger(__file__)
 
 class QueueMetrics:
     class EsKeys:
-        DOC_TYPE = "metrics"
         WAITING_TIME_FIELD = "average_waiting_time"
         QUEUE_LENGTH_FIELD = "queue_length"
         TIMESTAMP_FIELD = "timestamp"
@@ -66,7 +65,6 @@ class QueueMetrics:
             entries = [e for e in queue.entries if e.added]
             return dict(
                 _index=es_index,
-                _type=self.EsKeys.DOC_TYPE,
                 _source={
                     self.EsKeys.TIMESTAMP_FIELD: timestamp,
                     self.EsKeys.QUEUE_FIELD: queue.id,
@@ -93,7 +91,6 @@ class QueueMetrics:
     def _search_company_metrics(self, company_id: str, es_req: dict) -> dict:
         return self.es.search(
             index=f"{self._queue_metrics_prefix_for_company(company_id)}*",
-            doc_type=self.EsKeys.DOC_TYPE,
             body=es_req,
         )
 
@@ -109,7 +106,7 @@ class QueueMetrics:
             "dates": {
                 "date_histogram": {
                     "field": cls.EsKeys.TIMESTAMP_FIELD,
-                    "interval": f"{interval}s",
+                    "fixed_interval": f"{interval}s",
                     "min_doc_count": 1,
                 },
                 "aggs": {
@@ -161,7 +158,7 @@ class QueueMetrics:
         In case no queue ids are specified the avg across all the
         company queues is calculated for each metric
         """
-        # self._log_current_metrics(company_id, queue_ids=queue_ids)
+        # self._log_current_metrics(company, queue_ids=queue_ids)
 
         if from_date >= to_date:
             raise bad_request.FieldsValueError("from_date must be less than to_date")

server/bll/redis_cache_manager.py

@@ -0,0 +1,79 @@
+from contextlib import contextmanager
+from typing import Optional, TypeVar, Generic, Type, Callable
+
+from redis import StrictRedis
+
+import database
+from timing_context import TimingContext
+
+T = TypeVar("T")
+
+
+def _do_nothing(_: T):
+    return
+
+
+class RedisCacheManager(Generic[T]):
+    """
+    Class for store/retrieve of state objects from redis
+
+    self.state_class - class of the state
+    self.redis - instance of redis
+    self.expiration_interval - expiration interval in seconds
+    """
+
+    def __init__(
+        self, state_class: Type[T], redis: StrictRedis, expiration_interval: int
+    ):
+        self.state_class = state_class
+        self.redis = redis
+        self.expiration_interval = expiration_interval
+
+    def set_state(self, state: T) -> None:
+        redis_key = self._get_redis_key(state.id)
+        with TimingContext("redis", "cache_set_state"):
+            self.redis.set(redis_key, state.to_json())
+            self.redis.expire(redis_key, self.expiration_interval)
+
+    def get_state(self, state_id) -> Optional[T]:
+        redis_key = self._get_redis_key(state_id)
+        with TimingContext("redis", "cache_get_state"):
+            response = self.redis.get(redis_key)
+        if response:
+            return self.state_class.from_json(response)
+
+    def delete_state(self, state_id) -> None:
+        with TimingContext("redis", "cache_delete_state"):
+            self.redis.delete(self._get_redis_key(state_id))
+
+    def _get_redis_key(self, state_id):
+        return f"{self.state_class}/{state_id}"
+
+    @contextmanager
+    def get_or_create_state(
+        self,
+        state_id=None,
+        init_state: Callable[[T], None] = _do_nothing,
+        validate_state: Callable[[T], None] = _do_nothing,
+    ):
+        """
+        Try to retrieve state with the given id from the Redis cache if yes then validates it
+        If no then create a new one with randomly generated id
+        Yield the state and write it back to redis once the user code block exits
+        :param state_id: id of the state to retrieve
+        :param init_state: user callback to init the newly created state
+        If not passed then no init except for the id generation is done
+        :param validate_state: user callback to validate the state if retrieved from cache
+        Should throw an exception if the state is not valid. If not passed then no validation is done
+        """
+        state = self.get_state(state_id) if state_id else None
+        if state:
+            validate_state(state)
+        else:
+            state = self.state_class(id=database.utils.id())
+            init_state(state)
+
+        try:
+            yield state
+        finally:
+            self.set_state(state)

server/bll/statistics/resource_monitor.py

@@ -0,0 +1,90 @@
+from datetime import datetime
+import operator
+from threading import Thread, Lock
+from time import sleep
+
+import attr
+import psutil
+
+from utilities.threads_manager import ThreadsManager
+
+
+class ResourceMonitor(Thread):
+    @attr.s(auto_attribs=True)
+    class Sample:
+        cpu_usage: float = 0.0
+        mem_used_gb: float = 0
+        mem_free_gb: float = 0
+
+        @classmethod
+        def _apply(cls, op, *samples):
+            return cls(
+                **{
+                    field: op(*(getattr(sample, field) for sample in samples))
+                    for field in attr.fields_dict(cls)
+                }
+            )
+
+        def min(self, sample):
+            return self._apply(min, self, sample)
+
+        def max(self, sample):
+            return self._apply(max, self, sample)
+
+        def avg(self, sample, count):
+            res = self._apply(lambda x: x * count, self)
+            res = self._apply(operator.add, res, sample)
+            res = self._apply(lambda x: x / (count + 1), res)
+            return res
+
+    def __init__(self, sample_interval_sec=5):
+        super(ResourceMonitor, self).__init__(daemon=True)
+        self.sample_interval_sec = sample_interval_sec
+        self._lock = Lock()
+        self._clear()
+
+    def _clear(self):
+        sample = self._get_sample()
+        self._avg = sample
+        self._min = sample
+        self._max = sample
+        self._clear_time = datetime.utcnow()
+        self._count = 1
+
+    @classmethod
+    def _get_sample(cls) -> Sample:
+        return cls.Sample(
+            cpu_usage=psutil.cpu_percent(),
+            mem_used_gb=psutil.virtual_memory().used / (1024 ** 3),
+            mem_free_gb=psutil.virtual_memory().free / (1024 ** 3),
+        )
+
+    def run(self):
+        while not ThreadsManager.terminating:
+            sleep(self.sample_interval_sec)
+
+            sample = self._get_sample()
+
+            with self._lock:
+                self._min = self._min.min(sample)
+                self._max = self._max.max(sample)
+                self._avg = self._avg.avg(sample, self._count)
+                self._count += 1
+
+    def get_stats(self) -> dict:
+        """ Returns current resource statistics and clears internal resource statistics """
+        with self._lock:
+            min_ = attr.asdict(self._min)
+            max_ = attr.asdict(self._max)
+            avg = attr.asdict(self._avg)
+            interval = datetime.utcnow() - self._clear_time
+            self._clear()
+
+        return {
+            "interval_sec": interval.total_seconds(),
+            "num_cores": psutil.cpu_count(),
+            **{
+                k: {"min": v, "max": max_[k], "avg": avg[k]}
+                for k, v in min_.items()
+            }
+        }

server/bll/statistics/stats_reporter.py

@@ -0,0 +1,304 @@
+import logging
+import queue
+import random
+import time
+from datetime import timedelta, datetime
+from time import sleep
+from typing import Sequence, Optional
+
+import dpath
+import requests
+from requests.adapters import HTTPAdapter
+from requests.packages.urllib3.util.retry import Retry
+
+from bll.query import Builder as QueryBuilder
+from bll.util import get_server_uuid
+from bll.workers import WorkerStats, WorkerBLL
+from config import config
+from config.info import get_deployment_type
+from database.model import Company, User
+from database.model.queue import Queue
+from database.model.task.task import Task
+from tools import safe_get
+from utilities.json import dumps
+from utilities.threads_manager import ThreadsManager
+from version import __version__ as current_version
+from .resource_monitor import ResourceMonitor
+
+log = config.logger(__file__)
+
+worker_bll = WorkerBLL()
+
+
+class StatisticsReporter:
+    threads = ThreadsManager("Statistics", resource_monitor=ResourceMonitor)
+    send_queue = queue.Queue()
+    supported = config.get("apiserver.statistics.supported", True)
+
+    @classmethod
+    def start(cls):
+        cls.start_sender()
+        cls.start_reporter()
+
+    @classmethod
+    @threads.register("reporter", daemon=True)
+    def start_reporter(cls):
+        """
+        Periodically send statistics reports for companies who have opted in.
+        Note: in trains we usually have only a single company
+        """
+        if not cls.supported:
+            return
+
+        report_interval = timedelta(
+            hours=config.get("apiserver.statistics.report_interval_hours", 24)
+        )
+        sleep(report_interval.total_seconds())
+        while not ThreadsManager.terminating:
+            try:
+                for company in Company.objects(
+                    defaults__stats_option__enabled=True
+                ).only("id"):
+                    stats = cls.get_statistics(company.id)
+                    cls.send_queue.put(stats)
+
+            except Exception as ex:
+                log.exception(f"Failed collecting stats: {str(ex)}")
+
+            sleep(report_interval.total_seconds())
+
+    @classmethod
+    @threads.register("sender", daemon=True)
+    def start_sender(cls):
+        if not cls.supported:
+            return
+
+        url = config.get("apiserver.statistics.url")
+
+        retries = config.get("apiserver.statistics.max_retries", 5)
+        max_backoff = config.get("apiserver.statistics.max_backoff_sec", 5)
+        session = requests.Session()
+        adapter = HTTPAdapter(max_retries=Retry(retries))
+        session.mount("http://", adapter)
+        session.mount("https://", adapter)
+        session.headers["Content-type"] = "application/json"
+
+        WarningFilter.attach()
+
+        while not ThreadsManager.terminating:
+            try:
+                report = cls.send_queue.get()
+
+                # Set a random backoff factor each time we send a report
+                adapter.max_retries.backoff_factor = random.random() * max_backoff
+
+                session.post(url, data=dumps(report))
+
+            except Exception as ex:
+                pass
+
+    @classmethod
+    def get_statistics(cls, company_id: str) -> dict:
+        """
+        Returns a statistics report per company
+        """
+        return {
+            "time": datetime.utcnow(),
+            "company_id": company_id,
+            "server": {
+                "version": current_version,
+                "deployment": get_deployment_type(),
+                "uuid": get_server_uuid(),
+                "queues": {"count": Queue.objects(company=company_id).count()},
+                "users": {"count": User.objects(company=company_id).count()},
+                "resources": cls.threads.resource_monitor.get_stats(),
+                "experiments": next(
+                    iter(cls._get_experiments_stats(company_id).values()), {}
+                ),
+            },
+            "agents": cls._get_agents_statistics(company_id),
+        }
+
+    @classmethod
+    def _get_agents_statistics(cls, company_id: str) -> Sequence[dict]:
+        result = cls._get_resource_stats_per_agent(company_id, key="resources")
+        dpath.merge(
+            result, cls._get_experiments_stats_per_agent(company_id, key="experiments")
+        )
+        return [{"uuid": agent_id, **data} for agent_id, data in result.items()]
+
+    @classmethod
+    def _get_resource_stats_per_agent(cls, company_id: str, key: str) -> dict:
+        agent_resource_threshold_sec = timedelta(
+            hours=config.get("apiserver.statistics.report_interval_hours", 24)
+        ).total_seconds()
+        to_timestamp = int(time.time())
+        from_timestamp = to_timestamp - int(agent_resource_threshold_sec)
+        es_req = {
+            "size": 0,
+            "query": QueryBuilder.dates_range(from_timestamp, to_timestamp),
+            "aggs": {
+                "workers": {
+                    "terms": {"field": "worker"},
+                    "aggs": {
+                        "categories": {
+                            "terms": {"field": "category"},
+                            "aggs": {"count": {"cardinality": {"field": "variant"}}},
+                        },
+                        "metrics": {
+                            "terms": {"field": "metric"},
+                            "aggs": {
+                                "min": {"min": {"field": "value"}},
+                                "max": {"max": {"field": "value"}},
+                                "avg": {"avg": {"field": "value"}},
+                            },
+                        },
+                    },
+                }
+            },
+        }
+        res = cls._run_worker_stats_query(company_id, es_req)
+
+        def _get_cardinality_fields(categories: Sequence[dict]) -> dict:
+            names = {"cpu": "num_cores"}
+            return {
+                names[c["key"]]: safe_get(c, "count/value")
+                for c in categories
+                if c["key"] in names
+            }
+
+        def _get_metric_fields(metrics: Sequence[dict]) -> dict:
+            names = {
+                "cpu_usage": "cpu_usage",
+                "memory_used": "mem_used_gb",
+                "memory_free": "mem_free_gb",
+            }
+            return {
+                names[m["key"]]: {
+                    "min": safe_get(m, "min/value"),
+                    "max": safe_get(m, "max/value"),
+                    "avg": safe_get(m, "avg/value"),
+                }
+                for m in metrics
+                if m["key"] in names
+            }
+
+        buckets = safe_get(res, "aggregations/workers/buckets", default=[])
+        return {
+            b["key"]: {
+                key: {
+                    "interval_sec": agent_resource_threshold_sec,
+                    **_get_cardinality_fields(safe_get(b, "categories/buckets", [])),
+                    **_get_metric_fields(safe_get(b, "metrics/buckets", [])),
+                }
+            }
+            for b in buckets
+        }
+
+    @classmethod
+    def _get_experiments_stats_per_agent(cls, company_id: str, key: str) -> dict:
+        agent_relevant_threshold = timedelta(
+            days=config.get("apiserver.statistics.agent_relevant_threshold_days", 30)
+        )
+        to_timestamp = int(time.time())
+        from_timestamp = to_timestamp - int(agent_relevant_threshold.total_seconds())
+        workers = cls._get_active_workers(company_id, from_timestamp, to_timestamp)
+        if not workers:
+            return {}
+
+        stats = cls._get_experiments_stats(company_id, list(workers.keys()))
+        return {
+            worker_id: {key: {**workers[worker_id], **stat}}
+            for worker_id, stat in stats.items()
+        }
+
+    @classmethod
+    def _get_active_workers(
+        cls, company_id, from_timestamp: int, to_timestamp: int
+    ) -> dict:
+        es_req = {
+            "size": 0,
+            "query": QueryBuilder.dates_range(from_timestamp, to_timestamp),
+            "aggs": {
+                "workers": {
+                    "terms": {"field": "worker"},
+                    "aggs": {"last_activity_time": {"max": {"field": "timestamp"}}},
+                }
+            },
+        }
+        res = cls._run_worker_stats_query(company_id, es_req)
+        buckets = safe_get(res, "aggregations/workers/buckets", default=[])
+        return {
+            b["key"]: {"last_activity_time": b["last_activity_time"]["value"]}
+            for b in buckets
+        }
+
+    @classmethod
+    def _run_worker_stats_query(cls, company_id, es_req) -> dict:
+        return worker_bll.es_client.search(
+            index=f"{WorkerStats.worker_stats_prefix_for_company(company_id)}*",
+            body=es_req,
+        )
+
+    @classmethod
+    def _get_experiments_stats(
+        cls, company_id, workers: Optional[Sequence] = None
+    ) -> dict:
+        pipeline = [
+            {
+                "$match": {
+                    "company": company_id,
+                    "started": {"$exists": True, "$ne": None},
+                    "last_update": {"$exists": True, "$ne": None},
+                    "status": {"$nin": ["created", "queued"]},
+                    **({"last_worker": {"$in": workers}} if workers else {}),
+                }
+            },
+            {
+                "$group": {
+                    "_id": "$last_worker" if workers else None,
+                    "count": {"$sum": 1},
+                    "avg_run_time_sec": {
+                        "$avg": {
+                            "$divide": [
+                                {"$subtract": ["$last_update", "$started"]},
+                                1000,
+                            ]
+                        }
+                    },
+                    "avg_iterations": {"$avg": "$last_iteration"},
+                }
+            },
+            {
+                "$project": {
+                    "count": 1,
+                    "avg_run_time_sec": {"$trunc": "$avg_run_time_sec"},
+                    "avg_iterations": {"$trunc": "$avg_iterations"},
+                }
+            },
+        ]
+        return {
+            group["_id"]: {k: v for k, v in group.items() if k != "_id"}
+            for group in Task.aggregate(pipeline)
+        }
+
+
+class WarningFilter(logging.Filter):
+    @classmethod
+    def attach(cls):
+        from urllib3.connectionpool import (
+            ConnectionPool,
+        )  # required to make sure the logger is created
+
+        assert ConnectionPool  # make sure import is not optimized out
+
+        logging.getLogger("urllib3.connectionpool").addFilter(cls())
+
+    def filter(self, record):
+        if (
+            record.levelno == logging.WARNING
+            and len(record.args) > 2
+            and record.args[2] == "/stats"
+        ):
+            return False
+        return True

server/bll/task/hyperparams.py

@@ -0,0 +1,229 @@
+from datetime import datetime
+from itertools import chain
+from operator import attrgetter
+from typing import Sequence, Dict
+
+from boltons import iterutils
+
+from apierrors import errors
+from apimodels.tasks import (
+    HyperParamKey,
+    HyperParamItem,
+    ReplaceHyperparams,
+    Configuration,
+)
+from bll.task import TaskBLL
+from config import config
+from database.model.task.task import ParamsItem, Task, ConfigurationItem, TaskStatus
+from utilities.parameter_key_escaper import ParameterKeyEscaper
+
+log = config.logger(__file__)
+task_bll = TaskBLL()
+
+
+class HyperParams:
+    _properties_section = "properties"
+
+    @classmethod
+    def get_params(cls, company_id: str, task_ids: Sequence[str]) -> Dict[str, dict]:
+        only = ("id", "hyperparams")
+        tasks = task_bll.assert_exists(
+            company_id=company_id, task_ids=task_ids, only=only, allow_public=True,
+        )
+
+        return {
+            task.id: {"hyperparams": cls._get_params_list(items=task.hyperparams)}
+            for task in tasks
+        }
+
+    @classmethod
+    def _get_params_list(
+        cls, items: Dict[str, Dict[str, ParamsItem]]
+    ) -> Sequence[dict]:
+        ret = list(chain.from_iterable(v.values() for v in items.values()))
+        return [
+            p.to_proper_dict() for p in sorted(ret, key=attrgetter("section", "name"))
+        ]
+
+    @classmethod
+    def _normalize_params(cls, params: Sequence) -> bool:
+        """
+        Lower case properties section and return True if it is the only section
+        """
+        for p in params:
+            if p.section.lower() == cls._properties_section:
+                p.section = cls._properties_section
+
+        return all(p.section == cls._properties_section for p in params)
+
+    @classmethod
+    def delete_params(
+        cls, company_id: str, task_id: str, hyperparams=Sequence[HyperParamKey]
+    ) -> int:
+        properties_only = cls._normalize_params(hyperparams)
+        task = cls._get_task_for_update(
+            company=company_id, id=task_id, allow_all_statuses=properties_only
+        )
+
+        with_param, without_param = iterutils.partition(
+            hyperparams, key=lambda p: bool(p.name)
+        )
+        sections_to_delete = {p.section for p in without_param}
+        delete_cmds = {
+            f"unset__hyperparams__{ParameterKeyEscaper.escape(section)}": 1
+            for section in sections_to_delete
+        }
+
+        for item in with_param:
+            section = ParameterKeyEscaper.escape(item.section)
+            if item.section in sections_to_delete:
+                raise errors.bad_request.FieldsConflict(
+                    "Cannot delete section field if the whole section was scheduled for deletion"
+                )
+            name = ParameterKeyEscaper.escape(item.name)
+            delete_cmds[f"unset__hyperparams__{section}__{name}"] = 1
+
+        return task.update(**delete_cmds, last_update=datetime.utcnow())
+
+    @classmethod
+    def edit_params(
+        cls,
+        company_id: str,
+        task_id: str,
+        hyperparams: Sequence[HyperParamItem],
+        replace_hyperparams: str,
+    ) -> int:
+        properties_only = cls._normalize_params(hyperparams)
+        task = cls._get_task_for_update(
+            company=company_id, id=task_id, allow_all_statuses=properties_only
+        )
+
+        update_cmds = dict()
+        hyperparams = cls._db_dicts_from_list(hyperparams)
+        if replace_hyperparams == ReplaceHyperparams.all:
+            update_cmds["set__hyperparams"] = hyperparams
+        elif replace_hyperparams == ReplaceHyperparams.section:
+            for section, value in hyperparams.items():
+                update_cmds[f"set__hyperparams__{section}"] = value
+        else:
+            for section, section_params in hyperparams.items():
+                for name, value in section_params.items():
+                    update_cmds[f"set__hyperparams__{section}__{name}"] = value
+
+        return task.update(**update_cmds, last_update=datetime.utcnow())
+
+    @classmethod
+    def _db_dicts_from_list(cls, items: Sequence[HyperParamItem]) -> Dict[str, dict]:
+        sections = iterutils.bucketize(items, key=attrgetter("section"))
+        return {
+            ParameterKeyEscaper.escape(section): {
+                ParameterKeyEscaper.escape(param.name): ParamsItem(**param.to_struct())
+                for param in params
+            }
+            for section, params in sections.items()
+        }
+
+    @classmethod
+    def get_configurations(
+        cls, company_id: str, task_ids: Sequence[str], names: Sequence[str]
+    ) -> Dict[str, dict]:
+        only = ["id"]
+        if names:
+            only.extend(
+                f"configuration.{ParameterKeyEscaper.escape(name)}" for name in names
+            )
+        else:
+            only.append("configuration")
+        tasks = task_bll.assert_exists(
+            company_id=company_id, task_ids=task_ids, only=only, allow_public=True,
+        )
+
+        return {
+            task.id: {
+                "configuration": [
+                    c.to_proper_dict()
+                    for c in sorted(task.configuration.values(), key=attrgetter("name"))
+                ]
+            }
+            for task in tasks
+        }
+
+    @classmethod
+    def get_configuration_names(
+        cls, company_id: str, task_ids: Sequence[str]
+    ) -> Dict[str, list]:
+        pipeline = [
+            {
+                "$match": {
+                    "company": {"$in": [None, "", company_id]},
+                    "_id": {"$in": task_ids},
+                }
+            },
+            {"$project": {"items": {"$objectToArray": "$configuration"}}},
+            {"$unwind": "$items"},
+            {"$group": {"_id": "$_id", "names": {"$addToSet": "$items.k"}}},
+        ]
+
+        tasks = Task.aggregate(pipeline)
+
+        return {
+            task["_id"]: {
+                "names": sorted(
+                    ParameterKeyEscaper.unescape(name) for name in task["names"]
+                )
+            }
+            for task in tasks
+        }
+
+    @classmethod
+    def edit_configuration(
+        cls,
+        company_id: str,
+        task_id: str,
+        configuration: Sequence[Configuration],
+        replace_configuration: bool,
+    ) -> int:
+        task = cls._get_task_for_update(company=company_id, id=task_id)
+
+        update_cmds = dict()
+        configuration = {
+            ParameterKeyEscaper.escape(c.name): ConfigurationItem(**c.to_struct())
+            for c in configuration
+        }
+        if replace_configuration:
+            update_cmds["set__configuration"] = configuration
+        else:
+            for name, value in configuration.items():
+                update_cmds[f"set__configuration__{name}"] = value
+
+        return task.update(**update_cmds, last_update=datetime.utcnow())
+
+    @classmethod
+    def delete_configuration(
+        cls, company_id: str, task_id: str, configuration=Sequence[str]
+    ) -> int:
+        task = cls._get_task_for_update(company=company_id, id=task_id)
+
+        delete_cmds = {
+            f"unset__configuration__{ParameterKeyEscaper.escape(name)}": 1
+            for name in set(configuration)
+        }
+
+        return task.update(**delete_cmds, last_update=datetime.utcnow())
+
+    @staticmethod
+    def _get_task_for_update(
+        company: str, id: str, allow_all_statuses: bool = False
+    ) -> Task:
+        task = Task.get_for_writing(company=company, id=id, _only=("id", "status"))
+        if not task:
+            raise errors.bad_request.InvalidTaskId(id=id)
+
+        if allow_all_statuses:
+            return task
+
+        if task.status != TaskStatus.created:
+            raise errors.bad_request.InvalidTaskStatus(
+                expected=TaskStatus.created, status=task.status
+            )
+        return task

server/bll/task/non_responsive_tasks_watchdog.py

@@ -0,0 +1,89 @@
+from datetime import timedelta, datetime
+from time import sleep
+
+from apierrors import errors
+from bll.task import ChangeStatusRequest
+from config import config
+from database.model.task.task import TaskStatus, Task
+from utilities.threads_manager import ThreadsManager
+
+log = config.logger(__file__)
+
+
+class NonResponsiveTasksWatchdog:
+    threads = ThreadsManager()
+
+    class _Settings:
+        """
+        Retrieves watchdog settings from the config file
+        The properties are not cached so that the updates in
+        the config file are reflected
+        """
+
+        _prefix = "services.tasks.non_responsive_tasks_watchdog"
+
+        @property
+        def enabled(self):
+            return config.get(f"{self._prefix}.enabled", True)
+
+        @property
+        def watch_interval_sec(self):
+            return config.get(f"{self._prefix}.watch_interval_sec", 900)
+
+        @property
+        def threshold_sec(self):
+            return config.get(f"{self._prefix}.threshold_sec", 7200)
+
+    settings = _Settings()
+
+    @classmethod
+    @threads.register("non_responsive_tasks_watchdog", daemon=True)
+    def start(cls):
+        sleep(cls.settings.watch_interval_sec)
+        while not ThreadsManager.terminating:
+            watch_interval = cls.settings.watch_interval_sec
+            if cls.settings.enabled:
+                try:
+                    stopped = cls.cleanup_tasks(
+                        threshold_sec=cls.settings.threshold_sec
+                    )
+                    log.info(f"{stopped} non-responsive tasks stopped")
+                except Exception as ex:
+                    log.exception(f"Failed stopping tasks: {str(ex)}")
+            sleep(watch_interval)
+
+    @classmethod
+    def cleanup_tasks(cls, threshold_sec):
+        relevant_status = (TaskStatus.in_progress,)
+        threshold = timedelta(seconds=threshold_sec)
+        ref_time = datetime.utcnow() - threshold
+        log.info(
+            f"Starting cleanup cycle for running tasks last updated before {ref_time}"
+        )
+
+        tasks = list(
+            Task.objects(status__in=relevant_status, last_update__lt=ref_time).only(
+                "id", "name", "status", "project", "last_update"
+            )
+        )
+        log.info(f"{len(tasks)} non-responsive tasks found")
+        if not tasks:
+            return 0
+
+        err_count = 0
+        for task in tasks:
+            log.info(
+                f"Stopping {task.id} ({task.name}), last updated at {task.last_update}"
+            )
+            try:
+                ChangeStatusRequest(
+                    task=task,
+                    new_status=TaskStatus.stopped,
+                    status_reason="Forced stop (non-responsive)",
+                    status_message="Forced stop (non-responsive)",
+                    force=True,
+                ).execute()
+            except errors.bad_request.FailedChangingTaskStatus:
+                err_count += 1
+
+        return len(tasks) - err_count

server/bll/task/param_utils.py

@@ -0,0 +1,201 @@
+import itertools
+from typing import Sequence, Tuple
+
+import dpath
+
+from apierrors import errors
+from database.model.task.task import Task
+from tools import safe_get
+from utilities.parameter_key_escaper import ParameterKeyEscaper
+
+
+hyperparams_default_section = "Args"
+hyperparams_legacy_type = "legacy"
+tf_define_section = "TF_DEFINE"
+
+
+def split_param_name(full_name: str, default_section: str) -> Tuple[str, str]:
+    """
+    Return parameter section and name. The section is either TF_DEFINE or the default one
+    """
+    if default_section is None:
+        return None, full_name
+
+    section, _, name = full_name.partition("/")
+    if section != tf_define_section:
+        return default_section, full_name
+
+    if not name:
+        raise errors.bad_request.ValidationError("Parameter name cannot be empty")
+    return section, name
+
+
+def _get_full_param_name(param: dict) -> str:
+    section = param.get("section")
+    if section != tf_define_section:
+        return param["name"]
+
+    return "/".join((section, param["name"]))
+
+
+def _remove_legacy_params(data: dict, with_sections: bool = False) -> int:
+    """
+    Remove the legacy params from the data dict and return the number of removed params
+    If the path not found then return 0
+    """
+    removed = 0
+    if not data:
+        return removed
+
+    if with_sections:
+        for section, section_data in list(data.items()):
+            removed += _remove_legacy_params(section_data)
+            if not section_data:
+                """If section is empty after removing legacy params then delete it"""
+                del data[section]
+    else:
+        for key, param in list(data.items()):
+            if param.get("type") == hyperparams_legacy_type:
+                removed += 1
+                del data[key]
+
+    return removed
+
+
+def _get_legacy_params(data: dict, with_sections: bool = False) -> Sequence[str]:
+    """
+    Remove the legacy params from the data dict and return the number of removed params
+    If the path not found then return 0
+    """
+    if not data:
+        return []
+
+    if with_sections:
+        return itertools.chain.from_iterable(
+            _get_legacy_params(section_data) for section_data in data.values()
+        )
+
+    return [
+        param for param in data.values() if param.get("type") == hyperparams_legacy_type
+    ]
+
+
+def params_prepare_for_save(fields: dict, previous_task: Task = None):
+    """
+    If legacy hyper params or configuration is passed then replace the corresponding section in the new structure
+    Escape all the section and param names for hyper params and configuration to make it mongo sage
+    """
+    for old_params_field, new_params_field, default_section in (
+        ("execution/parameters", "hyperparams", hyperparams_default_section),
+        ("execution/model_desc", "configuration", None),
+    ):
+        legacy_params = safe_get(fields, old_params_field)
+        if legacy_params is None:
+            continue
+
+        if (
+            not safe_get(fields, new_params_field)
+            and previous_task
+            and previous_task[new_params_field]
+        ):
+            previous_data = previous_task.to_proper_dict().get(new_params_field)
+            removed = _remove_legacy_params(
+                previous_data, with_sections=default_section is not None
+            )
+            if not legacy_params and not removed:
+                # if we only need to delete legacy fields from the db
+                # but they are not there then there is no point to proceed
+                continue
+
+            fields_update = {new_params_field: previous_data}
+            params_unprepare_from_saved(fields_update)
+            fields.update(fields_update)
+
+        for full_name, value in legacy_params.items():
+            section, name = split_param_name(full_name, default_section)
+            new_path = list(filter(None, (new_params_field, section, name)))
+            new_param = dict(name=name, type=hyperparams_legacy_type, value=str(value))
+            if section is not None:
+                new_param["section"] = section
+            dpath.new(fields, new_path, new_param)
+        dpath.delete(fields, old_params_field)
+
+    for param_field in ("hyperparams", "configuration"):
+        params = safe_get(fields, param_field)
+        if params:
+            escaped_params = {
+                ParameterKeyEscaper.escape(key): {
+                    ParameterKeyEscaper.escape(k): v for k, v in value.items()
+                }
+                if isinstance(value, dict)
+                else value
+                for key, value in params.items()
+            }
+            dpath.set(fields, param_field, escaped_params)
+
+
+def params_unprepare_from_saved(fields, copy_to_legacy=False):
+    """
+    Unescape all section and param names for hyper params and configuration
+    If copy_to_legacy is set then copy hyperparams and configuration data to the legacy location for the old clients
+    """
+    for param_field in ("hyperparams", "configuration"):
+        params = safe_get(fields, param_field)
+        if params:
+            unescaped_params = {
+                ParameterKeyEscaper.unescape(key): {
+                    ParameterKeyEscaper.unescape(k): v for k, v in value.items()
+                }
+                if isinstance(value, dict)
+                else value
+                for key, value in params.items()
+            }
+            dpath.set(fields, param_field, unescaped_params)
+
+    if copy_to_legacy:
+        for new_params_field, old_params_field, use_sections in (
+            (f"hyperparams", "execution/parameters", True),
+            (f"configuration", "execution/model_desc", False),
+        ):
+            legacy_params = _get_legacy_params(
+                safe_get(fields, new_params_field), with_sections=use_sections
+            )
+            if legacy_params:
+                dpath.new(
+                    fields,
+                    old_params_field,
+                    {_get_full_param_name(p): p["value"] for p in legacy_params},
+                )
+
+
+def _process_path(path: str):
+    """
+    Frontend does a partial escaping on the path so the all '.' in section and key names are escaped
+    Need to unescape and apply a full mongo escaping
+    """
+    parts = path.split(".")
+    if len(parts) < 2 or len(parts) > 3:
+        raise errors.bad_request.ValidationError("invalid task field", path=path)
+    return ".".join(
+        ParameterKeyEscaper.escape(ParameterKeyEscaper.unescape(p)) for p in parts
+    )
+
+
+def escape_paths(paths: Sequence[str]) -> Sequence[str]:
+    for old_prefix, new_prefix in (
+        ("execution.parameters", f"hyperparams.{hyperparams_default_section}"),
+        ("execution.model_desc", f"configuration"),
+    ):
+        path: str
+        paths = [path.replace(old_prefix, new_prefix) for path in paths]
+
+    for prefix in (
+        "hyperparams.",
+        "-hyperparams.",
+        "configuration.",
+        "-configuration.",
+    ):
+        paths = [
+            _process_path(path) if path.startswith(prefix) else path for path in paths
+        ]
+    return paths

server/bll/task/task_bll.py

@@ -1,41 +1,66 @@
-import re
 from collections import OrderedDict
-from datetime import datetime, timedelta
+from datetime import datetime
+from operator import attrgetter
+from random import random
 from time import sleep
-from typing import Collection, Sequence, Tuple, Any
+from typing import Collection, Sequence, Tuple, Any, Optional, List, Dict
 
+import dpath
+import pymongo.results
 import six
 from mongoengine import Q
 from six import string_types
 
+import database.utils as dbutils
 import es_factory
 from apierrors import errors
+from apimodels.tasks import Artifact as ApiArtifact
+from bll.organization import OrgBLL, Tags
 from config import config
 from database.errors import translate_errors_context
 from database.model.model import Model
 from database.model.project import Project
+from database.model.task.metrics import EventStats, MetricEventStats
 from database.model.task.output import Output
 from database.model.task.task import (
     Task,
     TaskStatus,
     TaskStatusMessage,
     TaskSystemTags,
+    ArtifactModes,
+    Artifact,
+    external_task_types,
 )
 from database.utils import get_company_or_none_constraint, id as create_id
 from service_repo import APICall
 from timing_context import TimingContext
-from utilities.threads_manager import ThreadsManager
+from utilities.dicts import deep_merge
+from utilities.parameter_key_escaper import ParameterKeyEscaper
+from .param_utils import params_prepare_for_save
 from .utils import ChangeStatusRequest, validate_status_change
 
+log = config.logger(__file__)
+org_bll = OrgBLL()
+
 
 class TaskBLL(object):
-    threads = ThreadsManager()
-
     def __init__(self, events_es=None):
         self.events_es = (
             events_es if events_es is not None else es_factory.connect("events")
         )
 
+    @classmethod
+    def get_types(cls, company, project_ids: Optional[Sequence]) -> set:
+        """
+        Return the list of unique task types used by company and public tasks
+        If project ids passed then only tasks from these projects are considered
+        """
+        query = get_company_or_none_constraint(company)
+        if project_ids:
+            query &= Q(project__in=project_ids)
+        res = Task.objects(query).distinct(field="type")
+        return set(res).intersection(external_task_types)
+
     @staticmethod
     def get_task_with_access(
         task_id, company_id, only=None, allow_public=False, requires_write_access=False
@@ -60,25 +85,24 @@ class TaskBLL(object):
 
     @staticmethod
     def get_by_id(
-        company_id,
-        task_id,
-        required_status=None,
-        required_dataset=None,
-        only_fields=None,
+        company_id, task_id, required_status=None, only_fields=None, allow_public=False,
     ):
+        if only_fields:
+            if isinstance(only_fields, string_types):
+                only_fields = [only_fields]
+            else:
+                only_fields = list(only_fields)
+            only_fields = only_fields + ["status"]
 
         with TimingContext("mongo", "task_by_id_all"):
-            qs = Task.objects(id=task_id, company=company_id)
-            if only_fields:
-                qs = (
-                    qs.only(only_fields)
-                    if isinstance(only_fields, string_types)
-                    else qs.only(*only_fields)
-                )
-                qs = qs.only(
-                    "status", "input"
-                )  # make sure all fields we rely on here are also returned
-            task = qs.first()
+            tasks = Task.get_many(
+                company=company_id,
+                query=Q(id=task_id),
+                allow_public=allow_public,
+                override_projection=only_fields,
+                return_dicts=False,
+            )
+            task = None if not tasks else tasks[0]
 
         if not task:
             raise errors.bad_request.InvalidTaskId(id=task_id)
@@ -86,17 +110,12 @@ class TaskBLL(object):
         if required_status and not task.status == required_status:
             raise errors.bad_request.InvalidTaskStatus(expected=required_status)
 
-        if required_dataset and required_dataset not in (
-            entry.dataset for entry in task.input.view.entries
-        ):
-            raise errors.bad_request.InvalidId(
-                "not in input view", dataset=required_dataset
-            )
-
         return task
 
     @staticmethod
-    def assert_exists(company_id, task_ids, only=None, allow_public=False):
+    def assert_exists(
+        company_id, task_ids, only=None, allow_public=False, return_tasks=True
+    ) -> Optional[Sequence[Task]]:
         task_ids = [task_ids] if isinstance(task_ids, six.string_types) else task_ids
         with translate_errors_context(), TimingContext("mongo", "task_exists"):
             ids = set(task_ids)
@@ -107,14 +126,13 @@ class TaskBLL(object):
                 return_dicts=False,
             )
             if only:
-                res = q.only(*only)
-                count = len(res)
-            else:
-                count = q.count()
-                res = q.first()
-            if count != len(ids):
+                q = q.only(*only)
+
+            if q.count() != len(ids):
                 raise errors.bad_request.InvalidTaskId(ids=task_ids)
-            return res
+
+            if return_tasks:
+                return list(q)
 
     @staticmethod
     def create(call: APICall, fields: dict):
@@ -145,30 +163,122 @@ class TaskBLL(object):
         return model
 
     @classmethod
-    def validate(cls, task: Task):
-        assert isinstance(task, Task)
+    def clone_task(
+        cls,
+        company_id,
+        user_id,
+        task_id,
+        name: Optional[str] = None,
+        comment: Optional[str] = None,
+        parent: Optional[str] = None,
+        project: Optional[str] = None,
+        tags: Optional[Sequence[str]] = None,
+        system_tags: Optional[Sequence[str]] = None,
+        hyperparams: Optional[dict] = None,
+        configuration: Optional[dict] = None,
+        execution_overrides: Optional[dict] = None,
+        validate_references: bool = False,
+    ) -> Task:
+        task = cls.get_by_id(company_id=company_id, task_id=task_id, allow_public=True)
+        execution_dict = task.execution.to_proper_dict() if task.execution else {}
+        execution_model_overriden = False
+        params_dict = {
+            field: value
+            for field, value in (
+                ("hyperparams", hyperparams),
+                ("configuration", configuration),
+            )
+            if value is not None
+        }
+        if execution_overrides:
+            params_dict["execution"] = {}
+            for legacy_param in ("parameters", "configuration"):
+                legacy_value = execution_overrides.pop(legacy_param, None)
+                if legacy_value is not None:
+                    params_dict["execution"] = legacy_value
+            execution_dict = deep_merge(execution_dict, execution_overrides)
+            execution_model_overriden = execution_overrides.get("model") is not None
+        params_prepare_for_save(params_dict, previous_task=task)
 
-        if task.parent and not Task.get(
-            company=task.company, id=task.parent, _only=("id",), include_public=True
+        artifacts = execution_dict.get("artifacts")
+        if artifacts:
+            execution_dict["artifacts"] = [
+                a for a in artifacts if a.get("mode") != ArtifactModes.output
+            ]
+        now = datetime.utcnow()
+
+        with translate_errors_context():
+            new_task = Task(
+                id=create_id(),
+                user=user_id,
+                company=company_id,
+                created=now,
+                last_update=now,
+                name=name or task.name,
+                comment=comment or task.comment,
+                parent=parent or task.parent,
+                project=project or task.project,
+                tags=tags or task.tags,
+                system_tags=system_tags or [],
+                type=task.type,
+                script=task.script,
+                output=Output(destination=task.output.destination)
+                if task.output
+                else None,
+                execution=execution_dict,
+                configuration=params_dict.get("configuration") or task.configuration,
+                hyperparams=params_dict.get("hyperparams") or task.hyperparams,
+            )
+            cls.validate(
+                new_task,
+                validate_model=validate_references or execution_model_overriden,
+                validate_parent=validate_references or parent,
+                validate_project=validate_references or project,
+            )
+            new_task.save()
+
+            if task.project == new_task.project:
+                updated_tags = tags
+                updated_system_tags = system_tags
+            else:
+                updated_tags = new_task.tags
+                updated_system_tags = new_task.system_tags
+            org_bll.update_tags(
+                company_id,
+                Tags.Task,
+                project=new_task.project,
+                tags=updated_tags,
+                system_tags=updated_system_tags,
+            )
+
+        return new_task
+
+    @classmethod
+    def validate(
+        cls,
+        task: Task,
+        validate_model=True,
+        validate_parent=True,
+        validate_project=True,
+    ):
+        if (
+            validate_parent
+            and task.parent
+            and not Task.get(
+                company=task.company, id=task.parent, _only=("id",), include_public=True
+            )
         ):
             raise errors.bad_request.InvalidTaskId("invalid parent", parent=task.parent)
 
-        if task.project:
-            Project.get_for_writing(company=task.company, id=task.project)
+        if (
+            validate_project
+            and task.project
+            and not Project.get_for_writing(company=task.company, id=task.project)
+        ):
+            raise errors.bad_request.InvalidProjectId(id=task.project)
 
-        cls.validate_execution_model(task)
-
-        if task.execution:
-            if task.execution.parameters:
-                cls._validate_execution_parameters(task.execution.parameters)
-
-    @staticmethod
-    def _validate_execution_parameters(parameters):
-        invalid_keys = [k for k in parameters if re.search(r"\s", k)]
-        if invalid_keys:
-            raise errors.bad_request.ValidationError(
-                "execution.parameters keys contain whitespace", keys=invalid_keys
-            )
+        if validate_model:
+            cls.validate_execution_model(task)
 
     @staticmethod
     def get_unique_metric_variants(company_id, project_ids=None):
@@ -208,7 +318,7 @@ class TaskBLL(object):
         ]
 
         with translate_errors_context():
-            result = Task.aggregate(*pipeline)
+            result = Task.aggregate(pipeline)
             return [r["metrics"][0] for r in result]
 
     @staticmethod
@@ -226,7 +336,8 @@ class TaskBLL(object):
         last_update: datetime = None,
         last_iteration: int = None,
         last_iteration_max: int = None,
-        last_values: Sequence[Tuple[Tuple[str, ...], Any]] = None,
+        last_scalar_values: Sequence[Tuple[Tuple[str, ...], Any]] = None,
+        last_events: Dict[str, Dict[str, dict]] = None,
         **extra_updates,
     ):
         """
@@ -238,7 +349,8 @@ class TaskBLL(object):
             task's last iteration value.
         :param last_iteration_max: Last reported iteration. Use this to conditionally set a value only
             if the current task's last iteration value is smaller than the provided value.
-        :param last_values: Last reported metrics summary (value, metric, variant).
+        :param last_scalar_values: Last reported metrics summary for scalar events (value, metric, variant).
+        :param last_events: Last reported metrics summary (value, metric, event type).
         :param extra_updates: Extra task updates to include in this update call.
         :return:
         """
@@ -249,16 +361,34 @@ class TaskBLL(object):
         elif last_iteration_max is not None:
             extra_updates.update(max__last_iteration=last_iteration_max)
 
-        if last_values is not None:
+        if last_scalar_values is not None:
 
             def op_path(op, *path):
                 return "__".join((op, "last_metrics") + path)
 
-            for path, value in last_values:
-                extra_updates[op_path("set", *path)] = value
-                if path[-1] == "value":
+            for path, value in last_scalar_values:
+                if path[-1] == "min_value":
                     extra_updates[op_path("min", *path[:-1], "min_value")] = value
+                elif path[-1] == "max_value":
                     extra_updates[op_path("max", *path[:-1], "max_value")] = value
+                else:
+                    extra_updates[op_path("set", *path)] = value
+
+        if last_events is not None:
+
+            def events_per_type(metric_data: Dict[str, dict]) -> Dict[str, EventStats]:
+                return {
+                    event_type: EventStats(last_update=event["timestamp"])
+                    for event_type, event in metric_data.items()
+                }
+
+            metric_stats = {
+                dbutils.hash_field_name(metric_key): MetricEventStats(
+                    metric=metric_key, event_stats_by_type=events_per_type(metric_data)
+                )
+                for metric_key, metric_data in last_events.items()
+            }
+            extra_updates["metric_stats"] = metric_stats
 
         Task.objects(id=task_id, company=company_id).update(
             upsert=False, last_update=last_update, **extra_updates
@@ -373,7 +503,7 @@ class TaskBLL(object):
         :return: updated task fields
         """
 
-        task = TaskBLL.get_task_with_access(
+        task = cls.get_task_with_access(
             task_id,
             company_id=company_id,
             only=(
@@ -412,80 +542,125 @@ class TaskBLL(object):
         ).execute()
 
     @classmethod
-    @threads.register("non_responsive_tasks_watchdog", daemon=True)
-    def start_non_responsive_tasks_watchdog(cls):
-        log = config.logger("non_responsive_tasks_watchdog")
-        relevant_status = (TaskStatus.in_progress,)
-        threshold = timedelta(
-            seconds=config.get(
-                "services.tasks.non_responsive_tasks_watchdog.threshold_sec", 7200
-            )
-        )
-        while True:
-            sleep(
-                config.get(
-                    "services.tasks.non_responsive_tasks_watchdog.watch_interval_sec",
-                    900,
-                )
-            )
-            try:
+    def add_or_update_artifacts(
+        cls, task_id: str, company_id: str, artifacts: List[ApiArtifact]
+    ) -> Tuple[List[str], List[str]]:
+        key = attrgetter("key", "mode")
 
-                ref_time = datetime.utcnow() - threshold
+        if not artifacts:
+            return [], []
 
-                log.info(
-                    f"Starting cleanup cycle for running tasks last updated before {ref_time}"
+        with translate_errors_context(), TimingContext("mongo", "update_artifacts"):
+            artifacts: List[Artifact] = [
+                Artifact(**artifact.to_struct()) for artifact in artifacts
+            ]
+
+            attempts = int(config.get("services.tasks.artifacts.update_attempts", 10))
+
+            for retry in range(attempts):
+                task = cls.get_task_with_access(
+                    task_id, company_id=company_id, requires_write_access=True
                 )
 
-                tasks = list(
-                    Task.objects(
-                        status__in=relevant_status, last_update__lt=ref_time
-                    ).only("id", "name", "status", "project", "last_update")
+                current = list(map(key, task.execution.artifacts))
+                updated = [a for a in artifacts if key(a) in current]
+                added = [a for a in artifacts if a not in updated]
+
+                filter = {"_id": task_id, "company": company_id}
+                update = {}
+                array_filters = None
+                if current:
+                    filter["execution.artifacts"] = {
+                        "$size": len(current),
+                        "$all": [
+                            *(
+                                {"$elemMatch": {"key": key, "mode": mode}}
+                                for key, mode in current
+                            )
+                        ],
+                    }
+                else:
+                    filter["$or"] = [
+                        {"execution.artifacts": {"$exists": False}},
+                        {"execution.artifacts": {"$size": 0}},
+                    ]
+
+                if added:
+                    update["$push"] = {
+                        "execution.artifacts": {"$each": [a.to_mongo() for a in added]}
+                    }
+                if updated:
+                    update["$set"] = {
+                        f"execution.artifacts.$[artifact{index}]": artifact.to_mongo()
+                        for index, artifact in enumerate(updated)
+                    }
+                    array_filters = [
+                        {
+                            f"artifact{index}.key": artifact.key,
+                            f"artifact{index}.mode": artifact.mode,
+                        }
+                        for index, artifact in enumerate(updated)
+                    ]
+
+                if not update:
+                    return [], []
+
+                result: pymongo.results.UpdateResult = Task._get_collection().update_one(
+                    filter=filter,
+                    update=update,
+                    array_filters=array_filters,
+                    upsert=False,
                 )
 
-                if tasks:
+                if result.matched_count >= 1:
+                    break
 
-                    log.info(f"Stopping {len(tasks)} non-responsive tasks")
+                wait_msec = random() * int(
+                    config.get("services.tasks.artifacts.update_retry_msec", 500)
+                )
 
-                    for task in tasks:
-                        log.info(
-                            f"Stopping {task.id} ({task.name}), last updated at {task.last_update}"
-                        )
-                        ChangeStatusRequest(
-                            task=task,
-                            new_status=TaskStatus.stopped,
-                            status_reason="Forced stop (non-responsive)",
-                            status_message="Forced stop (non-responsive)",
-                            force=True,
-                        ).execute()
+                log.warning(
+                    f"Failed to update artifacts for task {task_id} (updated by another party),"
+                    f" retrying {retry+1}/{attempts} in {wait_msec}ms"
+                )
 
-                log.info(f"Done")
+                sleep(wait_msec / 1000)
+            else:
+                raise errors.server_error.UpdateFailed(
+                    "task artifacts updated by another party"
+                )
 
-            except Exception as ex:
-                log.exception(f"Failed stopping tasks: {str(ex)}")
+            return [a.key for a in added], [a.key for a in updated]
 
     @staticmethod
-    def get_aggregated_project_execution_parameters(
+    def get_aggregated_project_parameters(
         company_id,
         project_ids: Sequence[str] = None,
         page: int = 0,
         page_size: int = 500,
-    ) -> Tuple[int, int, Sequence[str]]:
+    ) -> Tuple[int, int, Sequence[dict]]:
 
         page = max(0, page)
         page_size = max(1, page_size)
-
         pipeline = [
             {
                 "$match": {
                     "company": company_id,
-                    "execution.parameters": {"$exists": True, "$gt": {}},
+                    "hyperparams": {"$exists": True, "$gt": {}},
                     **({"project": {"$in": project_ids}} if project_ids else {}),
                 }
             },
-            {"$project": {"parameters": {"$objectToArray": "$execution.parameters"}}},
-            {"$unwind": "$parameters"},
-            {"$group": {"_id": "$parameters.k"}},
-            {"$sort": {"_id": 1}},
+            {"$project": {"sections": {"$objectToArray": "$hyperparams"}}},
+            {"$unwind": "$sections"},
+            {
+                "$project": {
+                    "section": "$sections.k",
+                    "names": {"$objectToArray": "$sections.v"},
+                }
+            },
+            {"$unwind": "$names"},
+            {"$group": {"_id": {"section": "$section", "name": "$names.k"}}},
+            {"$sort": OrderedDict({"_id.section": 1, "_id.name": 1})},
             {
                 "$group": {
                     "_id": 1,
@@ -502,10 +677,7 @@ class TaskBLL(object):
         ]
 
         with translate_errors_context():
-            result = next(
-                Task.aggregate(*pipeline),
-                None,
-            )
+            result = next(Task.aggregate(pipeline), None)
 
         total = 0
         remaining = 0
@@ -513,7 +685,15 @@ class TaskBLL(object):
 
         if result:
             total = int(result.get("total", -1))
-            results = [r["_id"] for r in result.get("results", [])]
+            results = [
+                {
+                    "section": ParameterKeyEscaper.unescape(
+                        dpath.get(r, "_id/section")
+                    ),
+                    "name": ParameterKeyEscaper.unescape(dpath.get(r, "_id/name")),
+                }
+                for r in result.get("results", [])
+            ]
             remaining = max(0, total - (len(results) + page * page_size))
 
         return total, remaining, results

server/bll/util.py

@@ -1,7 +1,9 @@
+import functools
 from operator import itemgetter
 from typing import Sequence, Optional, Callable, Tuple, Dict, Any, Set
 
 from database.model import AttributedDocument
+from database.model.settings import Settings
 
 
 def extract_properties_to_lists(
@@ -33,14 +35,21 @@ class SetFieldsResolver:
     SET_MODIFIERS = ("min", "max")
 
     def __init__(self, set_fields: Dict[str, Any]):
-        self.orig_fields = set_fields
-        self.fields = {
-            f: fname
-            for f, modifier, dunder, fname in (
-                (f,) + f.partition("__") for f in set_fields.keys()
-            )
-            if dunder and modifier in self.SET_MODIFIERS
-        }
+        self.orig_fields = {}
+        self.fields = {}
+        self.add_fields(**set_fields)
+
+    def add_fields(self, **set_fields: Any):
+        self.orig_fields.update(set_fields)
+        self.fields.update(
+            {
+                f: fname
+                for f, modifier, dunder, fname in (
+                    (f,) + f.partition("__") for f in set_fields.keys()
+                )
+                if dunder and modifier in self.SET_MODIFIERS
+            }
+        )
 
     def _get_updated_name(self, doc: AttributedDocument, name: str) -> str:
         if name in self.fields and doc.get_field_value(self.fields[name]) is None:
@@ -64,3 +73,8 @@ class SetFieldsResolver:
         in the format suitable for projection (dot separated)
         """
         return set(name.replace("__", ".") for name in self.fields.values())
+
+
+@functools.lru_cache()
+def get_server_uuid() -> Optional[str]:
+    return Settings.get_by_key("server.uuid")

server/bll/workers/__init__.py

@@ -4,6 +4,7 @@ from typing import Sequence, Set, Optional
 
 import attr
 import elasticsearch.helpers
+
 import es_factory
 from apierrors import APIError
 from apierrors.errors import bad_request, server_error
@@ -20,12 +21,12 @@ from config import config
 from database.errors import translate_errors_context
 from database.model.auth import User
 from database.model.company import Company
+from database.model.project import Project
 from database.model.queue import Queue
 from database.model.task.task import Task
-from service_repo.redis_manager import redman
+from redis_manager import redman
 from timing_context import TimingContext
 from tools import safe_get
-
 from .stats import WorkerStats
 
 log = config.logger(__file__)
@@ -33,9 +34,9 @@ log = config.logger(__file__)
 
 class WorkerBLL:
     def __init__(self, es=None, redis=None):
-        self.es = es if es is not None else es_factory.connect("workers")
-        self.redis = redis if redis is not None else redman.connection("workers")
-        self._stats = WorkerStats(self.es)
+        self.es_client = es or es_factory.connect("workers")
+        self.redis = redis or redman.connection("workers")
+        self._stats = WorkerStats(self.es_client)
 
     @property
     def stats(self) -> WorkerStats:
@@ -49,6 +50,7 @@ class WorkerBLL:
         ip: str = "",
         queues: Sequence[str] = None,
         timeout: int = 0,
+        tags: Sequence[str] = None,
     ) -> WorkerEntry:
         """
         Register a worker
@@ -58,6 +60,7 @@ class WorkerBLL:
         :param ip: the real ip of the worker
         :param queues: queues reported as being monitored by the worker
         :param timeout: registration expiration timeout in seconds
+        :param tags: a list of tags for this worker
         :raise bad_request.InvalidUserId: in case the calling user or company does not exist
         :return: worker entry instance
         """
@@ -91,6 +94,7 @@ class WorkerBLL:
                 register_time=now,
                 register_timeout=timeout,
                 last_activity_time=now,
+                tags=tags,
             )
 
             self.redis.setex(key, timedelta(seconds=timeout), entry.to_json())
@@ -113,12 +117,15 @@ class WorkerBLL:
             raise bad_request.WorkerNotRegistered(worker=worker)
 
     def status_report(
-        self, company_id: str, user_id: str, ip: str, report: StatusReportRequest
+        self, company_id: str, user_id: str, ip: str, report: StatusReportRequest, tags: Sequence[str] = None,
     ) -> None:
         """
         Write worker status report
         :param company_id: worker's company ID
         :param user_id: user_id ID under which this worker is running
+        :param ip: worker IP
+        :param report: the report itself
+        :param tags: tags for this worker
         :raise bad_request.InvalidTaskId: the reported task was not found
         :return: worker entry instance
         """
@@ -129,6 +136,9 @@ class WorkerBLL:
             now = datetime.utcnow()
             entry.last_activity_time = now
 
+            if tags is not None:
+                entry.tags = tags
+
             if report.machine_stats:
                 self._log_stats_to_es(
                     company_id=company_id,
@@ -146,6 +156,7 @@ class WorkerBLL:
 
             if not report.task:
                 entry.task = None
+                entry.project = None
             else:
                 with translate_errors_context():
                     query = dict(id=report.task, company=company_id)
@@ -160,6 +171,12 @@ class WorkerBLL:
                         raise bad_request.InvalidTaskId(**query)
                     entry.task = IdNameEntry(id=task.id, name=task.name)
 
+                    entry.project = None
+                    if task.project:
+                        project = Project.objects(id=task.project).only("name").first()
+                        if project:
+                            entry.project = IdNameEntry(id=project.id, name=project.name)
+
             entry.last_report_time = now
         except APIError:
             raise
@@ -223,7 +240,7 @@ class WorkerBLL:
                 },
             ]
             queues_info = {
-                res["_id"]: res for res in Queue.objects.aggregate(*projection)
+                res["_id"]: res for res in Queue.objects.aggregate(projection)
             }
             task_ids = task_ids.union(
                 filter(
@@ -369,7 +386,6 @@ class WorkerBLL:
         def make_doc(category, metric, variant, value) -> dict:
             return dict(
                 _index=es_index,
-                _type="stat",
                 _source=dict(
                     timestamp=timestamp,
                     worker=worker,
@@ -396,7 +412,7 @@ class WorkerBLL:
                     for i, val in enumerate(value)
                 )
 
-        es_res = elasticsearch.helpers.bulk(self.es, actions)
+        es_res = elasticsearch.helpers.bulk(self.es_client, actions)
         added, errors = es_res[:2]
         return (added == len(actions)) and not errors
 

server/bll/workers/stats.py

@@ -25,7 +25,6 @@ class WorkerStats:
     def _search_company_stats(self, company_id: str, es_req: dict) -> dict:
         return self.es.search(
             index=f"{self.worker_stats_prefix_for_company(company_id)}*",
-            doc_type="stat",
             body=es_req,
         )
 
@@ -53,7 +52,7 @@ class WorkerStats:
 
         res = self._search_company_stats(company_id, es_req)
 
-        if not res["hits"]["total"]:
+        if not res["hits"]["total"]["value"]:
             raise bad_request.WorkerStatsNotFound(
                 f"No statistic metrics found for the company {company_id} and workers {worker_ids}"
             )
@@ -87,7 +86,7 @@ class WorkerStats:
                 "dates": {
                     "date_histogram": {
                         "field": "timestamp",
-                        "interval": f"{request.interval}s",
+                        "fixed_interval": f"{request.interval}s",
                         "min_doc_count": 1,
                     },
                     "aggs": {
@@ -216,7 +215,7 @@ class WorkerStats:
                 "dates": {
                     "date_histogram": {
                         "field": "timestamp",
-                        "interval": f"{interval}s",
+                        "fixed_interval": f"{interval}s",
                     },
                     "aggs": {"workers_count": {"cardinality": {"field": "worker"}}},
                 }

server/config/basic.py

@@ -1,5 +1,6 @@
 import logging
 import os
+import platform
 from functools import reduce
 from os import getenv
 from os.path import expandvars
@@ -15,7 +16,7 @@ from pyparsing import (
 
 DEFAULT_EXTRA_CONFIG_PATH = "/opt/trains/config"
 EXTRA_CONFIG_PATH_ENV_KEY = "TRAINS_CONFIG_DIR"
-EXTRA_CONFIG_PATH_SEP = ":"
+EXTRA_CONFIG_PATH_SEP = ":" if platform.system() != "Windows" else ';'
 
 EXTRA_CONFIG_VALUES_ENV_KEY_SEP = "__"
 EXTRA_CONFIG_VALUES_ENV_KEY_PREFIX = f"TRAINS{EXTRA_CONFIG_VALUES_ENV_KEY_SEP}"
@@ -47,7 +48,7 @@ class BasicConfig:
     def logger(self, name):
         if Path(name).is_file():
             name = Path(name).stem
-        path = ".".join((self.prefix, Path(name).stem))
+        path = ".".join((self.prefix, name))
         return logging.getLogger(path)
 
     def _read_extra_env_config_values(self):
@@ -57,7 +58,7 @@ class BasicConfig:
 
         keys = sorted(k for k in os.environ if k.startswith(prefix))
         for key in keys:
-            path = key[len(prefix) :].replace(EXTRA_CONFIG_VALUES_ENV_KEY_SEP, ".")
+            path = key[len(prefix) :].replace(EXTRA_CONFIG_VALUES_ENV_KEY_SEP, ".").lower()
             result = ConfigTree.merge_configs(
                 result, ConfigFactory.parse_string(f"{path}: {os.environ[key]}")
             )
@@ -77,7 +78,7 @@ class BasicConfig:
             if not path.is_dir() and str(path) != DEFAULT_EXTRA_CONFIG_PATH
         ]
         if invalid:
-            print(f"WARNING: Invalid paths in {key} env var: {' '.join(invalid)}")
+            print(f"WARNING: Invalid paths in {key} env var: {' '.join(map(str, invalid))}")
         return [path for path in paths if path.is_dir()]
 
     def _load(self, verbose=True):

server/config/default/apiserver.conf

@@ -26,6 +26,17 @@
         check_max_version: false
     }
 
+    pre_populate {
+        enabled: false
+        zip_files: ["/path/to/export.zip"]
+        fail_on_error: false
+        # artifacts_path: "/mnt/fileserver"
+    }
+
+    # time in seconds to take an exclusive lock to init es and mongodb
+    # not including the pre_populate
+    db_init_timout: 120
+
     mongo {
         # controls whether FieldDoesNotExist exception will be raised for any extra attribute existing in stored data
         # but not declared in a data model
@@ -36,6 +47,17 @@
         }
     }
 
+    elastic {
+        probing {
+            # settings for inital probing of elastic connection
+            max_retries: 4
+            timeout: 30
+        }
+        upgrade_monitoring {
+            v16_migration_verification: true
+        }
+    }
+
     auth {
         # verify user tokens
         verify_user_tokens: false
@@ -101,4 +123,18 @@
         # GET request timeout
         request_timeout_sec: 3.0
     }
+
+    statistics {
+        # Note: statistics are sent ONLY if the user has actively opted-in
+        supported: true
+
+        url: "https://updates.trains.allegro.ai/stats"
+
+        report_interval_hours: 24
+        agent_relevant_threshold_days: 30
+
+        max_retries: 5
+        max_backoff_sec: 5
+    }
+
 }

server/config/default/hosts.conf

@@ -1,21 +1,21 @@
 elastic {
   events {
-    hosts: [{host: "127.0.0.1", port: 9200}]
+    hosts: [{host: "127.0.0.1", port: 9211}]
     args {
       timeout: 60
       dead_timeout: 10
-      max_retries: 5
+      max_retries: 3
       retry_on_timeout: true
     }
     index_version: "1"
   }
 
   workers {
-    hosts: [{host:"127.0.0.1", port:9200}]
+    hosts: [{host:"127.0.0.1", port:9211}]
     args {
       timeout: 60
       dead_timeout: 10
-      max_retries: 5
+      max_retries: 3
       retry_on_timeout: true
     }
     index_version: "1"
@@ -32,6 +32,11 @@ mongo {
 }
 
 redis {
+  apiserver {
+      host: "127.0.0.1"
+      port: 6379
+      db: 0
+  }
   workers {
     host: "127.0.0.1"
     port: 6379

server/config/default/secure.conf

@@ -13,17 +13,21 @@
     credentials {
         # system credentials as they appear in the auth DB, used for intra-service communications
         apiserver {
+            role: "system"
             user_key: "62T8CP7HGBC6647XF9314C2VY67RJO"
             user_secret: "FhS8VZv_I4%6Mo$8S1BWc$n$=o1dMYSivuiWU-Vguq7qGOKskG-d+b@tn_Iq"
         }
         webserver {
+            role: "system"
             user_key: "EYVQ385RW7Y2QQUH88CZ7DWIQ1WUHP"
             user_secret: "yfc8KQo*GMXb*9p((qcYC7ByFIpF7I&4VH3BfUYXH%o9vX1ZUZQEEw1Inc)S"
+            revoke_in_fixed_mode: true
         }
         tests {
+            role: "user"
+            display_name: "Default User"
             user_key: "EGRTCO8JMSIGI6S39GTP43NFWXDQOW"
             user_secret: "x!XTov_G-#vspE*Y(h$Anm&DIc5Ou-F)jsl$PdOyj5wG1&E!Z8"
-
         }
     }
 }

server/config/default/services/auth.conf

@@ -0,0 +1,16 @@
+fixed_users {
+  guest {
+    enabled: false
+
+    default_company: "025315a9321f49f8be07f5ac48fbcf92"
+
+    name: "Guest"
+    username: "guest"
+    password: "guest"
+
+    # Allow access only to the following endpoints when using user/pass credentials
+    allow_endpoints: [
+      "auth.login"
+    ]
+  }
+}

server/config/default/services/events.conf

@@ -1,3 +1,13 @@
-{
-    es_index_prefix:"events"
-}
+es_index_prefix: "events"
+
+ignore_iteration {
+    metrics: [":monitor:machine", ":monitor:gpu"]
+}
+
+# max number of concurrent queries to ES when calculating events metrics
+# should not exceed the amount of concurrent connections set in the ES driver
+max_metrics_concurrency: 4
+
+events_retrieval {
+    state_expiration_sec: 3600
+}

server/config/default/services/organization.conf

@@ -0,0 +1,3 @@
+tags_cache {
+  expiration_seconds: 3600
+}

server/config/default/services/projects.conf

@@ -0,0 +1,8 @@
+# Order of featured projects, by name or ID
+featured_order: [
+  #  {id: "<project-id>"}
+  #  OR
+  #  {name: "<project-name>"}
+  #  OR
+  #  {name_regex: "<python-regex>"}
+]

server/config/default/services/tasks.conf

@@ -1,7 +1,16 @@
 non_responsive_tasks_watchdog {
+    enabled: true
+
     # In-progress tasks older than this value in seconds will be stopped by the watchdog
     threshold_sec: 7200
 
     # Watchdog will sleep for this number of seconds after each cycle
     watch_interval_sec: 900
 }
+
+artifacts {
+    update_attempts: 10
+    update_retry_msec: 500
+}
+
+multi_task_histogram_limit: 100

server/config/info.py

@@ -1,28 +1,47 @@
 from functools import lru_cache
+from os import getenv
 from pathlib import Path
+from version import __version__
+
+from config import config
 
 root = Path(__file__).parent.parent
 
 
+def _get(prop_name, env_suffix=None, default=""):
+    value = getenv(f"TRAINS_SERVER_{env_suffix or prop_name}")
+    if value:
+        return value
+
+    try:
+        return (root / prop_name).read_text().strip()
+    except FileNotFoundError:
+        return default
+
+
 @lru_cache()
 def get_build_number():
-    try:
-        return (root / "BUILD").read_text().strip()
-    except FileNotFoundError:
-        return ""
+    return _get("BUILD")
 
 
 @lru_cache()
 def get_version():
-    try:
-        return (root / "VERSION").read_text().strip()
-    except FileNotFoundError:
-        return ""
+    return _get("VERSION", default=__version__)
 
 
 @lru_cache()
 def get_commit_number():
-    try:
-        return (root / "COMMIT").read_text().strip()
-    except FileNotFoundError:
-        return ""
+    return _get("COMMIT")
+
+
+@lru_cache()
+def get_deployment_type() -> str:
+    return _get("DEPLOY", env_suffix="DEPLOYMENT_TYPE", default="manual")
+
+
+def get_default_company():
+    return config.get("apiserver.default_company")
+
+
+missed_es_upgrade = False
+es_connection_error = False

server/database/__init__.py

@@ -1,5 +1,6 @@
 from os import getenv
 
+from boltons.iterutils import first
 from furl import furl
 from jsonmodels import models
 from jsonmodels.errors import ValidationError
@@ -11,14 +12,16 @@ from config import config
 from .defs import Database
 from .utils import get_items
 
-from boltons.iterutils import first
-
 log = config.logger("database")
 
 strict = config.get("apiserver.mongo.strict", True)
 
-OVERRIDE_HOST_ENV_KEY = ("MONGODB_SERVICE_HOST", "MONGODB_SERVICE_SERVICE_HOST")
-OVERRIDE_PORT_ENV_KEY = "MONGODB_SERVICE_PORT"
+OVERRIDE_HOST_ENV_KEY = (
+    "TRAINS_MONGODB_SERVICE_HOST",
+    "MONGODB_SERVICE_HOST",
+    "MONGODB_SERVICE_SERVICE_HOST",
+)
+OVERRIDE_PORT_ENV_KEY = ("TRAINS_MONGODB_SERVICE_PORT", "MONGODB_SERVICE_PORT")
 
 _entries = []
 
@@ -41,7 +44,7 @@ def initialize():
     if override_hostname:
         log.info(f"Using override mongodb host {override_hostname}")
 
-    override_port = getenv(OVERRIDE_PORT_ENV_KEY)
+    override_port = first(map(getenv, OVERRIDE_PORT_ENV_KEY), None)
     if override_port:
         log.info(f"Using override mongodb port {override_port}")
 
@@ -76,6 +79,10 @@ def get_entries():
     return _entries
 
 
+def get_hosts():
+    return [entry.host for entry in get_entries()]
+
+
 def get_aliases():
     return [entry.alias for entry in get_entries()]
 

server/database/fields.py

@@ -14,6 +14,9 @@ from mongoengine import (
     DictField,
     DynamicField,
 )
+from mongoengine.fields import key_not_string, key_starts_with_dollar
+
+NoneType = type(None)
 
 
 class LengthRangeListField(ListField):
@@ -125,17 +128,39 @@ def contains_empty_key(d):
             return True
 
 
-class SafeMapField(MapField):
+class DictValidationMixin:
+    """
+    DictField validation in MongoEngine requires default alias and permissions to access DB version:
+    https://github.com/MongoEngine/mongoengine/issues/2239
+    This is a stripped down implementation that does not require any of the above and implies Mongo ver 3.6+
+    """
+
+    def _safe_validate(self: DictField, value):
+        if not isinstance(value, dict):
+            self.error("Only dictionaries may be used in a DictField")
+
+        if key_not_string(value):
+            msg = "Invalid dictionary key - documents must have only string keys"
+            self.error(msg)
+
+        if key_starts_with_dollar(value):
+            self.error(
+                'Invalid dictionary key name - keys may not startswith "$" characters'
+            )
+        super(DictField, self).validate(value)
+
+
+class SafeMapField(MapField, DictValidationMixin):
     def validate(self, value):
-        super(SafeMapField, self).validate(value)
+        self._safe_validate(value)
 
         if contains_empty_key(value):
             self.error("Empty keys are not allowed in a MapField")
 
 
-class SafeDictField(DictField):
+class SafeDictField(DictField, DictValidationMixin):
     def validate(self, value):
-        super(SafeDictField, self).validate(value)
+        self._safe_validate(value)
 
         if contains_empty_key(value):
             self.error("Empty keys are not allowed in a DictField")
@@ -146,6 +171,7 @@ class SafeSortedListField(SortedListField):
     SortedListField that does not raise an error in case items are not comparable
     (in which case they will be sorted by their string representation)
     """
+
     def to_mongo(self, *args, **kwargs):
         try:
             return super(SafeSortedListField, self).to_mongo(*args, **kwargs)
@@ -155,7 +181,10 @@ class SafeSortedListField(SortedListField):
     def _safe_to_mongo(self, value, use_db_field=True, fields=None):
         value = super(SortedListField, self).to_mongo(value, use_db_field, fields)
         if self._ordering is not None:
-            def key(v): return str(itemgetter(self._ordering)(v))
+
+            def key(v):
+                return str(itemgetter(self._ordering)(v))
+
         else:
             key = str
         return sorted(value, key=key, reverse=self._order_reverse)

server/database/model/auth.py

@@ -32,6 +32,8 @@ class Role(object):
     """ Company user """
     annotator = "annotator"
     """ Annotator with limited access"""
+    guest = "guest"
+    """ Guest user. Read Only."""
 
     @classmethod
     def get_system_roles(cls) -> set:
@@ -43,6 +45,7 @@ class Role(object):
 
 
 class Credentials(EmbeddedDocument):
+    meta = {"strict": False}
     key = StringField(required=True)
     secret = StringField(required=True)
     last_used = DateTimeField()
@@ -52,7 +55,7 @@ class User(DbModelMixin, AuthDocument):
     meta = {"db_alias": Database.auth, "strict": strict}
 
     id = StringField(primary_key=True)
-    name = StringField(unique_with="company")
+    name = StringField()
 
     created = DateTimeField()
     """ User auth entry creation time """

server/database/model/base.py

@@ -1,14 +1,15 @@
 import re
 from collections import namedtuple
 from functools import reduce
-from typing import Collection, Sequence, Union
+from typing import Collection, Sequence, Union, Optional, Type, Tuple
 
-from boltons.iterutils import first
+from boltons.iterutils import first, bucketize, partition
 from dateutil.parser import parse as parse_datetime
 from mongoengine import Q, Document, ListField, StringField
 from pymongo.command_cursor import CommandCursor
 
 from apierrors import errors
+from apierrors.base import BaseError
 from config import config
 from database.errors import MakeGetAllQueryError
 from database.projection import project_dict, ProjectionHelper
@@ -34,7 +35,12 @@ class AuthDocument(Document):
 
 
 class ProperDictMixin(object):
-    def to_proper_dict(self, strip_private=True, only=None, extra_dict=None) -> dict:
+    def to_proper_dict(
+        self: Union["ProperDictMixin", Document],
+        strip_private=True,
+        only=None,
+        extra_dict=None,
+    ) -> dict:
         return self.properize_dict(
             self.to_mongo(use_db_field=False).to_dict(),
             strip_private=strip_private,
@@ -60,7 +66,7 @@ class ProperDictMixin(object):
 
 class GetMixin(PropsMixin):
     _text_score = "$text_score"
-
+    _projection_key = "projection"
     _ordering_key = "order_by"
     _search_text_key = "search_text"
 
@@ -71,6 +77,8 @@ class GetMixin(PropsMixin):
     }
     MultiFieldParameters = namedtuple("MultiFieldParameters", "pattern fields")
 
+    _field_collation_overrides = {}
+
     class QueryParameterOptions(object):
         def __init__(
             self,
@@ -91,11 +99,48 @@ class GetMixin(PropsMixin):
             self.list_fields = list_fields
             self.pattern_fields = pattern_fields
 
+    class ListFieldBucketHelper:
+        op_prefix = "__$"
+        legacy_exclude_prefix = "-"
+
+        _default = "in"
+        _ops = {"not": "nin"}
+        _next = _default
+
+        def __init__(self, legacy=False):
+            self._legacy = legacy
+
+        def key(self, v):
+            if v is None:
+                self._next = self._default
+                return self._default
+            elif self._legacy and v.startswith(self.legacy_exclude_prefix):
+                self._next = self._default
+                return self._ops["not"]
+            elif v.startswith(self.op_prefix):
+                self._next = self._ops.get(v[len(self.op_prefix) :], self._default)
+                return None
+
+            next_ = self._next
+            self._next = self._default
+            return next_
+
+        def value_transform(self, v):
+            if self._legacy and v and v.startswith(self.legacy_exclude_prefix):
+                return v[len(self.legacy_exclude_prefix) :]
+            return v
+
     get_all_query_options = QueryParameterOptions()
 
     @classmethod
     def get(
-        cls, company, id, *, _only=None, include_public=False, **kwargs
+        cls: Union["GetMixin", Document],
+        company,
+        id,
+        *,
+        _only=None,
+        include_public=False,
+        **kwargs,
     ) -> "GetMixin":
         q = cls.objects(
             cls._prepare_perm_query(company, allow_public=include_public)
@@ -162,17 +207,7 @@ class GetMixin(PropsMixin):
             for field in tuple(opts.list_fields or ()):
                 data = parameters.pop(field, None)
                 if data:
-                    if not isinstance(data, (list, tuple)):
-                        raise MakeGetAllQueryError("expected list", field)
-                    exclude = [t for t in data if t.startswith("-")]
-                    include = list(set(data).difference(exclude))
-                    mongoengine_field = field.replace(".", "__")
-                    if include:
-                        dict_query[f"{mongoengine_field}__in"] = include
-                    if exclude:
-                        dict_query[f"{mongoengine_field}__nin"] = [
-                            t[1:] for t in exclude
-                        ]
+                    query &= cls.get_list_field_query(field, data)
 
             for field in opts.fields or []:
                 data = parameters.pop(field, None)
@@ -216,6 +251,47 @@ class GetMixin(PropsMixin):
 
         return query & RegexQ(**dict_query)
 
+    @classmethod
+    def get_list_field_query(cls, field: str, data: Sequence[Optional[str]]) -> Q:
+        """
+        Get a proper mongoengine Q object that represents an "or" query for the provided values
+        with respect to the given list field, with support for "none of empty" in case a None value
+        is included.
+
+        - Exclusion can be specified by a leading "-" for each value (API versions <2.8)
+            or by a preceding "__$not" value (operator)
+        """
+        if not isinstance(data, (list, tuple)):
+            raise MakeGetAllQueryError("expected list", field)
+
+        # TODO: backwards compatibility only for older API versions
+        helper = cls.ListFieldBucketHelper(legacy=True)
+        actions = bucketize(
+            data, key=helper.key, value_transform=helper.value_transform
+        )
+
+        allow_empty = None in actions.get("in", {})
+        mongoengine_field = field.replace(".", "__")
+
+        q = RegexQ()
+        for action in filter(None, actions):
+            q &= RegexQ(
+                **{
+                    f"{mongoengine_field}__{action}": list(
+                        set(filter(None, actions[action]))
+                    )
+                }
+            )
+
+        if not allow_empty:
+            return q
+
+        return (
+            q
+            | Q(**{f"{mongoengine_field}__exists": False})
+            | Q(**{mongoengine_field: []})
+        )
+
     @classmethod
     def _prepare_perm_query(cls, company, allow_public=False):
         if allow_public:
@@ -270,11 +346,40 @@ class GetMixin(PropsMixin):
             return override_projection
         if not parameters:
             return []
-        return parameters.get("projection") or parameters.get("only_fields", [])
+        return parameters.get(cls._projection_key) or parameters.get("only_fields", [])
 
     @classmethod
-    def set_default_ordering(cls, parameters, value):
-        parameters[cls._ordering_key] = parameters.get(cls._ordering_key) or value
+    def split_projection(
+        cls, projection: Sequence[str]
+    ) -> Tuple[Collection[str], Collection[str]]:
+        """Return include and exclude lists based on passed projection and class definition"""
+        if projection:
+            include, exclude = partition(
+                projection, key=lambda x: x[0] != ProjectionHelper.exclusion_prefix,
+            )
+        else:
+            include, exclude = [], []
+        exclude = {x.lstrip(ProjectionHelper.exclusion_prefix) for x in exclude}
+        return include, set(cls.get_exclude_fields()).union(exclude).difference(include)
+
+    @classmethod
+    def set_projection(cls, parameters: dict, value: Sequence[str]) -> Sequence[str]:
+        parameters.pop("only_fields", None)
+        parameters[cls._projection_key] = value
+        return value
+
+    @classmethod
+    def get_ordering(cls, parameters: dict) -> Optional[Sequence[str]]:
+        return parameters.get(cls._ordering_key)
+
+    @classmethod
+    def set_ordering(cls, parameters: dict, value: Sequence[str]) -> Sequence[str]:
+        parameters[cls._ordering_key] = value
+        return value
+
+    @classmethod
+    def set_default_ordering(cls, parameters: dict, value: Sequence[str]) -> None:
+        cls.set_ordering(parameters, cls.get_ordering(parameters) or value)
 
     @classmethod
     def get_many_with_join(
@@ -394,7 +499,27 @@ class GetMixin(PropsMixin):
         )
 
     @classmethod
-    def _get_many_no_company(cls, query, parameters=None, override_projection=None):
+    def get_many_public(
+        cls, query: Q = None, projection: Collection[str] = None,
+    ):
+        """
+        Fetch all public documents matching a provided query.
+        :param query: Optional query object (mongoengine.Q).
+        :param projection: A list of projection fields.
+        :return: A list of documents matching the query.
+        """
+        q = get_company_or_none_constraint()
+        _query = (q & query) if query else q
+
+        return cls._get_many_no_company(query=_query, override_projection=projection)
+
+    @classmethod
+    def _get_many_no_company(
+        cls: Union["GetMixin", Document],
+        query: Q,
+        parameters=None,
+        override_projection=None,
+    ):
         """
         Fetch all documents matching a provided query.
         This is a company-less version for internal uses. We assume the caller has either added any necessary
@@ -414,7 +539,9 @@ class GetMixin(PropsMixin):
         search_text = parameters.get(cls._search_text_key)
         order_by = cls.validate_order_by(parameters=parameters, search_text=search_text)
         page, page_size = cls.validate_paging(parameters=parameters)
-        only = cls.get_projection(parameters, override_projection)
+        include, exclude = cls.split_projection(
+            cls.get_projection(parameters, override_projection)
+        )
 
         qs = cls.objects(query)
         if search_text:
@@ -422,13 +549,14 @@ class GetMixin(PropsMixin):
         if order_by:
             # add ordering
             qs = qs.order_by(*order_by)
-        if only:
+
+        if include:
             # add projection
-            qs = qs.only(*only)
-        else:
-            exclude = set(cls.get_exclude_fields()).difference(only)
-            if exclude:
-                qs = qs.exclude(*exclude)
+            qs = qs.only(*include)
+
+        if exclude:
+            qs = qs.exclude(*exclude)
+
         if page is not None and page_size:
             # add paging
             qs = qs.skip(page * page_size).limit(page_size)
@@ -445,6 +573,8 @@ class GetMixin(PropsMixin):
         """
         Fetch all documents matching a provided query. For the first order by field
         the None values are sorted in the end regardless of the sorting order.
+        If the first order field is a user defined parameter (either from execution.parameters,
+        or from last_metrics) then the collation is set that sorts strings in numeric order where possible.
         This is a company-less version for internal uses. We assume the caller has either added any necessary
         constraints to the query or that no constraints are required.
 
@@ -462,7 +592,9 @@ class GetMixin(PropsMixin):
         search_text = parameters.get(cls._search_text_key)
         order_by = cls.validate_order_by(parameters=parameters, search_text=search_text)
         page, page_size = cls.validate_paging(parameters=parameters)
-        only = cls.get_projection(parameters, override_projection)
+        include, exclude = cls.split_projection(
+            cls.get_projection(parameters, override_projection)
+        )
 
         query_sets = [cls.objects(query)]
         if order_by:
@@ -485,20 +617,29 @@ class GetMixin(PropsMixin):
                 query_sets = [cls.objects(non_empty), cls.objects(empty)]
 
             query_sets = [qs.order_by(*order_by) for qs in query_sets]
+            if order_field:
+                collation_override = first(
+                    v
+                    for k, v in cls._field_collation_overrides.items()
+                    if order_field.startswith(k)
+                )
+                if collation_override:
+                    query_sets = [
+                        qs.collation(collation=collation_override) for qs in query_sets
+                    ]
 
         if search_text:
             query_sets = [qs.search_text(search_text) for qs in query_sets]
 
-        if only:
+        if include:
             # add projection
-            query_sets = [qs.only(*only) for qs in query_sets]
-        else:
-            exclude = set(cls.get_exclude_fields())
-            if exclude:
-                query_sets = [qs.exclude(*exclude) for qs in query_sets]
+            query_sets = [qs.only(*include) for qs in query_sets]
+
+        if exclude:
+            query_sets = [qs.exclude(*exclude) for qs in query_sets]
 
         if page is None or not page_size:
-            return [obj.to_proper_dict(only=only) for qs in query_sets for obj in qs]
+            return [obj.to_proper_dict(only=include) for qs in query_sets for obj in qs]
 
         # add paging
         ret = []
@@ -509,7 +650,8 @@ class GetMixin(PropsMixin):
                 start -= qs_size
                 continue
             ret.extend(
-                obj.to_proper_dict(only=only) for obj in qs.skip(start).limit(page_size)
+                obj.to_proper_dict(only=include)
+                for obj in qs.skip(start).limit(page_size)
             )
             if len(ret) >= page_size:
                 break
@@ -578,7 +720,13 @@ class UpdateMixin(object):
         return update_dict
 
     @classmethod
-    def safe_update(cls, company_id, id, partial_update_dict, injected_update=None):
+    def safe_update(
+        cls: Union["UpdateMixin", Document],
+        company_id,
+        id,
+        partial_update_dict,
+        injected_update=None,
+    ):
         update_dict = cls.get_safe_update_dict(partial_update_dict)
         if not update_dict:
             return 0, {}
@@ -595,7 +743,10 @@ class DbModelMixin(GetMixin, ProperDictMixin, UpdateMixin):
 
     @classmethod
     def aggregate(
-        cls: Document, *pipeline: dict, allow_disk_use=None, **kwargs
+        cls: Union["DbModelMixin", Document],
+        pipeline: Sequence[dict],
+        allow_disk_use=None,
+        **kwargs,
     ) -> CommandCursor:
         """
         Aggregate objects of this document class according to the provided pipeline.
@@ -610,7 +761,32 @@ class DbModelMixin(GetMixin, ProperDictMixin, UpdateMixin):
             if allow_disk_use is not None
             else config.get("apiserver.mongo.aggregate.allow_disk_use", True)
         )
-        return cls.objects.aggregate(*pipeline, **kwargs)
+        return cls.objects.aggregate(pipeline, **kwargs)
+
+    @classmethod
+    def set_public(
+        cls: Type[Document],
+        company_id: str,
+        ids: Sequence[str],
+        invalid_cls: Type[BaseError],
+        enabled: bool = True,
+    ):
+        if enabled:
+            items = list(cls.objects(id__in=ids, company=company_id).only("id"))
+            update = dict(set__company_origin=company_id, unset__company=1)
+        else:
+            items = list(
+                cls.objects(
+                    id__in=ids, company__in=(None, ""), company_origin=company_id
+                ).only("id")
+            )
+            update = dict(set__company=company_id, unset__company_origin=1)
+
+        if len(items) < len(ids):
+            missing = tuple(set(ids).difference(i.id for i in items))
+            raise invalid_cls(ids=missing)
+
+        return {"updated": cls.objects(id__in=ids).update(**update)}
 
 
 def validate_id(cls, company, **kwargs):
@@ -632,5 +808,5 @@ def validate_id(cls, company, **kwargs):
         id_to_name.setdefault(obj_id, []).append(name)
     raise errors.bad_request.ValidationError(
         "Invalid {} ids".format(cls.__name__.lower()),
-        **{name: obj_id for obj_id in missing for name in id_to_name[obj_id]}
+        **{name: obj_id for obj_id in missing for name in id_to_name[obj_id]},
     )

server/database/model/company.py

@@ -1,23 +1,36 @@
-from mongoengine import Document, EmbeddedDocument, EmbeddedDocumentField, StringField, Q
+from mongoengine import (
+    Document,
+    EmbeddedDocument,
+    EmbeddedDocumentField,
+    StringField,
+    Q,
+    BooleanField,
+    DateTimeField,
+)
 
 from database import Database, strict
 from database.fields import StrippedStringField
 from database.model import DbModelMixin
 
 
+class ReportStatsOption(EmbeddedDocument):
+    enabled = BooleanField(default=False)  # opt-in for statistics reporting
+    enabled_version = StringField()  # server version when enabled
+    enabled_time = DateTimeField()  # time when enabled
+    enabled_user = StringField()  # ID of user who enabled
+
+
 class CompanyDefaults(EmbeddedDocument):
     cluster = StringField()
+    stats_option = EmbeddedDocumentField(ReportStatsOption, default=ReportStatsOption)
 
 
 class Company(DbModelMixin, Document):
-    meta = {
-        'db_alias': Database.backend,
-        'strict': strict,
-    }
+    meta = {"db_alias": Database.backend, "strict": strict}
 
     id = StringField(primary_key=True)
     name = StrippedStringField(unique=True, min_length=3)
-    defaults = EmbeddedDocumentField(CompanyDefaults)
+    defaults = EmbeddedDocumentField(CompanyDefaults, default=CompanyDefaults)
 
     @classmethod
     def _prepare_perm_query(cls, company, allow_public=False):

server/database/model/model.py

@@ -1,8 +1,9 @@
-from mongoengine import Document, StringField, DateTimeField, ListField, BooleanField
+from mongoengine import Document, StringField, DateTimeField, BooleanField
 
 from database import Database, strict
-from database.fields import StrippedStringField, SafeDictField
+from database.fields import StrippedStringField, SafeDictField, SafeSortedListField
 from database.model import DbModelMixin
+from database.model.base import GetMixin
 from database.model.model_labels import ModelLabels
 from database.model.company import Company
 from database.model.project import Project
@@ -12,46 +13,63 @@ from database.model.user import User
 
 class Model(DbModelMixin, Document):
     meta = {
-        'db_alias': Database.backend,
-        'strict': strict,
-        'indexes': [
+        "db_alias": Database.backend,
+        "strict": strict,
+        "indexes": [
+            "parent",
+            "project",
+            "task",
+            ("company", "framework"),
+            ("company", "name"),
+            ("company", "user"),
             {
-                'name': '%s.model.main_text_index' % Database.backend,
-                'fields': [
-                    '$name',
-                    '$id',
-                    '$comment',
-                    '$parent',
-                    '$task',
-                    '$project',
-                ],
-                'default_language': 'english',
-                'weights': {
-                    'name': 10,
-                    'id': 10,
-                    'comment': 10,
-                    'parent': 5,
-                    'task': 3,
-                    'project': 3,
-                }
-            }
+                "name": "%s.model.main_text_index" % Database.backend,
+                "fields": ["$name", "$id", "$comment", "$parent", "$task", "$project"],
+                "default_language": "english",
+                "weights": {
+                    "name": 10,
+                    "id": 10,
+                    "comment": 10,
+                    "parent": 5,
+                    "task": 3,
+                    "project": 3,
+                },
+            },
         ],
     }
+    get_all_query_options = GetMixin.QueryParameterOptions(
+        pattern_fields=("name", "comment"),
+        fields=("ready",),
+        list_fields=(
+            "tags",
+            "system_tags",
+            "framework",
+            "uri",
+            "id",
+            "user",
+            "project",
+            "task",
+            "parent",
+        ),
+    )
 
     id = StringField(primary_key=True)
     name = StrippedStringField(user_set_allowed=True, min_length=3)
-    parent = StringField(reference_field='Model', required=False)
+    parent = StringField(reference_field="Model", required=False)
     user = StringField(required=True, reference_field=User)
     company = StringField(required=True, reference_field=Company)
     project = StringField(reference_field=Project, user_set_allowed=True)
     created = DateTimeField(required=True, user_set_allowed=True)
     task = StringField(reference_field=Task)
     comment = StringField(user_set_allowed=True)
-    tags = ListField(StringField(required=True), user_set_allowed=True)
-    system_tags = ListField(StringField(required=True), user_set_allowed=True)
-    uri = StrippedStringField(default='', user_set_allowed=True)
+    tags = SafeSortedListField(StringField(required=True), user_set_allowed=True)
+    system_tags = SafeSortedListField(StringField(required=True), user_set_allowed=True)
+    uri = StrippedStringField(default="", user_set_allowed=True)
     framework = StringField()
     design = SafeDictField()
     labels = ModelLabels()
     ready = BooleanField(required=True)
-    ui_cache = SafeDictField(default=dict, user_set_allowed=True, exclude_by_default=True)
+    ui_cache = SafeDictField(
+        default=dict, user_set_allowed=True, exclude_by_default=True
+    )
+    company_origin = StringField(exclude_by_default=True)

server/database/model/model_labels.py

@@ -1,11 +1,14 @@
-from mongoengine import MapField, IntField
+from database.fields import NoneType, UnionField, SafeMapField
 
 
-class ModelLabels(MapField):
+class ModelLabels(SafeMapField):
     def __init__(self, *args, **kwargs):
-        super(ModelLabels, self).__init__(field=IntField(), *args, **kwargs)
+        super(ModelLabels, self).__init__(
+            field=UnionField(types=(int, NoneType)), *args, **kwargs
+        )
 
     def validate(self, value):
         super(ModelLabels, self).validate(value)
-        if value and (len(set(value.values())) < len(value)):
+        non_empty_values = list(filter(None, value.values()))
+        if non_empty_values and len(set(non_empty_values)) < len(non_empty_values):
             self.error("Same label id appears more than once in model labels")

server/database/model/project.py

@@ -1,7 +1,7 @@
-from mongoengine import StringField, DateTimeField, ListField
+from mongoengine import StringField, DateTimeField, IntField
 
 from database import Database, strict
-from database.fields import StrippedStringField
+from database.fields import StrippedStringField, SafeSortedListField
 from database.model import AttributedDocument
 from database.model.base import GetMixin
 
@@ -17,12 +17,13 @@ class Project(AttributedDocument):
         "db_alias": Database.backend,
         "strict": strict,
         "indexes": [
+            ("company", "name"),
             {
                 "name": "%s.project.main_text_index" % Database.backend,
                 "fields": ["$name", "$id", "$description"],
                 "default_language": "english",
                 "weights": {"name": 10, "id": 10, "description": 10},
-            }
+            },
         ],
     }
 
@@ -35,7 +36,11 @@ class Project(AttributedDocument):
     )
     description = StringField(required=True)
     created = DateTimeField(required=True)
-    tags = ListField(StringField(required=True))
-    system_tags = ListField(StringField(required=True))
+    tags = SafeSortedListField(StringField(required=True))
+    system_tags = SafeSortedListField(StringField(required=True))
     default_output_destination = StrippedStringField()
     last_update = DateTimeField()
+    featured = IntField(default=9999)
+    logo_url = StringField()
+    logo_blob = StringField(exclude_by_default=True)
+    company_origin = StringField(exclude_by_default=True)

server/database/model/queue.py

@@ -4,11 +4,10 @@ from mongoengine import (
     StringField,
     DateTimeField,
     EmbeddedDocumentListField,
-    ListField,
 )
 
 from database import Database, strict
-from database.fields import StrippedStringField
+from database.fields import StrippedStringField, SafeSortedListField
 from database.model import DbModelMixin
 from database.model.base import ProperDictMixin, GetMixin
 from database.model.company import Company
@@ -41,7 +40,7 @@ class Queue(DbModelMixin, Document):
     )
     company = StringField(required=True, reference_field=Company)
     created = DateTimeField(required=True)
-    tags = ListField(StringField(required=True), default=list, user_set_allowed=True)
-    system_tags = ListField(StringField(required=True), user_set_allowed=True)
+    tags = SafeSortedListField(StringField(required=True), default=list, user_set_allowed=True)
+    system_tags = SafeSortedListField(StringField(required=True), user_set_allowed=True)
     entries = EmbeddedDocumentListField(Entry, default=list)
     last_update = DateTimeField()

server/database/model/settings.py

@@ -0,0 +1,57 @@
+from typing import Any, Optional, Sequence, Tuple
+
+from mongoengine import Document, StringField, DynamicField, Q
+from mongoengine.errors import NotUniqueError
+
+from database import Database, strict
+from database.model import DbModelMixin
+
+
+class SettingKeys:
+    server__uuid = "server.uuid"
+
+
+class Settings(DbModelMixin, Document):
+    meta = {
+        "db_alias": Database.backend,
+        "strict": strict,
+    }
+
+    key = StringField(primary_key=True)
+    value = DynamicField()
+
+    @classmethod
+    def get_by_key(cls, key: str, default: Optional[Any] = None, sep: str = ".") -> Any:
+        key = key.strip(sep)
+        res = Settings.objects(key=key).first()
+        if not res:
+            return default
+        return res.value
+
+    @classmethod
+    def get_by_prefix(
+        cls, key_prefix: str, default: Optional[Any] = None, sep: str = "."
+    ) -> Sequence[Tuple[str, Any]]:
+        key_prefix = key_prefix.strip(sep)
+        query = Q(key=key_prefix) | Q(key__startswith=key_prefix + sep)
+        res = Settings.objects(query)
+        if not res:
+            return default
+        return [(x.key, x.value) for x in res]
+
+    @classmethod
+    def set_or_add_value(cls, key: str, value: Any, sep: str = ".") -> bool:
+        """ Sets a new value or adds a new key/value setting (if key does not exist) """
+        key = key.strip(sep)
+        res = Settings.objects(key=key).update(key=key, value=value, upsert=True)
+        return bool(res)
+
+    @classmethod
+    def add_value(cls, key: str, value: Any, sep: str = ".") -> bool:
+        """ Adds a new key/value settings. Fails if key already exists. """
+        key = key.strip(sep)
+        try:
+            res = cls(key=key, value=value).save(force_insert=True)
+            return bool(res)
+        except NotUniqueError:
+            return False

server/database/model/task/metrics.py

@@ -1,10 +1,18 @@
-from mongoengine import EmbeddedDocument, StringField, DynamicField
+from mongoengine import (
+    EmbeddedDocument,
+    StringField,
+    DynamicField,
+    LongField,
+    EmbeddedDocumentField,
+)
+
+from database.fields import SafeMapField
 
 
 class MetricEvent(EmbeddedDocument):
     meta = {
         # For backwards compatibility reasons
-        'strict': False,
+        "strict": False,
     }
 
     metric = StringField(required=True)
@@ -12,3 +20,20 @@ class MetricEvent(EmbeddedDocument):
     value = DynamicField(required=True)
     min_value = DynamicField()  # for backwards compatibility reasons
     max_value = DynamicField()  # for backwards compatibility reasons
+
+
+class EventStats(EmbeddedDocument):
+    meta = {
+        # For backwards compatibility reasons
+        "strict": False,
+    }
+    last_update = LongField()
+
+
+class MetricEventStats(EmbeddedDocument):
+    meta = {
+        # For backwards compatibility reasons
+        "strict": False,
+    }
+    metric = StringField(required=True)
+    event_stats_by_type = SafeMapField(field=EmbeddedDocumentField(EventStats))

server/database/model/task/task.py

@@ -18,10 +18,11 @@ from database.fields import (
     SafeSortedListField,
 )
 from database.model import AttributedDocument
+from database.model.base import ProperDictMixin, GetMixin
 from database.model.model_labels import ModelLabels
 from database.model.project import Project
 from database.utils import get_options
-from .metrics import MetricEvent
+from .metrics import MetricEvent, MetricEventStats
 from .output import Output
 
 DEFAULT_LAST_ITERATION = 0
@@ -48,13 +49,13 @@ class TaskSystemTags(object):
     development = "development"
 
 
-class Script(EmbeddedDocument):
+class Script(EmbeddedDocument, ProperDictMixin):
     binary = StringField(default="python")
-    repository = StringField(required=True)
+    repository = StringField(default="")
     tag = StringField()
     branch = StringField()
     version_num = StringField()
-    entry_point = StringField(required=True)
+    entry_point = StringField(default="")
     working_dir = StringField()
     requirements = SafeDictField()
     diff = StringField()
@@ -66,10 +67,15 @@ class ArtifactTypeData(EmbeddedDocument):
     data_hash = StringField()
 
 
+class ArtifactModes:
+    input = "input"
+    output = "output"
+
+
 class Artifact(EmbeddedDocument):
     key = StringField(required=True)
     type = StringField(required=True)
-    mode = StringField(choices=("input", "output"), default="output")
+    mode = StringField(choices=get_options(ArtifactModes), default=ArtifactModes.output)
     uri = StringField()
     hash = StringField()
     content_size = LongField()
@@ -78,7 +84,23 @@ class Artifact(EmbeddedDocument):
     display_data = SafeSortedListField(ListField(UnionField((int, float, str))))
 
 
-class Execution(EmbeddedDocument):
+class ParamsItem(EmbeddedDocument, ProperDictMixin):
+    section = StringField(required=True)
+    name = StringField(required=True)
+    value = StringField(required=True)
+    type = StringField()
+    description = StringField()
+
+
+class ConfigurationItem(EmbeddedDocument, ProperDictMixin):
+    name = StringField(required=True)
+    value = StringField(required=True)
+    type = StringField()
+    description = StringField()
+
+
+class Execution(EmbeddedDocument, ProperDictMixin):
+    meta = {"strict": strict}
     test_split = IntField(default=0)
     parameters = SafeDictField(default=dict)
     model = StringField(reference_field="Model")
@@ -94,9 +116,29 @@ class Execution(EmbeddedDocument):
 class TaskType(object):
     training = "training"
     testing = "testing"
+    inference = "inference"
+    data_processing = "data_processing"
+    application = "application"
+    monitor = "monitor"
+    controller = "controller"
+    optimizer = "optimizer"
+    service = "service"
+    qc = "qc"
+    custom = "custom"
+
+
+external_task_types = set(get_options(TaskType))
 
 
 class Task(AttributedDocument):
+    _numeric_locale = {"locale": "en_US", "numericOrdering": True}
+    _field_collation_overrides = {
+        "execution.parameters.": _numeric_locale,
+        "last_metrics.": _numeric_locale,
+        "hyperparams.": _numeric_locale,
+        "configuration.": _numeric_locale,
+    }
+
     meta = {
         "db_alias": Database.backend,
         "strict": strict,
@@ -104,6 +146,13 @@ class Task(AttributedDocument):
             "created",
             "started",
             "completed",
+            "parent",
+            "project",
+            ("company", "name"),
+            ("company", "user"),
+            ("company", "type", "system_tags", "status"),
+            ("company", "project", "type", "system_tags", "status"),
+            ("status", "last_update"),  # for maintenance tasks
             {
                 "name": "%s.task.main_text_index" % Database.backend,
                 "fields": [
@@ -128,6 +177,12 @@ class Task(AttributedDocument):
             },
         ],
     }
+    get_all_query_options = GetMixin.QueryParameterOptions(
+        list_fields=("id", "user", "tags", "system_tags", "type", "status", "project"),
+        datetime_fields=("status_changed",),
+        pattern_fields=("name", "comment"),
+        fields=("parent",),
+    )
 
     id = StringField(primary_key=True)
     name = StrippedStringField(
@@ -146,13 +201,19 @@ class Task(AttributedDocument):
     published = DateTimeField()
     parent = StringField()
     project = StringField(reference_field=Project, user_set_allowed=True)
-    output = EmbeddedDocumentField(Output, default=Output)
+    output: Output = EmbeddedDocumentField(Output, default=Output)
     execution: Execution = EmbeddedDocumentField(Execution, default=Execution)
-    tags = ListField(StringField(required=True), user_set_allowed=True)
-    system_tags = ListField(StringField(required=True), user_set_allowed=True)
-    script = EmbeddedDocumentField(Script)
+    tags = SafeSortedListField(StringField(required=True), user_set_allowed=True)
+    system_tags = SafeSortedListField(StringField(required=True), user_set_allowed=True)
+    script: Script = EmbeddedDocumentField(Script, default=Script)
     last_worker = StringField()
     last_worker_report = DateTimeField()
     last_update = DateTimeField()
     last_iteration = IntField(default=DEFAULT_LAST_ITERATION)
     last_metrics = SafeMapField(field=SafeMapField(EmbeddedDocumentField(MetricEvent)))
+    metric_stats = SafeMapField(field=EmbeddedDocumentField(MetricEventStats))
+    company_origin = StringField(exclude_by_default=True)
+    duration = IntField()  # task duration in seconds
+    hyperparams = SafeMapField(field=SafeMapField(EmbeddedDocumentField(ParamsItem)))
+    configuration = SafeMapField(field=EmbeddedDocumentField(ConfigurationItem))
+    runtime = SafeDictField(default=dict)

server/database/model/user.py

@@ -1,16 +1,17 @@
-from mongoengine import Document, StringField
+from mongoengine import Document, StringField, DynamicField
 
 from database import Database, strict
-from database.fields import SafeDictField
 from database.model import DbModelMixin
+from database.model.base import GetMixin
 from database.model.company import Company
 
 
 class User(DbModelMixin, Document):
     meta = {
-        'db_alias': Database.backend,
-        'strict': strict,
+        "db_alias": Database.backend,
+        "strict": strict,
     }
+    get_all_query_options = GetMixin.QueryParameterOptions(list_fields=("id",))
 
     id = StringField(primary_key=True)
     company = StringField(required=True, reference_field=Company)
@@ -18,4 +19,4 @@ class User(DbModelMixin, Document):
     family_name = StringField(user_set_allowed=True)
     given_name = StringField(user_set_allowed=True)
     avatar = StringField()
-    preferences = SafeDictField(default=dict, exclude_by_default=True)
+    preferences = DynamicField(default="", exclude_by_default=True)

server/database/projection.py

@@ -45,7 +45,7 @@ def project_dict(data, projection, separator=SEP):
                         )
 
                     dst[path_part] = [
-                        copy_path(path_parts[depth + 1:], s, d)
+                        copy_path(path_parts[depth + 1 :], s, d)
                         for s, d in zip(src_part, dst[path_part])
                     ]
 
@@ -96,6 +96,7 @@ class _ProxyManager:
 
 class ProjectionHelper(object):
     pool = ThreadPoolExecutor()
+    exclusion_prefix = "-"
 
     @property
     def doc_projection(self):
@@ -128,20 +129,28 @@ class ProjectionHelper(object):
             []
         )  # Projection information for reference fields (used in join queries)
         for field in projection:
+            field_ = field.lstrip(self.exclusion_prefix)
             for ref_field, ref_field_cls in doc_cls.get_reference_fields().items():
-                if not field.startswith(ref_field):
+                if not field_.startswith(ref_field):
                     # Doesn't start with a reference field
                     continue
-                if field == ref_field:
+                if field_ == ref_field:
                     # Field is exactly a reference field. In this case we won't perform any inner projection (for that,
                     # use '<reference field name>.*')
                     continue
-                subfield = field[len(ref_field):]
+                subfield = field_[len(ref_field) :]
                 if not subfield.startswith(SEP):
                     # Starts with something that looks like a reference field, but isn't
                     continue
 
-                ref_projection_info.append((ref_field, ref_field_cls, subfield[1:]))
+                ref_projection_info.append(
+                    (
+                        ref_field,
+                        ref_field_cls,
+                        ("" if field_[0] == field[0] else self.exclusion_prefix)
+                        + subfield[1:],
+                    )
+                )
                 break
             else:
                 # Not a reference field, just add to the top-level projection
@@ -149,7 +158,7 @@ class ProjectionHelper(object):
                 orig_field = field
                 if field.endswith(".*"):
                     field = field[:-2]
-                if not field:
+                if not field.lstrip(self.exclusion_prefix):
                     raise errors.bad_request.InvalidFields(
                         field=orig_field, object=doc_cls.__name__
                     )
@@ -199,7 +208,7 @@ class ProjectionHelper(object):
         # Make sure this doesn't contain any reference field we'll join anyway
         # (i.e. in case only_fields=[project, project.name])
         doc_projection = normalize_cls_projection(
-            doc_cls, doc_projection.difference(ref_projection).union({"id"})
+            doc_cls, doc_projection.difference(ref_projection)
         )
 
         # Make sure that in case one or more field is a subfield of another field, we only use the the top-level field.
@@ -218,7 +227,10 @@ class ProjectionHelper(object):
 
         # Make sure we didn't get any invalid projection fields for this class
         invalid_fields = [
-            f for f in doc_projection if f.split(SEP)[0] not in doc_cls.get_fields()
+            f
+            for f in doc_projection
+            if f.partition(SEP)[0].lstrip(self.exclusion_prefix)
+            not in doc_cls.get_fields()
         ]
         if invalid_fields:
             raise errors.bad_request.InvalidFields(
@@ -234,6 +246,13 @@ class ProjectionHelper(object):
                 doc_projection.add(field)
             doc_projection = list(doc_projection)
 
+        # If there are include fields (not only exclude) then add an id field
+        if (
+            not all(p.startswith(self.exclusion_prefix) for p in doc_projection)
+            and "id" not in doc_projection
+        ):
+            doc_projection.append("id")
+
         self._doc_projection = doc_projection
         self._ref_projection = ref_projection
 
@@ -314,6 +333,7 @@ class ProjectionHelper(object):
             ]
 
             if items:
+
                 def do_projection(item):
                     ref_field_name, data, ids = item
 

server/database/query.py

@@ -1,8 +1,14 @@
 import copy
 import re
+from typing import Union
 
 from mongoengine import Q
-from mongoengine.queryset.visitor import QueryCompilerVisitor, SimplificationVisitor, QCombination
+from mongoengine.queryset.visitor import (
+    QueryCompilerVisitor,
+    SimplificationVisitor,
+    QCombination,
+    QNode,
+)
 
 
 class RegexWrapper(object):
@@ -17,17 +23,16 @@ class RegexWrapper(object):
 
 
 class RegexMixin(object):
-
-    def to_query(self, document):
+    def to_query(self: Union["RegexMixin", QNode], document):
         query = self.accept(SimplificationVisitor())
         query = query.accept(RegexQueryCompilerVisitor(document))
         return query
 
-    def _combine(self, other, operation):
+    def _combine(self: Union["RegexMixin", QNode], other, operation):
         """Combine this node with another node into a QCombination
         object.
         """
-        if getattr(other, 'empty', True):
+        if getattr(other, "empty", True):
             return self
 
         if self.empty:

server/database/utils.py

@@ -95,21 +95,18 @@ def parse_from_call(call_data, fields, cls_fields, discard_none_values=True):
                     res[field] = None
                 continue
             if desc:
-                if callable(desc):
-                    desc(value)
-                else:
-                    if issubclass(desc, (list, tuple, dict)) and not isinstance(
-                        value, desc
-                    ):
-                        raise ParseCallError(
-                            "expecting %s" % desc.__name__, field=field
-                        )
-                    if issubclass(desc, Document) and not desc.objects(id=value).only(
-                        "id"
-                    ):
+                if issubclass(desc, Document):
+                    if not desc.objects(id=value).only("id"):
                         raise ParseCallError(
                             "expecting %s id" % desc.__name__, id=value, field=field
                         )
+                elif callable(desc):
+                    try:
+                        desc(value)
+                    except TypeError:
+                        raise ParseCallError(f"expecting {desc.__name__}", field=field)
+                    except Exception as ex:
+                        raise ParseCallError(str(ex), field=field)
             res[field] = value
         return res
 

server/elastic/apply_mappings.py

@@ -4,53 +4,54 @@ Apply elasticsearch mappings to given hosts.
 """
 import argparse
 import json
-import requests
 from pathlib import Path
+from typing import Optional, Sequence
 
-from requests.adapters import HTTPAdapter
-from requests.packages.urllib3.util.retry import Retry
+from elasticsearch import Elasticsearch
 
-HERE = Path(__file__).parent
+HERE = Path(__file__).resolve().parent
 
 
-def apply_mappings_to_host(host: str):
-    def _send_mapping(f):
+def apply_mappings_to_cluster(
+    hosts: Sequence, key: Optional[str] = None, es_args: dict = None
+):
+    """Hosts maybe a sequence of strings or dicts in the form {"host": <host>, "port": <port>}"""
+
+    def _send_template(f):
         with f.open() as json_data:
             data = json.load(json_data)
-            es_server = host
-            url = f"{es_server}/_template/{f.stem}"
-
-            session = requests.Session()
-            adapter = HTTPAdapter(max_retries=Retry(5, backoff_factor=0.5))
-            session.mount('http://', adapter)
-
-            session.delete(url)
-            r = session.post(
-                url,
-                headers={"Content-Type": "application/json"},
-                data=json.dumps(data),
-            )
-            return {"mapping": f.stem, "result": r.text}
+            template_name = f.stem
+            res = es.indices.put_template(template_name, body=data)
+            return {"mapping": template_name, "result": res}
 
     p = HERE / "mappings"
-    return [
-        _send_mapping(f) for f in p.iterdir() if f.is_file() and f.suffix == ".json"
-    ]
+    if key:
+        files = (p / key).glob("*.json")
+    else:
+        files = p.glob("**/*.json")
+
+    es = Elasticsearch(hosts=hosts, **(es_args or {}))
+    return [_send_template(f) for f in files]
 
 
 def parse_args():
     parser = argparse.ArgumentParser(
         description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter
     )
-    parser.add_argument("hosts", nargs="+")
+    parser.add_argument("--key", help="host key, e.g. events, datasets etc.")
+    parser.add_argument(
+        "--hosts",
+        nargs="+",
+        help="list of es hosts from the same cluster, where each host is http[s]://[user:password@]host:port",
+    )
     return parser.parse_args()
 
 
 def main():
-    for host in parse_args().hosts:
-        print(">>>>> Applying mapping to " + host)
-        res = apply_mappings_to_host(host)
-        print(res)
+    args = parse_args()
+    print(">>>>> Applying mapping to " + str(args.hosts))
+    res = apply_mappings_to_cluster(args.hosts, args.key)
+    print(res)
 
 
 if __name__ == "__main__":

server/elastic/initialize.py

@@ -0,0 +1,113 @@
+import logging
+from time import sleep
+from typing import Type, Optional, Sequence, Any, Union
+
+import urllib3.exceptions
+from elasticsearch import Elasticsearch, exceptions
+
+import es_factory
+from config import config
+from elastic.apply_mappings import apply_mappings_to_cluster
+
+log = config.logger(__file__)
+
+
+class MissingElasticConfiguration(Exception):
+    """
+    Exception when cluster configuration is not found in config files
+    """
+
+    pass
+
+
+class ElasticConnectionError(Exception):
+    """
+    Exception when could not connect to elastic during init
+    """
+
+    pass
+
+
+class ConnectionErrorFilter(logging.Filter):
+    def __init__(
+        self,
+        level: Optional[Union[int, str]] = None,
+        err_type: Optional[Type] = None,
+        args_prefix: Optional[Sequence[Any]] = None,
+    ):
+        super(ConnectionErrorFilter, self).__init__()
+        if level is None:
+            self.level = None
+        else:
+            try:
+                self.level = int(level)
+            except ValueError:
+                self.level = logging.getLevelName(level)
+
+        self.err_type = err_type
+        self.args = args_prefix and tuple(args_prefix)
+        self.last_blocked = None
+
+    def filter(self, record):
+        try:
+            allow = (
+                (self.err_type is None or record.exc_info[0] != self.err_type)
+                and (self.level is None or record.levelno != self.level)
+                and (self.args is None or record.args[: len(self.args)] != self.args)
+            )
+            if not allow:
+                self.last_blocked = record
+            return allow
+        except Exception:
+            return True
+
+
+def check_elastic_empty() -> bool:
+    """
+    Check for elasticsearch connection
+    Use probing settings and not the default es cluster ones
+    so that we can handle correctly the connection rejects due to ES not fully started yet
+    :return:
+    """
+    cluster_conf = es_factory.get_cluster_config("events")
+    max_retries = config.get("apiserver.elastic.probing.max_retries", 4)
+    timeout = config.get("apiserver.elastic.probing.timeout", 30)
+
+    es_logger = logging.getLogger("elasticsearch")
+    log_filter = ConnectionErrorFilter(
+        err_type=urllib3.exceptions.NewConnectionError, args_prefix=("GET",)
+    )
+
+    try:
+        es_logger.addFilter(log_filter)
+        for retry in range(max_retries):
+            try:
+                es = Elasticsearch(hosts=cluster_conf.get("hosts"))
+                return not es.indices.get_template(name="events*")
+            except exceptions.NotFoundError as ex:
+                log.error(ex)
+                return True
+            except exceptions.ConnectionError as ex:
+                if retry >= max_retries - 1:
+                    raise ElasticConnectionError(
+                        f"Error connecting to Elasticsearch: {str(ex)}"
+                    )
+                log.warn(
+                    f"Could not connect to ElasticSearch Service. Retry {retry+1} of {max_retries}. Waiting for {timeout}sec"
+                )
+                sleep(timeout)
+    finally:
+        es_logger.removeFilter(log_filter)
+
+
+def init_es_data():
+    for name in es_factory.get_all_cluster_names():
+        cluster_conf = es_factory.get_cluster_config(name)
+        hosts_config = cluster_conf.get("hosts")
+        if not hosts_config:
+            raise MissingElasticConfiguration(f"for cluster '{name}'")
+
+        log.info(f"Applying mappings to ES host: {hosts_config}")
+        args = cluster_conf.get("args", {})
+        res = apply_mappings_to_cluster(hosts_config, name, es_args=args)
+        log.info(res)

server/elastic/mappings/events.json

@@ -1,27 +0,0 @@
-{
-  "template": "events-*",
-  "settings": {
-    "number_of_shards": 5
-  },
-  "mappings": {
-    "_default_": {
-      "_source": {
-        "enabled": true
-      },
-      "_routing": {
-        "required": true
-      },
-      "properties": {
-        "@timestamp": { "type": "date" },
-        "task":       { "type": "keyword" },
-        "type":       { "type": "keyword" },
-        "worker":     { "type": "keyword" },
-        "timestamp":  { "type": "date" },
-        "iter":       { "type": "long" },
-        "metric":     { "type": "keyword" },
-        "variant":    { "type": "keyword" },
-        "value":      { "type": "float" }
-      }
-    }
-  }
-}

server/elastic/mappings/events/events.json

@@ -0,0 +1,40 @@
+{
+  "index_patterns": "events-*",
+  "settings": {
+    "number_of_shards": 1
+  },
+  "mappings": {
+    "_source": {
+      "enabled": true
+    },
+    "properties": {
+      "@timestamp": {
+        "type": "date"
+      },
+      "task": {
+        "type": "keyword"
+      },
+      "type": {
+        "type": "keyword"
+      },
+      "worker": {
+        "type": "keyword"
+      },
+      "timestamp": {
+        "type": "date"
+      },
+      "iter": {
+        "type": "long"
+      },
+      "metric": {
+        "type": "keyword"
+      },
+      "variant": {
+        "type": "keyword"
+      },
+      "value": {
+        "type": "float"
+      }
+    }
+  }
+}

server/elastic/mappings/events/events_log.json

@@ -0,0 +1,15 @@
+{
+  "index_patterns": "events-log-*",
+  "order": 1,
+  "mappings": {
+    "properties": {
+      "msg": {
+        "type": "text",
+        "index": false
+      },
+      "level": {
+        "type": "keyword"
+      }
+    }
+  }
+}

server/elastic/mappings/events/events_plot.json

@@ -0,0 +1,12 @@
+{
+  "index_patterns": "events-plot-*",
+  "order": 1,
+  "mappings": {
+    "properties": {
+      "plot_str": {
+        "type": "text",
+        "index": false
+      }
+    }
+  }
+}

server/elastic/mappings/events/events_training_debug_image.json

@@ -0,0 +1,14 @@
+{
+  "index_patterns": "events-training_debug_image-*",
+  "order": 1,
+  "mappings": {
+    "properties": {
+      "key": {
+        "type": "keyword"
+      },
+      "url": {
+        "type": "keyword"
+      }
+    }
+  }
+}

server/elastic/mappings/events_log.json

@@ -1,12 +0,0 @@
-{
-  "template": "events-log-*",
-  "order" : 1,
-  "mappings": {
-    "_default_": {
-      "properties": {
-        "msg":    { "type":"text", "index": false },
-        "level":  { "type":"keyword" }
-      }
-    }
-  }
-}

server/elastic/mappings/events_plot.json

@@ -1,11 +0,0 @@
-{
-  "template": "events-plot-*",
-  "order" : 1,
-  "mappings": {
-    "_default_": {
-      "properties": {
-        "plot_str": { "type":"text", "index": false }
-      }
-    }
-  }
-}

server/elastic/mappings/events_training_debug_image.json

@@ -1,12 +0,0 @@
-{
-  "template": "events-training_debug_image-*",
-  "order" : 1,
-  "mappings": {
-    "_default_": {
-      "properties": {
-        "key":      { "type": "keyword" },
-        "url":      { "type": "keyword" }
-      }
-    }
-  }
-}

server/elastic/mappings/queue_metrics.json

@@ -1,27 +0,0 @@
-{
-  "template": "queue_metrics_*",
-  "settings": {
-    "number_of_shards": 1
-  },
-  "mappings": {
-    "metrics": {
-      "_source": {
-        "enabled": true
-      },
-      "properties": {
-            "timestamp":  {
-              "type": "date"
-            },
-            "queue": {
-              "type": "keyword"
-            },
-            "average_waiting_time": {
-              "type": "float"
-            },
-            "queue_length": {
-              "type": "integer"
-            }
-      }
-    }
-  }
-}

server/elastic/mappings/worker_stats.json

@@ -1,23 +0,0 @@
-{
-  "template": "worker_stats_*",
-  "settings": {
-    "number_of_shards": 1
-  },
-  "mappings": {
-    "stat": {
-      "_source": {
-        "enabled": true
-      },
-      "properties": {
-            "timestamp":  { "type": "date"    },
-            "worker":     { "type": "keyword" },
-            "category":   { "type": "keyword" },
-            "metric":     { "type": "keyword" },
-            "variant":    { "type": "keyword" },
-            "value":      { "type": "float"   },
-            "unit":       { "type": "keyword" },
-            "task":       { "type": "keyword" }
-      }
-    }
-  }
-}

server/elastic/mappings/workers/queue_metrics.json

@@ -0,0 +1,25 @@
+{
+  "index_patterns": "queue_metrics_*",
+  "settings": {
+    "number_of_shards": 1
+  },
+  "mappings": {
+    "_source": {
+      "enabled": true
+    },
+    "properties": {
+      "timestamp": {
+        "type": "date"
+      },
+      "queue": {
+        "type": "keyword"
+      },
+      "average_waiting_time": {
+        "type": "float"
+      },
+      "queue_length": {
+        "type": "integer"
+      }
+    }
+  }
+}

server/elastic/mappings/workers/worker_stats.json

@@ -0,0 +1,37 @@
+{
+  "index_patterns": "worker_stats_*",
+  "settings": {
+    "number_of_shards": 1
+  },
+  "mappings": {
+    "_source": {
+      "enabled": true
+    },
+    "properties": {
+      "timestamp": {
+        "type": "date"
+      },
+      "worker": {
+        "type": "keyword"
+      },
+      "category": {
+        "type": "keyword"
+      },
+      "metric": {
+        "type": "keyword"
+      },
+      "variant": {
+        "type": "keyword"
+      },
+      "value": {
+        "type": "float"
+      },
+      "unit": {
+        "type": "keyword"
+      },
+      "task": {
+        "type": "keyword"
+      }
+    }
+  }
+}

server/es_factory.py

@@ -1,20 +1,25 @@
 from datetime import datetime
 from os import getenv
 
+from boltons.iterutils import first
 from elasticsearch import Elasticsearch, Transport
 
 from config import config
 
 log = config.logger(__file__)
 
-OVERRIDE_HOST_ENV_KEY = ("ELASTIC_SERVICE_HOST", "ELASTIC_SERVICE_SERVICE_HOST")
-OVERRIDE_PORT_ENV_KEY = "ELASTIC_SERVICE_PORT"
+OVERRIDE_HOST_ENV_KEY = (
+    "TRAINS_ELASTIC_SERVICE_HOST",
+    "ELASTIC_SERVICE_HOST",
+    "ELASTIC_SERVICE_SERVICE_HOST",
+)
+OVERRIDE_PORT_ENV_KEY = ("TRAINS_ELASTIC_SERVICE_PORT", "ELASTIC_SERVICE_PORT")
 
-OVERRIDE_HOST = next(filter(None, map(getenv, OVERRIDE_HOST_ENV_KEY)), None)
+OVERRIDE_HOST = first(filter(None, map(getenv, OVERRIDE_HOST_ENV_KEY)))
 if OVERRIDE_HOST:
     log.info(f"Using override elastic host {OVERRIDE_HOST}")
 
-OVERRIDE_PORT = getenv(OVERRIDE_PORT_ENV_KEY)
+OVERRIDE_PORT = first(filter(None, map(getenv, OVERRIDE_PORT_ENV_KEY)))
 if OVERRIDE_PORT:
     log.info(f"Using override elastic port {OVERRIDE_PORT}")
 
@@ -25,6 +30,7 @@ class MissingClusterConfiguration(Exception):
     """
     Exception when cluster configuration is not found in config files
     """
+
     pass
 
 
@@ -32,6 +38,7 @@ class InvalidClusterConfiguration(Exception):
     """
     Exception when cluster configuration does not contain required properties
     """
+
     pass
 
 
@@ -46,16 +53,22 @@ def connect(cluster_name):
     """
     if cluster_name not in _instances:
         cluster_config = get_cluster_config(cluster_name)
-        hosts = cluster_config.get('hosts', None)
+        hosts = cluster_config.get("hosts", None)
         if not hosts:
             raise InvalidClusterConfiguration(cluster_name)
 
-        args = cluster_config.get('args', {})
-        _instances[cluster_name] = Elasticsearch(hosts=hosts, transport_class=Transport, **args)
+        args = cluster_config.get("args", {})
+        _instances[cluster_name] = Elasticsearch(
+            hosts=hosts, transport_class=Transport, **args
+        )
 
     return _instances[cluster_name]
 
 
+def get_all_cluster_names():
+    return list(config.get("hosts.elastic"))
+
+
 def get_cluster_config(cluster_name):
     """
     Returns cluster config for the specified cluster path
@@ -63,13 +76,13 @@ def get_cluster_config(cluster_name):
     :return: config section for the cluster
     :raises MissingClusterConfiguration: in case no config section is found for the cluster
     """
-    cluster_key = '.'.join(('hosts.elastic', cluster_name))
+    cluster_key = ".".join(("hosts.elastic", cluster_name))
     cluster_config = config.get(cluster_key, None)
     if not cluster_config:
         raise MissingClusterConfiguration(cluster_name)
 
     def set_host_prop(key, value):
-        for host in cluster_config.get('hosts', []):
+        for host in cluster_config.get("hosts", []):
             host[key] = value
 
     if OVERRIDE_HOST:

server/init_data.py

@@ -1,209 +0,0 @@
-import importlib.util
-from datetime import datetime
-from pathlib import Path
-
-import attr
-from furl import furl
-from mongoengine.connection import get_db
-from semantic_version import Version
-
-import database.utils
-from bll.queue import QueueBLL
-from config import config
-from database import Database
-from database.model.auth import Role
-from database.model.auth import User as AuthUser, Credentials
-from database.model.company import Company
-from database.model.queue import Queue
-from database.model.user import User
-from database.model.version import Version as DatabaseVersion
-from elastic.apply_mappings import apply_mappings_to_host
-from es_factory import get_cluster_config
-from service_repo.auth.fixed_user import FixedUser
-
-log = config.logger(__file__)
-
-migration_dir = (Path(__file__) / "../../migration/mongodb").resolve()
-
-
-class MissingElasticConfiguration(Exception):
-    """
-    Exception when cluster configuration is not found in config files
-    """
-
-    pass
-
-
-def init_es_data():
-    hosts_config = get_cluster_config("events").get("hosts")
-    if not hosts_config:
-        raise MissingElasticConfiguration("for cluster 'events'")
-
-    for conf in hosts_config:
-        host = furl(scheme="http", host=conf["host"], port=conf["port"]).url
-        log.info(f"Applying mappings to host: {host}")
-        res = apply_mappings_to_host(host)
-        log.info(res)
-
-
-def _ensure_company():
-    company_id = config.get("apiserver.default_company")
-    company = Company.objects(id=company_id).only("id").first()
-    if company:
-        return company_id
-
-    company_name = "trains"
-    log.info(f"Creating company: {company_name}")
-    company = Company(id=company_id, name=company_name)
-    company.save()
-    return company_id
-
-
-def _ensure_default_queue(company):
-    """
-    If no queue is present for the company then
-    create a new one and mark it as a default
-    """
-    queue = Queue.objects(company=company).only("id").first()
-    if queue:
-        return
-
-    QueueBLL.create(company, name="default", system_tags=["default"])
-
-
-def _ensure_auth_user(user_data, company_id):
-    ensure_credentials = {"key", "secret"}.issubset(user_data.keys())
-    if ensure_credentials:
-        user = AuthUser.objects(
-            credentials__match=Credentials(
-                key=user_data["key"], secret=user_data["secret"]
-            )
-        ).first()
-        if user:
-            return user.id
-
-    log.info(f"Creating user: {user_data['name']}")
-    user = AuthUser(
-        id=user_data.get("id", f"__{user_data['name']}__"),
-        name=user_data["name"],
-        company=company_id,
-        role=user_data["role"],
-        email=user_data["email"],
-        created=datetime.utcnow(),
-        credentials=[Credentials(key=user_data["key"], secret=user_data["secret"])]
-        if ensure_credentials
-        else None,
-    )
-
-    user.save()
-
-    return user.id
-
-
-def _ensure_user(user: FixedUser, company_id: str):
-    if User.objects(id=user.user_id).first():
-        return
-
-    data = attr.asdict(user)
-    data["id"] = user.user_id
-    data["email"] = f"{user.user_id}@example.com"
-    data["role"] = Role.user
-
-    _ensure_auth_user(
-        user_data=data,
-        company_id=company_id,
-    )
-
-    given_name, _, family_name = user.name.partition(" ")
-
-    User(
-        id=user.user_id,
-        company=company_id,
-        name=user.name,
-        given_name=given_name,
-        family_name=family_name,
-    ).save()
-
-
-def _apply_migrations():
-    if not migration_dir.is_dir():
-        raise ValueError(f"Invalid migration dir {migration_dir}")
-
-    try:
-        previous_versions = sorted(
-            (Version(ver.num) for ver in DatabaseVersion.objects().only("num")),
-            reverse=True,
-        )
-    except ValueError as ex:
-        raise ValueError(f"Invalid database version number encountered: {ex}")
-
-    last_version = previous_versions[0] if previous_versions else Version("0.0.0")
-
-    try:
-        new_scripts = {
-            ver: path
-            for ver, path in (
-                (Version(f.stem), f) for f in migration_dir.glob("*.py")
-            )
-            if ver > last_version
-        }
-    except ValueError as ex:
-        raise ValueError(f"Failed parsing migration version from file: {ex}")
-
-    dbs = {Database.auth: "migrate_auth", Database.backend: "migrate_backend"}
-
-    migration_log = log.getChild("mongodb_migration")
-
-    for script_version in sorted(new_scripts.keys()):
-        script = new_scripts[script_version]
-        spec = importlib.util.spec_from_file_location(script.stem, str(script))
-        module = importlib.util.module_from_spec(spec)
-        spec.loader.exec_module(module)
-
-        for alias, func_name in dbs.items():
-            func = getattr(module, func_name, None)
-            if not func:
-                continue
-            try:
-                migration_log.info(f"Applying {script.stem}/{func_name}()")
-                func(get_db(alias))
-            except Exception:
-                migration_log.exception(f"Failed applying {script}:{func_name}()")
-                raise ValueError("Migration failed, aborting. Please restore backup.")
-
-        DatabaseVersion(
-            id=database.utils.id(),
-            num=script.stem,
-            created=datetime.utcnow(),
-            desc="Applied on server startup",
-        ).save()
-
-
-def init_mongo_data():
-    try:
-        _apply_migrations()
-
-        company_id = _ensure_company()
-        _ensure_default_queue(company_id)
-
-        users = [
-            {"name": "apiserver", "role": Role.system, "email": "apiserver@example.com"},
-            {"name": "webserver", "role": Role.system, "email": "webserver@example.com"},
-            {"name": "tests", "role": Role.user, "email": "tests@example.com"},
-        ]
-
-        for user in users:
-            credentials = config.get(f"secure.credentials.{user['name']}")
-            user["key"] = credentials.user_key
-            user["secret"] = credentials.user_secret
-            _ensure_auth_user(user, company_id)
-
-        if FixedUser.enabled():
-            log.info("Fixed users mode is enabled")
-            for user in FixedUser.from_config():
-                try:
-                    _ensure_user(user, company_id)
-                except Exception as ex:
-                    log.error(f"Failed creating fixed user {user['name']}: {ex}")
-    except Exception as ex:
-        log.exception("Failed initializing mongodb")

server/mongo/initialize/__init__.py

@@ -0,0 +1,89 @@
+from pathlib import Path
+from typing import Sequence, Union
+
+from config import config
+from config.info import get_default_company
+from database.model.auth import Role
+from service_repo.auth.fixed_user import FixedUser
+from .migration import _apply_migrations, check_mongo_empty, get_last_server_version
+from .pre_populate import PrePopulate
+from .user import ensure_fixed_user, _ensure_auth_user, _ensure_backend_user
+from .util import _ensure_company, _ensure_default_queue, _ensure_uuid
+
+log = config.logger(__package__)
+
+
+def _pre_populate(company_id: str, zip_file: str):
+    if not zip_file or not Path(zip_file).is_file():
+        msg = f"Invalid pre-populate zip file: {zip_file}"
+        if config.get("apiserver.pre_populate.fail_on_error", False):
+            log.error(msg)
+            raise ValueError(msg)
+        else:
+            log.warning(msg)
+    else:
+        log.info(f"Pre-populating using {zip_file}")
+
+        PrePopulate.import_from_zip(
+            zip_file,
+            artifacts_path=config.get("apiserver.pre_populate.artifacts_path", None),
+        )
+
+
+def _resolve_zip_files(zip_files: Union[Sequence[str], str]) -> Sequence[str]:
+    if isinstance(zip_files, str):
+        zip_files = [zip_files]
+    for p in map(Path, zip_files):
+        if p.is_file():
+            yield p
+        if p.is_dir():
+            yield from p.glob("*.zip")
+        log.warning(f"Invalid pre-populate entry {str(p)}, skipping")
+
+
+def pre_populate_data():
+    for zip_file in _resolve_zip_files(config.get("apiserver.pre_populate.zip_files")):
+        _pre_populate(company_id=get_default_company(), zip_file=zip_file)
+
+    PrePopulate.update_featured_projects_order()
+
+
+def init_mongo_data():
+    try:
+        _apply_migrations(log)
+
+        _ensure_uuid()
+
+        company_id = _ensure_company(get_default_company(), "trains", log)
+
+        _ensure_default_queue(company_id)
+
+        fixed_mode = FixedUser.enabled()
+
+        for user, credentials in config.get("secure.credentials", {}).items():
+            user_data = {
+                "name": user,
+                "role": credentials.role,
+                "email": f"{user}@example.com",
+                "key": credentials.user_key,
+                "secret": credentials.user_secret,
+            }
+            revoke = fixed_mode and credentials.get("revoke_in_fixed_mode", False)
+            user_id = _ensure_auth_user(user_data, company_id, log=log, revoke=revoke)
+            if credentials.role == Role.user:
+                _ensure_backend_user(user_id, company_id, credentials.display_name)
+
+        if fixed_mode:
+            log.info("Fixed users mode is enabled")
+            FixedUser.validate()
+
+            if FixedUser.guest_enabled():
+                _ensure_company(FixedUser.get_guest_user().company, "guests", log)
+
+            for user in FixedUser.from_config():
+                try:
+                    ensure_fixed_user(user, log=log)
+                except Exception as ex:
+                    log.error(f"Failed creating fixed user {user.name}: {ex}")
+    except Exception as ex:
+        log.exception("Failed initializing mongodb")

server/mongo/initialize/migration.py

@@ -0,0 +1,91 @@
+import importlib.util
+from datetime import datetime
+from logging import Logger
+from pathlib import Path
+
+from mongoengine.connection import get_db
+from semantic_version import Version
+
+import database.utils
+from database import Database
+from database.model.version import Version as DatabaseVersion
+
+migration_dir = Path(__file__).resolve().parent.with_name("migrations")
+
+
+def check_mongo_empty() -> bool:
+    return not all(
+        get_db(alias).collection_names()
+        for alias in database.utils.get_options(Database)
+    )
+
+
+def get_last_server_version() -> Version:
+    try:
+        previous_versions = sorted(
+            (Version(ver.num) for ver in DatabaseVersion.objects().only("num")),
+            reverse=True,
+        )
+    except ValueError as ex:
+        raise ValueError(f"Invalid database version number encountered: {ex}")
+
+    return previous_versions[0] if previous_versions else Version("0.0.0")
+
+
+def _apply_migrations(log: Logger):
+    """
+    Apply migrations as found in the migration dir.
+    Returns a boolean indicating whether the database was empty prior to migration.
+    """
+    log = log.getChild(Path(__file__).stem)
+
+    log.info(f"Started mongodb migrations")
+
+    if not migration_dir.is_dir():
+        raise ValueError(f"Invalid migration dir {migration_dir}")
+
+    empty_dbs = check_mongo_empty()
+    last_version = get_last_server_version()
+
+    try:
+        new_scripts = {
+            ver: path
+            for ver, path in ((Version(f.stem), f) for f in migration_dir.glob("*.py"))
+            if ver > last_version
+        }
+    except ValueError as ex:
+        raise ValueError(f"Failed parsing migration version from file: {ex}")
+
+    dbs = {Database.auth: "migrate_auth", Database.backend: "migrate_backend"}
+
+    for script_version in sorted(new_scripts):
+        script = new_scripts[script_version]
+
+        if empty_dbs:
+            log.info(f"Skipping migration {script.name} (empty databases)")
+        else:
+            spec = importlib.util.spec_from_file_location(script.stem, str(script))
+            module = importlib.util.module_from_spec(spec)
+            spec.loader.exec_module(module)
+
+            for alias, func_name in dbs.items():
+                func = getattr(module, func_name, None)
+                if not func:
+                    continue
+                try:
+                    log.info(f"Applying {script.stem}/{func_name}()")
+                    func(get_db(alias))
+                except Exception:
+                    log.exception(f"Failed applying {script}:{func_name}()")
+                    raise ValueError(
+                        "Migration failed, aborting. Please restore backup."
+                    )
+
+        DatabaseVersion(
+            id=database.utils.id(),
+            num=script.stem,
+            created=datetime.utcnow(),
+            desc="Applied on server startup",
+        ).save()
+
+    log.info("Finished mongodb migrations")

server/mongo/initialize/pre_populate.py

@@ -0,0 +1,728 @@
+import hashlib
+import importlib
+import os
+import re
+from collections import defaultdict
+from datetime import datetime, timezone
+from functools import partial
+from io import BytesIO
+from itertools import chain
+from operator import attrgetter
+from os.path import splitext
+from pathlib import Path
+from typing import (
+    Optional,
+    Any,
+    Type,
+    Set,
+    Dict,
+    Sequence,
+    Tuple,
+    BinaryIO,
+    Union,
+    Mapping,
+)
+from urllib.parse import unquote, urlparse
+from zipfile import ZipFile, ZIP_BZIP2
+
+import dpath
+import mongoengine
+from boltons.iterutils import chunked_iter
+from furl import furl
+from mongoengine import Q
+
+from bll.event import EventBLL
+from bll.task.param_utils import (
+    split_param_name,
+    hyperparams_default_section,
+    hyperparams_legacy_type,
+)
+from config import config
+from config.info import get_default_company
+from database.model import EntityVisibility
+from database.model.model import Model
+from database.model.project import Project
+from database.model.task.task import Task, ArtifactModes, TaskStatus
+from database.utils import get_options
+from tools import safe_get
+from utilities import json
+from .user import _ensure_backend_user
+
+
+class PrePopulate:
+    event_bll = EventBLL()
+    events_file_suffix = "_events"
+    export_tag_prefix = "Exported:"
+    export_tag = f"{export_tag_prefix} %Y-%m-%d %H:%M:%S"
+    metadata_filename = "metadata.json"
+    zip_args = dict(mode="w", compression=ZIP_BZIP2)
+    artifacts_ext = ".artifacts"
+    img_source_regex = re.compile(
+        r"['\"]source['\"]:\s?['\"](https?://(?:localhost:8081|files.*?)/.*?)['\"]",
+        flags=re.IGNORECASE,
+    )
+
+    class JsonLinesWriter:
+        def __init__(self, file: BinaryIO):
+            self.file = file
+            self.empty = True
+
+        def __enter__(self):
+            self._write("[")
+            return self
+
+        def __exit__(self, exc_type, exc_value, exc_traceback):
+            self._write("\n]")
+
+        def _write(self, data: str):
+            self.file.write(data.encode("utf-8"))
+
+        def write(self, line: str):
+            if not self.empty:
+                self._write(",")
+            self._write("\n" + line)
+            self.empty = False
+
+    @staticmethod
+    def _get_last_update_time(entity) -> datetime:
+        return getattr(entity, "last_update", None) or getattr(entity, "created")
+
+    @classmethod
+    def _check_for_update(
+        cls, map_file: Path, entities: dict, metadata_hash: str
+    ) -> Tuple[bool, Sequence[str]]:
+        if not map_file.is_file():
+            return True, []
+
+        files = []
+        try:
+            map_data = json.loads(map_file.read_text())
+            files = map_data.get("files", [])
+            for file in files:
+                if not Path(file).is_file():
+                    return True, files
+
+            new_times = {
+                item.id: cls._get_last_update_time(item).replace(tzinfo=timezone.utc)
+                for item in chain.from_iterable(entities.values())
+            }
+            old_times = map_data.get("entities", {})
+
+            if set(new_times.keys()) != set(old_times.keys()):
+                return True, files
+
+            for id_, new_timestamp in new_times.items():
+                if new_timestamp != old_times[id_]:
+                    return True, files
+
+            if metadata_hash != map_data.get("metadata_hash", ""):
+                return True, files
+
+        except Exception as ex:
+            print("Error reading map file. " + str(ex))
+            return True, files
+
+        return False, files
+
+    @classmethod
+    def _write_update_file(
+        cls,
+        map_file: Path,
+        entities: dict,
+        created_files: Sequence[str],
+        metadata_hash: str,
+    ):
+        map_file.write_text(
+            json.dumps(
+                dict(
+                    files=created_files,
+                    entities={
+                        entity.id: cls._get_last_update_time(entity)
+                        for entity in chain.from_iterable(entities.values())
+                    },
+                    metadata_hash=metadata_hash,
+                )
+            )
+        )
+
+    @staticmethod
+    def _filter_artifacts(artifacts: Sequence[str]) -> Sequence[str]:
+        def is_fileserver_link(a: str) -> bool:
+            a = a.lower()
+            if a.startswith("https://files."):
+                return True
+            if a.startswith("http"):
+                parsed = urlparse(a)
+                if parsed.scheme in {"http", "https"} and parsed.netloc.endswith(
+                    "8081"
+                ):
+                    return True
+            return False
+
+        fileserver_links = [a for a in artifacts if is_fileserver_link(a)]
+        print(
+            f"Found {len(fileserver_links)} files on the fileserver from {len(artifacts)} total"
+        )
+
+        return fileserver_links
+
+    @classmethod
+    def export_to_zip(
+        cls,
+        filename: str,
+        experiments: Sequence[str] = None,
+        projects: Sequence[str] = None,
+        artifacts_path: str = None,
+        task_statuses: Sequence[str] = None,
+        tag_exported_entities: bool = False,
+        metadata: Mapping[str, Any] = None,
+    ) -> Sequence[str]:
+        if task_statuses and not set(task_statuses).issubset(get_options(TaskStatus)):
+            raise ValueError("Invalid task statuses")
+
+        file = Path(filename)
+        entities = cls._resolve_entities(
+            experiments=experiments, projects=projects, task_statuses=task_statuses
+        )
+
+        hash_ = hashlib.md5()
+        if metadata:
+            meta_str = json.dumps(metadata)
+            hash_.update(meta_str.encode())
+            metadata_hash = hash_.hexdigest()
+        else:
+            meta_str, metadata_hash = "", ""
+
+        map_file = file.with_suffix(".map")
+        updated, old_files = cls._check_for_update(
+            map_file, entities=entities, metadata_hash=metadata_hash
+        )
+        if not updated:
+            print(f"There are no updates from the last export")
+            return old_files
+
+        for old in old_files:
+            old_path = Path(old)
+            if old_path.is_file():
+                old_path.unlink()
+
+        with ZipFile(file, **cls.zip_args) as zfile:
+            if metadata:
+                zfile.writestr(cls.metadata_filename, meta_str)
+            artifacts = cls._export(
+                zfile,
+                entities=entities,
+                hash_=hash_,
+                tag_entities=tag_exported_entities,
+            )
+
+        file_with_hash = file.with_name(f"{file.stem}_{hash_.hexdigest()}{file.suffix}")
+        file.replace(file_with_hash)
+        created_files = [str(file_with_hash)]
+
+        artifacts = cls._filter_artifacts(artifacts)
+        if artifacts and artifacts_path and os.path.isdir(artifacts_path):
+            artifacts_file = file_with_hash.with_suffix(cls.artifacts_ext)
+            with ZipFile(artifacts_file, **cls.zip_args) as zfile:
+                cls._export_artifacts(zfile, artifacts, artifacts_path)
+            created_files.append(str(artifacts_file))
+
+        cls._write_update_file(
+            map_file,
+            entities=entities,
+            created_files=created_files,
+            metadata_hash=metadata_hash,
+        )
+
+        return created_files
+
+    @classmethod
+    def import_from_zip(
+        cls,
+        filename: str,
+        artifacts_path: str,
+        company_id: Optional[str] = None,
+        user_id: str = "",
+        user_name: str = "",
+    ):
+        metadata = None
+
+        with ZipFile(filename) as zfile:
+            try:
+                with zfile.open(cls.metadata_filename) as f:
+                    metadata = json.loads(f.read())
+
+                    meta_public = metadata.get("public")
+                    if company_id is None and meta_public is not None:
+                        company_id = "" if meta_public else get_default_company()
+
+                    if not user_id:
+                        meta_user_id = metadata.get("user_id", "")
+                        meta_user_name = metadata.get("user_name", "")
+                        user_id, user_name = meta_user_id, meta_user_name
+            except Exception:
+                pass
+
+            if not user_id:
+                user_id, user_name = "__allegroai__", "Allegro.ai"
+
+            # Make sure we won't end up with an invalid company ID
+            if company_id is None:
+                company_id = ""
+
+            # Always use a public user for pre-populated data
+            user_id = _ensure_backend_user(
+                user_id=user_id, user_name=user_name, company_id="",
+            )
+
+            cls._import(zfile, company_id, user_id, metadata)
+
+        if artifacts_path and os.path.isdir(artifacts_path):
+            artifacts_file = Path(filename).with_suffix(cls.artifacts_ext)
+            if artifacts_file.is_file():
+                print(f"Unzipping artifacts into {artifacts_path}")
+                with ZipFile(artifacts_file) as zfile:
+                    zfile.extractall(artifacts_path)
+
+    @classmethod
+    def upgrade_zip(cls, filename) -> Sequence:
+        hash_ = hashlib.md5()
+        task_file = cls._get_base_filename(Task) + ".json"
+        temp_file = Path("temp.zip")
+        file = Path(filename)
+        with ZipFile(file) as reader, ZipFile(temp_file, **cls.zip_args) as writer:
+            for file_info in reader.filelist:
+                if file_info.orig_filename == task_file:
+                    with reader.open(file_info) as f:
+                        content = cls._upgrade_tasks(f)
+                else:
+                    content = reader.read(file_info)
+                writer.writestr(file_info, content)
+                hash_.update(content)
+
+        base_file_name, _, old_hash = file.stem.rpartition("_")
+        new_hash = hash_.hexdigest()
+        if old_hash == new_hash:
+            print(f"The file {filename} was not updated")
+            temp_file.unlink()
+            return []
+
+        new_file = file.with_name(f"{base_file_name}_{new_hash}{file.suffix}")
+        temp_file.replace(new_file)
+        upadated = [str(new_file)]
+
+        artifacts_file = file.with_suffix(cls.artifacts_ext)
+        if artifacts_file.is_file():
+            new_artifacts = new_file.with_suffix(cls.artifacts_ext)
+            artifacts_file.replace(new_artifacts)
+            upadated.append(str(new_artifacts))
+
+        print(f"File {str(file)} replaced with {str(new_file)}")
+        file.unlink()
+
+        return upadated
+
+    @staticmethod
+    def _upgrade_task_data(task_data: dict):
+        for old_param_field, new_param_field, default_section in (
+            ("execution/parameters", "hyperparams", hyperparams_default_section),
+            ("execution/model_desc", "configuration", None),
+        ):
+            legacy = safe_get(task_data, old_param_field)
+            if not legacy:
+                continue
+            for full_name, value in legacy.items():
+                section, name = split_param_name(full_name, default_section)
+                new_path = list(filter(None, (new_param_field, section, name)))
+                if not safe_get(task_data, new_path):
+                    new_param = dict(
+                        name=name, type=hyperparams_legacy_type, value=str(value)
+                    )
+                    if section is not None:
+                        new_param["section"] = section
+                    dpath.new(task_data, new_path, new_param)
+            dpath.delete(task_data, old_param_field)
+
+    @classmethod
+    def _upgrade_tasks(cls, f: BinaryIO) -> bytes:
+        """
+        Build content array that contains fixed tasks from the passed file
+        For each task the old execution.parameters and model.design are
+        converted to the new structure.
+        The fix is done on Task objects (not the dictionary) so that
+        the fields are serialized back in the same order as they were in the original file
+        """
+        with BytesIO() as temp:
+            with cls.JsonLinesWriter(temp) as w:
+                for line in cls.json_lines(f):
+                    task_data = Task.from_json(line).to_proper_dict()
+                    cls._upgrade_task_data(task_data)
+                    new_task = Task(**task_data)
+                    w.write(new_task.to_json())
+            return temp.getvalue()
+
+    @classmethod
+    def update_featured_projects_order(cls):
+        featured_order = config.get("services.projects.featured_order", [])
+        if not featured_order:
+            return
+
+        def get_index(p: Project):
+            for index, entry in enumerate(featured_order):
+                if (
+                    entry.get("id", None) == p.id
+                    or entry.get("name", None) == p.name
+                    or ("name_regex" in entry and re.match(entry["name_regex"], p.name))
+                ):
+                    return index
+            return 999
+
+        for project in Project.get_many_public(projection=["id", "name"]):
+            featured_index = get_index(project)
+            Project.objects(id=project.id).update(featured=featured_index)
+
+    @staticmethod
+    def _resolve_type(
+        cls: Type[mongoengine.Document], ids: Optional[Sequence[str]]
+    ) -> Sequence[Any]:
+        ids = set(ids)
+        items = list(cls.objects(id__in=list(ids)))
+        resolved = {i.id for i in items}
+        missing = ids - resolved
+        for name_candidate in missing:
+            results = list(cls.objects(name=name_candidate))
+            if not results:
+                print(f"ERROR: no match for `{name_candidate}`")
+                exit(1)
+            elif len(results) > 1:
+                print(f"ERROR: more than one match for `{name_candidate}`")
+                exit(1)
+            items.append(results[0])
+        return items
+
+    @classmethod
+    def _resolve_entities(
+        cls,
+        experiments: Sequence[str] = None,
+        projects: Sequence[str] = None,
+        task_statuses: Sequence[str] = None,
+    ) -> Dict[Type[mongoengine.Document], Set[mongoengine.Document]]:
+        entities = defaultdict(set)
+
+        if projects:
+            print("Reading projects...")
+            entities[Project].update(cls._resolve_type(Project, projects))
+            print("--> Reading project experiments...")
+            query = Q(
+                project__in=list(set(filter(None, (p.id for p in entities[Project])))),
+                system_tags__nin=[EntityVisibility.archived.value],
+            )
+            if task_statuses:
+                query &= Q(status__in=list(set(task_statuses)))
+            objs = Task.objects(query)
+            entities[Task].update(o for o in objs if o.id not in (experiments or []))
+
+        if experiments:
+            print("Reading experiments...")
+            entities[Task].update(cls._resolve_type(Task, experiments))
+            print("--> Reading experiments projects...")
+            objs = Project.objects(
+                id__in=list(set(filter(None, (p.project for p in entities[Task]))))
+            )
+            project_ids = {p.id for p in entities[Project]}
+            entities[Project].update(o for o in objs if o.id not in project_ids)
+
+        model_ids = {
+            model_id
+            for task in entities[Task]
+            for model_id in (task.output.model, task.execution.model)
+            if model_id
+        }
+        if model_ids:
+            print("Reading models...")
+            entities[Model] = set(Model.objects(id__in=list(model_ids)))
+
+        return entities
+
+    @classmethod
+    def _filter_out_export_tags(cls, tags: Sequence[str]) -> Sequence[str]:
+        if not tags:
+            return tags
+        return [tag for tag in tags if not tag.startswith(cls.export_tag_prefix)]
+
+    @classmethod
+    def _cleanup_model(cls, model: Model):
+        model.company = ""
+        model.user = ""
+        model.tags = cls._filter_out_export_tags(model.tags)
+
+    @classmethod
+    def _cleanup_task(cls, task: Task):
+        task.comment = "Auto generated by Allegro.ai"
+        task.status_message = ""
+        task.status_reason = ""
+        task.user = ""
+        task.company = ""
+        task.tags = cls._filter_out_export_tags(task.tags)
+        if task.output:
+            task.output.destination = None
+
+    @classmethod
+    def _cleanup_project(cls, project: Project):
+        project.user = ""
+        project.company = ""
+        project.tags = cls._filter_out_export_tags(project.tags)
+
+    @classmethod
+    def _cleanup_entity(cls, entity_cls, entity):
+        if entity_cls == Task:
+            cls._cleanup_task(entity)
+        elif entity_cls == Model:
+            cls._cleanup_model(entity)
+        elif entity == Project:
+            cls._cleanup_project(entity)
+
+    @classmethod
+    def _add_tag(cls, items: Sequence[Union[Project, Task, Model]], tag: str):
+        try:
+            for item in items:
+                item.update(upsert=False, tags=sorted(item.tags + [tag]))
+        except AttributeError:
+            pass
+
+    @classmethod
+    def _export_task_events(
+        cls, task: Task, base_filename: str, writer: ZipFile, hash_
+    ) -> Sequence[str]:
+        artifacts = []
+        filename = f"{base_filename}_{task.id}{cls.events_file_suffix}.json"
+        print(f"Writing task events into {writer.filename}:{filename}")
+        with BytesIO() as f:
+            with cls.JsonLinesWriter(f) as w:
+                scroll_id = None
+                while True:
+                    res = cls.event_bll.get_task_events(
+                        task.company, task.id, scroll_id=scroll_id
+                    )
+                    if not res.events:
+                        break
+                    scroll_id = res.next_scroll_id
+                    for event in res.events:
+                        event_type = event.get("type")
+                        if event_type == "training_debug_image":
+                            url = cls._get_fixed_url(event.get("url"))
+                            if url:
+                                event["url"] = url
+                                artifacts.append(url)
+                        elif event_type == "plot":
+                            plot_str: str = event.get("plot_str", "")
+                            for match in cls.img_source_regex.findall(plot_str):
+                                url = cls._get_fixed_url(match)
+                                if match != url:
+                                    plot_str = plot_str.replace(match, url)
+                                artifacts.append(url)
+                        w.write(json.dumps(event))
+            data = f.getvalue()
+            hash_.update(data)
+            writer.writestr(filename, data)
+
+        return artifacts
+
+    @staticmethod
+    def _get_fixed_url(url: Optional[str]) -> Optional[str]:
+        if not (url and url.lower().startswith("s3://")):
+            return url
+        try:
+            fixed = furl(url)
+            fixed.scheme = "https"
+            fixed.host += ".s3.amazonaws.com"
+            return fixed.url
+        except Exception as ex:
+            print(f"Failed processing link {url}. " + str(ex))
+            return url
+
+    @classmethod
+    def _export_entity_related_data(
+        cls, entity_cls, entity, base_filename: str, writer: ZipFile, hash_
+    ):
+        if entity_cls == Task:
+            return [
+                *cls._get_task_output_artifacts(entity),
+                *cls._export_task_events(entity, base_filename, writer, hash_),
+            ]
+
+        if entity_cls == Model:
+            entity.uri = cls._get_fixed_url(entity.uri)
+            return [entity.uri] if entity.uri else []
+
+        return []
+
+    @classmethod
+    def _get_task_output_artifacts(cls, task: Task) -> Sequence[str]:
+        if not task.execution.artifacts:
+            return []
+
+        for a in task.execution.artifacts:
+            if a.mode == ArtifactModes.output:
+                a.uri = cls._get_fixed_url(a.uri)
+
+        return [
+            a.uri
+            for a in task.execution.artifacts
+            if a.mode == ArtifactModes.output and a.uri
+        ]
+
+    @classmethod
+    def _export_artifacts(
+        cls, writer: ZipFile, artifacts: Sequence[str], artifacts_path: str
+    ):
+        unique_paths = set(unquote(str(furl(artifact).path)) for artifact in artifacts)
+        print(f"Writing {len(unique_paths)} artifacts into {writer.filename}")
+        for path in unique_paths:
+            path = path.lstrip("/")
+            full_path = os.path.join(artifacts_path, path)
+            if os.path.isfile(full_path):
+                writer.write(full_path, path)
+            else:
+                print(f"Artifact {full_path} not found")
+
+    @staticmethod
+    def _get_base_filename(cls_: type):
+        return f"{cls_.__module__}.{cls_.__name__}"
+
+    @classmethod
+    def _export(
+        cls, writer: ZipFile, entities: dict, hash_, tag_entities: bool = False
+    ) -> Sequence[str]:
+        """
+        Export the requested experiments, projects and models and return the list of artifact files
+        Always do the export on sorted items since the order of items influence hash
+        """
+        artifacts = []
+        now = datetime.utcnow()
+        for cls_ in sorted(entities, key=attrgetter("__name__")):
+            items = sorted(entities[cls_], key=attrgetter("id"))
+            if not items:
+                continue
+            base_filename = cls._get_base_filename(cls_)
+            for item in items:
+                artifacts.extend(
+                    cls._export_entity_related_data(
+                        cls_, item, base_filename, writer, hash_
+                    )
+                )
+            filename = base_filename + ".json"
+            print(f"Writing {len(items)} items into {writer.filename}:{filename}")
+            with BytesIO() as f:
+                with cls.JsonLinesWriter(f) as w:
+                    for item in items:
+                        cls._cleanup_entity(cls_, item)
+                        w.write(item.to_json())
+                data = f.getvalue()
+                hash_.update(data)
+                writer.writestr(filename, data)
+
+            if tag_entities:
+                cls._add_tag(items, now.strftime(cls.export_tag))
+
+        return artifacts
+
+    @staticmethod
+    def json_lines(file: BinaryIO):
+        for line in file:
+            clean = (
+                line.decode("utf-8")
+                .rstrip("\r\n")
+                .strip()
+                .lstrip("[")
+                .rstrip(",]")
+                .strip()
+            )
+            if not clean:
+                continue
+            yield clean
+
+    @classmethod
+    def _import(
+        cls,
+        reader: ZipFile,
+        company_id: str = "",
+        user_id: str = None,
+        metadata: Mapping[str, Any] = None,
+    ):
+        """
+        Import entities and events from the zip file
+        Start from entities since event import will require the tasks already in DB
+        """
+        event_file_ending = cls.events_file_suffix + ".json"
+        entity_files = (
+            fi
+            for fi in reader.filelist
+            if not fi.orig_filename.endswith(event_file_ending)
+            and fi.orig_filename != cls.metadata_filename
+        )
+        event_files = (
+            fi for fi in reader.filelist if fi.orig_filename.endswith(event_file_ending)
+        )
+        for files, reader_func in (
+            (entity_files, partial(cls._import_entity, metadata=metadata or {})),
+            (event_files, cls._import_events),
+        ):
+            for file_info in files:
+                with reader.open(file_info) as f:
+                    full_name = splitext(file_info.orig_filename)[0]
+                    print(f"Reading {reader.filename}:{full_name}...")
+                    reader_func(f, full_name, company_id, user_id)
+
+    @classmethod
+    def _import_entity(
+        cls,
+        f: BinaryIO,
+        full_name: str,
+        company_id: str,
+        user_id: str,
+        metadata: Mapping[str, Any],
+    ):
+        module_name, _, class_name = full_name.rpartition(".")
+        module = importlib.import_module(module_name)
+        cls_: Type[mongoengine.Document] = getattr(module, class_name)
+        print(f"Writing {cls_.__name__.lower()}s into database")
+
+        override_project_count = 0
+        for item in cls.json_lines(f):
+            doc = cls_.from_json(item, created=True)
+            if hasattr(doc, "user"):
+                doc.user = user_id
+            if hasattr(doc, "company"):
+                doc.company = company_id
+            if isinstance(doc, Project):
+                override_project_name = metadata.get("project_name", None)
+                if override_project_name:
+                    if override_project_count:
+                        override_project_name = (
+                            f"{override_project_name} {override_project_count + 1}"
+                        )
+                    override_project_count += 1
+                    doc.name = override_project_name
+
+                doc.logo_url = metadata.get("logo_url", None)
+                doc.logo_blob = metadata.get("logo_blob", None)
+
+                cls_.objects(company=company_id, name=doc.name, id__ne=doc.id).update(
+                    set__name=f"{doc.name}_{datetime.utcnow().strftime('%Y-%m-%d_%H-%M-%S')}"
+                )
+
+            doc.save()
+
+            if isinstance(doc, Task):
+                cls.event_bll.delete_task_events(company_id, doc.id, allow_locked=True)
+
+    @classmethod
+    def _import_events(cls, f: BinaryIO, full_name: str, company_id: str, _):
+        _, _, task_id = full_name[0 : -len(cls.events_file_suffix)].rpartition("_")
+        print(f"Writing events for task {task_id} into database")
+        for events_chunk in chunked_iter(cls.json_lines(f), 1000):
+            events = [json.loads(item) for item in events_chunk]
+            cls.event_bll.add_events(
+                company_id, events=events, worker="", allow_locked_tasks=True
+            )

server/mongo/initialize/user.py

@@ -0,0 +1,80 @@
+from datetime import datetime
+from logging import Logger
+
+import attr
+
+from database.model.auth import Role
+from database.model.auth import User as AuthUser, Credentials
+from database.model.user import User
+from service_repo.auth.fixed_user import FixedUser
+
+
+def _ensure_auth_user(user_data: dict, company_id: str, log: Logger, revoke: bool = False):
+    key, secret = user_data.get("key"), user_data.get("secret")
+    if not (key and secret):
+        credentials = None
+    else:
+        creds = Credentials(key=key, secret=secret)
+
+        user = AuthUser.objects(credentials__match=creds).first()
+        if user:
+            if revoke:
+                user.credentials = []
+                user.save()
+            return user.id
+
+        credentials = [] if revoke else [creds]
+
+    user_id = user_data.get("id", f"__{user_data['name']}__")
+
+    log.info(f"Creating user: {user_data['name']}")
+
+    user = AuthUser(
+        id=user_id,
+        name=user_data["name"],
+        company=company_id,
+        role=user_data["role"],
+        email=user_data["email"],
+        created=datetime.utcnow(),
+        credentials=credentials,
+    )
+
+    user.save()
+
+    return user.id
+
+
+def _ensure_backend_user(user_id: str, company_id: str, user_name: str):
+    given_name, _, family_name = user_name.partition(" ")
+
+    User(
+        id=user_id,
+        company=company_id,
+        name=user_name,
+        given_name=given_name,
+        family_name=family_name,
+    ).save()
+
+    return user_id
+
+
+def ensure_fixed_user(user: FixedUser, log: Logger):
+    db_user = User.objects(company=user.company, id=user.user_id).first()
+    if db_user:
+        # noinspection PyBroadException
+        try:
+            log.info(f"Updating user name: {user.name}")
+            given_name, _, family_name = user.name.partition(" ")
+            db_user.update(name=user.name, given_name=given_name, family_name=family_name)
+        except Exception:
+            pass
+        return
+
+    data = attr.asdict(user)
+    data["id"] = user.user_id
+    data["email"] = f"{user.user_id}@example.com"
+    data["role"] = Role.guest if user.is_guest else Role.user
+
+    _ensure_auth_user(user_data=data, company_id=user.company, log=log)
+
+    return _ensure_backend_user(user.user_id, user.company, user.name)

server/mongo/initialize/util.py

@@ -0,0 +1,37 @@
+from logging import Logger
+from uuid import uuid4
+
+from bll.queue import QueueBLL
+from config import config
+from database.model.company import Company
+from database.model.queue import Queue
+from database.model.settings import Settings, SettingKeys
+
+log = config.logger(__file__)
+
+
+def _ensure_company(company_id, company_name, log: Logger):
+    company = Company.objects(id=company_id).only("id").first()
+    if company:
+        return company_id
+
+    log.info(f"Creating company: {company_name}")
+    company = Company(id=company_id, name=company_name)
+    company.save()
+    return company_id
+
+
+def _ensure_default_queue(company):
+    """
+    If no queue is present for the company then
+    create a new one and mark it as a default
+    """
+    queue = Queue.objects(company=company).only("id").first()
+    if queue:
+        return
+
+    QueueBLL.create(company, name="default", system_tags=["default"])
+
+
+def _ensure_uuid():
+    Settings.add_value(SettingKeys.server__uuid, str(uuid4()))

server/mongo/migrations/0.13.0.py

@@ -0,0 +1,20 @@
+import json
+
+from pymongo.database import Database, Collection
+
+
+def migrate_auth(db: Database):
+    collection: Collection = db["user"]
+    if "name_1_company_1" in [doc["name"] for doc in collection.list_indexes()]:
+        collection.drop_index("name_1_company_1")
+
+
+def migrate_backend(db: Database):
+    collection: Collection = db["user"]
+    users = collection.find(
+        {"preferences": {"$exists": True, "$ne": None, "$type": "object"}}
+    )
+    for doc in users:
+        collection.update_one(
+            {"_id": doc["_id"]}, {"$set": {"preferences": json.dumps(doc["preferences"])}}
+        )

server/mongo/migrations/0.14.0.py

@@ -0,0 +1,46 @@
+import hashlib
+
+from pymongo.database import Database, Collection
+
+from service_repo.auth.fixed_user import FixedUser
+
+
+def _get_ids():
+    if not FixedUser.enabled():
+        return
+
+    return {
+        hashlib.md5(f"{user.username}:{user.password}".encode()).hexdigest(): user.user_id
+        for user in FixedUser.from_config()
+    }
+
+
+def _switch_uuid(collection: Collection, uuid_field: str, uuids: dict):
+    docs = list(collection.find({uuid_field: {"$in": [uuids]}}))
+    if not docs:
+        return
+    replaced_uuids = [doc[uuid_field] for doc in docs]
+    for doc in docs:
+        doc[uuid_field] = uuids[doc[uuid_field]]
+    collection.insert_many(docs)
+    collection.delete_many({uuid_field: {"$in": replaced_uuids}})
+
+
+def migrate_auth(db: Database):
+    uuids = _get_ids()
+    if not uuids:
+        return
+
+    collection = db["user"]
+    collection.drop_index("name_1_company_1")
+
+    _switch_uuid(collection=collection, uuid_field="_id", uuids=uuids)
+
+
+def migrate_backend(db: Database):
+    uuids = _get_ids()
+    if not uuids:
+        return
+
+    for name in ("project", "task", "model"):
+        _switch_uuid(collection=db[name], uuid_field="user", uuids=uuids)

server/mongo/migrations/0.15.0.py

@@ -0,0 +1,58 @@
+from collections import Collection
+from typing import Sequence
+
+from pymongo.database import Database, Collection
+
+
+def _drop_all_indices_from_collections(db: Database, names: Sequence[str]):
+    for collection_name in db.list_collection_names():
+        if collection_name not in names:
+            continue
+        collection: Collection = db[collection_name]
+        collection.drop_indexes()
+
+
+def migrate_auth(db: Database):
+    """
+    Remove the old indices from the collections since
+    they may come out of sync with the latest changes
+    in the code and mongo libraries update
+    """
+    _drop_all_indices_from_collections(db, ["user"])
+
+
+def migrate_backend(db: Database):
+    """
+    1. Sort tags and system tags
+    2. Remove the old indices from the collections since
+        they may come out of sync with the latest changes
+        in the code and mongo libraries update
+    """
+
+    fields = ("tags", "system_tags")
+    query = {"$or": [{field: {"$exists": True, "$ne": []}} for field in fields]}
+    for collection_name in ("task", "model", "project", "queue"):
+        collection = db[collection_name]
+        for doc in collection.find(filter=query, projection=fields):
+            update = {
+                field: sorted(doc[field])
+                for field in fields
+                if doc.get(field)
+            }
+            if update:
+                collection.update_one({"_id": doc["_id"]}, {"$set": update})
+
+    _drop_all_indices_from_collections(
+        db,
+        [
+            "company",
+            "model",
+            "project",
+            "queue",
+            "settings",
+            "task",
+            "task__trash",
+            "user",
+            "versions",
+        ],
+    )

server/mongo/migrations/0.16.0.py

@@ -0,0 +1,36 @@
+from pymongo.database import Database, Collection
+
+from bll.task.param_utils import (
+    hyperparams_legacy_type,
+    hyperparams_default_section,
+    split_param_name,
+)
+from tools import safe_get
+
+
+def migrate_backend(db: Database):
+    hyperparam_fields = ("execution.parameters", "hyperparams")
+    configuration_fields = ("execution.model_desc", "configuration")
+    collection: Collection = db["task"]
+    for doc in collection.find(projection=hyperparam_fields + configuration_fields):
+        set_commands = {}
+        for (old_field, new_field), default_section in zip(
+            (hyperparam_fields, configuration_fields),
+            (hyperparams_default_section, None),
+        ):
+            legacy = safe_get(doc, old_field, separator=".")
+            if not legacy:
+                continue
+            for full_name, value in legacy.items():
+                section, name = split_param_name(full_name, default_section)
+                new_path = list(filter(None, (new_field, section, name)))
+                # if safe_get(doc, new_path) is not None:
+                #    continue
+                new_value = dict(
+                    name=name, type=hyperparams_legacy_type, value=str(value)
+                )
+                if section is not None:
+                    new_value["section"] = section
+                set_commands[".".join(new_path)] = new_value
+        if set_commands:
+            collection.update_one({"_id": doc["_id"]}, {"$set": set_commands})