Update AWS AMIs for v0.15.0

Fix the way a fixed user id is generated

.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

@@ -1,4 +1,4 @@
-# TRAINS Server
+# Trains Server
 
 ##  Auto-Magical Experiment Manager & Version Control for AI
 
@@ -7,27 +7,24 @@
 [![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/)
+
 ## 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 +41,43 @@ 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://github.com/allegroai/trains-server/blob/master/docs/install_aws.md)
+- Pre-built [GCP Custom Image](https://github.com/allegroai/trains-server/blob/master/docs/install_gcp.md)
+- Pre-built Docker Image
+    - [Linux](https://github.com/allegroai/trains-server/blob/master/docs/install_linux_mac.md)
+    - [macOS](https://github.com/allegroai/trains-server/blob/master/docs/install_linux_mac.md)
+    - [Windows 10](https://github.com/allegroai/trains-server/blob/master/docs/install_win.md)
+- Kubernetes    
+    - [Kubernetes Helm](https://github.com/allegroai/trains-server-helm#prerequisites)
+    - Manual [Kubernetes installation](https://github.com/allegroai/trains-server-k8s#prerequisites)
 
-    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 +90,80 @@ 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?
+## Advanced Functionality
 
-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
+**trains-server** provides a few additional useful features, which can be manually enabled:
+ 
+* [Web login authentication](https://github.com/allegroai/trains-server/blob/master/docs/faq.md#web-auth)
+* [Non-responsive experiments watchdog](https://github.com/allegroai/trains-server/blob/master/docs/faq.md#watchdog-the-non-responsive-task-watchdog-settings)  
+
+## 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. 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://github.com/allegroai/trains-server/blob/master/docs/faq.md#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 server [FAQ](https://github.com/allegroai/trains-server/blob/master/docs/faq.md), 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

@@ -20,9 +20,12 @@ services:
       - 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:

docker-compose-win10.yml

@@ -0,0 +1,122 @@
+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__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"
+      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:
+      memlock:
+        soft: -1
+        hard: -1
+      nofile:
+        soft: 65536
+        hard: 65536
+    image: docker.elastic.co/elasticsearch/elasticsearch:5.6.16
+    restart: unless-stopped
+    volumes:
+    - c:/opt/trains/data/elastic:/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
+    ports:
+    - "8081:8081"
+
+  mongo:
+    networks:
+      - backend
+    container_name: trains-mongo
+    image: mongo:3.6.5
+    restart: unless-stopped
+    command: --setParameter internalQueryExecMaxBlockingSortBytes=196100200
+    volumes:
+    - mongodata:/data
+    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
+
+volumes:
+  mongodata:

docker-compose.yml

@@ -16,9 +16,14 @@ services:
       - 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__apiserver__mongo__pre_populate__enabled: "true"
+      TRAINS__apiserver__mongo__pre_populate__zip_file: "/opt/trains/db-pre-populate/export.zip"
     ports:
     - "8008:8008"
     networks:
@@ -110,6 +115,36 @@ services:
     ports:
     - "8080:80"
 
+  agent-services:
+    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: ${TRAINS_API_HOST:-}
+      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 +48,161 @@ 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 - v0.15.0 (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-0a05eb5b384a84609 
+* **ap-south-1** : ami-00f190b50e60b1eb5 
+* **eu-west-3** : ami-044fad585e1d1798e 
+* **eu-west-2** : ami-04ab930416a4af8c5 
+* **eu-west-1** : ami-00c022f333417e78e 
+* **ap-northeast-2** : ami-0c436e94f461a9a22 
+* **ap-northeast-1** : ami-018e761ad0009d5d4 
+* **sa-east-1** : ami-0b6c0e8e93b6ebbdd 
+* **ca-central-1** : ami-0cf12aab70c14237d 
+* **ap-southeast-1** : ami-0fe7840b9bde05581 
+* **ap-southeast-2** : ami-00f230e86e1afda91 
+* **eu-central-1** : ami-0635d13b79f76e04f 
+* **us-east-2** : ami-0b323078d0206db0e 
+* **us-west-1** : ami-07fdc1d461906f957 
+* **us-west-2** : ami-0a5cac167c3ebdedb 
+* **us-east-1** : ami-0d03956bea3aa5a44
+
+### v0.15.0 (static update)
+
+* **eu-north-1** : ami-0475a5068d615769b 
+* **ap-south-1** : ami-00c7e642badaa2ebf 
+* **eu-west-3** : ami-0655f769c28843e25 
+* **eu-west-2** : ami-04d82f48f09e2b846 
+* **eu-west-1** : ami-07a2aab2dc7b4ec5f 
+* **ap-northeast-2** : ami-0257ab220a8bc7a52 
+* **ap-northeast-1** : ami-0c4900af758b91dde 
+* **sa-east-1** : ami-021f758a4a21d5725 
+* **ca-central-1** : ami-0ce9703b3b47cfe70 
+* **ap-southeast-1** : ami-0b38689fdb8f71b74 
+* **ap-southeast-2** : ami-0c2b3a171e7ae4b00 
+* **eu-central-1** : ami-0fdd3420d6e6b4a1f 
+* **us-east-2** : ami-0288e9654da36ed1c 
+* **us-west-1** : ami-0f1d6ee0b73fe9ca2 
+* **us-west-2** : ami-025f0c5bfeacbf390 
+* **us-east-1** : ami-0b17b0bfa8b91f805 
+
+### 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 +220,8 @@ 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 +239,8 @@ 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 +259,7 @@ 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 +277,4 @@ 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 +1,58 @@
+# 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**.  
+The service port numbers on our Trains Server GCP Custom Image are:
+
+- Web application: `8080`
+- API Server: `8008`
+- File Server: `8081`
+
+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**.
+
+## Released versions
+
+The following sections contain lists of Custom Image URLs (exported in different formats) for each released **trains-server** version.
+
+### Latest version image (v0.14.1)
+
+- https://storage.googleapis.com/allegro-files/trains-server/trains-server.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:
+
+        sudo 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.
+
+        sudo 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/fileserver.py

@@ -10,10 +10,14 @@ 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.route("/", methods=["POST"])
 def upload():
@@ -54,12 +58,13 @@ 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__ = "2.8.0"

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

@@ -58,3 +58,7 @@ class UpdateResponse(models.Base):
 class PagedRequest(models.Base):
     page = fields.IntField()
     page_size = fields.IntField()
+
+
+class IdResponse(models.Base):
+    id = fields.StringField(required=True)

server/apimodels/events.py

@@ -1,9 +1,12 @@
 from typing import Sequence
 
-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
 
 from apimodels import ListField, IntField, ActualEnumField
+from bll.event.event_metrics import EventType
 from bll.event.scalar_key import ScalarKeyEnum
 
 
@@ -17,4 +20,52 @@ 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)]
+    )
+
+
+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 LogEventsRequest(Base):
+    task: str = StringField(required=True)
+    batch_size: int = IntField(default=500)
+    navigate_earlier: bool = BoolField(default=True)
+    refresh: bool = BoolField(default=False)
+    scroll_id: str = StringField()
+
+
+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

@@ -9,7 +9,7 @@ from apimodels.tasks import PublishResponse as TaskPublishResponse
 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 +1,10 @@
+from jsonmodels import fields, models
+
+
+class Filter(models.Base):
+    system_tags = fields.ListField([str])
+
+
+class TagsRequest(models.Base):
+    include_system = fields.BoolField(default=False)
+    filter = fields.EmbeddedField(Filter)

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

@@ -1,6 +1,6 @@
 import six
 from jsonmodels import models
-from jsonmodels.fields import StringField, BoolField, IntField
+from jsonmodels.fields import StringField, BoolField, IntField, EmbeddedField
 from jsonmodels.validators import Enum
 
 from apimodels import DictField, ListField
@@ -9,6 +9,24 @@ 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 +90,31 @@ 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()
+    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)

server/apimodels/workers.py

@@ -1,4 +1,3 @@
-import json
 from enum import Enum
 
 import six
@@ -13,7 +12,7 @@ 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
 
@@ -61,7 +60,7 @@ 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)
@@ -75,13 +74,6 @@ class WorkerEntry(Base):
     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))
-
 
 class CurrentTaskEntry(IdNameEntry):
     running_time = IntField()

server/bll/event/debug_images_iterator.py

@@ -0,0 +1,462 @@
+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}}]
+                }
+            },
+            "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, routing=task)
+        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}},
+        ]
+        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": {"_term": "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, routing=metric.task)
+        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
 
-import attr
 import six
 from elasticsearch import helpers
 from mongoengine import Q
@@ -14,67 +13,92 @@ 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 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")
 
-    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, redis=self.redis)
 
     @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
 
@@ -103,6 +127,9 @@ 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
@@ -117,89 +144,82 @@ 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])
+            es_action["_routing"] = 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 +230,34 @@ class EventBLL(object):
         metric_hash = dbutils.hash_field_name(metric)
         variant_hash = dbutils.hash_field_name(variant)
 
-        last_events = task_last_events[task_id]
-
         timestamp = last_events[metric_hash][variant_hash].get("timestamp", None)
         if timestamp is None or timestamp < event["timestamp"]:
             last_events[metric_hash][variant_hash] = event
 
-    def _update_task(self, company_id, task_id, now, iter_max=None, last_events=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][event_type] = event
+
+    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 +270,18 @@ 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"],
                 )
             )
 
+        if last_events:
+            fields["last_events"] = last_events
+
         if not fields:
             return False
 
@@ -245,7 +289,7 @@ 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,
@@ -276,7 +320,9 @@ 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")
+                es_res = self.es.search(
+                    index=es_index, body=es_req, scroll="1h", routing=task_id
+                )
 
         events = [hit["_source"] for hit in es_res["hits"]["hits"]]
         next_scroll_id = es_res["_scroll_id"]
@@ -294,10 +340,16 @@ 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": {
@@ -496,8 +548,18 @@ 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}}]}},
@@ -537,14 +599,14 @@ class EventBLL(object):
                 "metrics": {
                     "terms": {
                         "field": "metric",
-                        "size": 1000,
+                        "size": EventMetrics.MAX_METRICS_COUNT,
                         "order": {"_term": "asc"},
                     },
                     "aggs": {
                         "variants": {
                             "terms": {
                                 "field": "variant",
-                                "size": 1000,
+                                "size": EventMetrics.MAX_VARIANTS_COUNT,
                                 "order": {"_term": "asc"},
                             },
                             "aggs": {

server/bll/event/event_metrics.py

@@ -1,12 +1,13 @@
 import itertools
 from collections import defaultdict
 from concurrent.futures import ThreadPoolExecutor
+from enum import Enum
 from functools import partial
 from operator import itemgetter
+from typing import Sequence, Tuple, Callable, Iterable
 
+from boltons.iterutils import bucketize
 from elasticsearch import Elasticsearch
-from typing import Sequence, Tuple, Callable
-
 from mongoengine import Q
 
 from apierrors import errors
@@ -20,10 +21,19 @@ from utilities 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_TASKS_COUNT = 50
     MAX_METRICS_COUNT = 200
     MAX_VARIANTS_COUNT = 500
+    MAX_AGGS_ELEMENTS_COUNT = 50
 
     def __init__(self, es: Elasticsearch):
         self.es = es
@@ -62,6 +72,12 @@ class EventMetrics:
         Compare scalar metrics for different tasks per metric and variant
         The amount of points in each histogram should not exceed the requested samples
         """
+        if len(task_ids) > self.MAX_TASKS_COUNT:
+            raise errors.BadRequest(
+                f"Up to {self.MAX_TASKS_COUNT} tasks supported for comparison",
+                len(task_ids),
+            )
+
         task_name_by_id = {}
         with translate_errors_context():
             task_objs = Task.get_many(
@@ -97,6 +113,31 @@ class EventMetrics:
     MetricInterval = Tuple[int, Sequence[TaskMetric]]
     MetricData = Tuple[str, dict]
 
+    def _split_metrics_by_max_aggs_count(
+        self, task_metrics: Sequence[TaskMetric]
+    ) -> Iterable[Sequence[TaskMetric]]:
+        """
+        Return task metrics in groups where amount of task metrics in each group
+        is roughly limited by MAX_AGGS_ELEMENTS_COUNT. The split is done on metrics and
+        variants while always preserving all their tasks in the same group
+        """
+        if len(task_metrics) < self.MAX_AGGS_ELEMENTS_COUNT:
+            yield task_metrics
+            return
+
+        tm_grouped = bucketize(task_metrics, key=itemgetter(1, 2))
+        groups = []
+        for group in tm_grouped.values():
+            groups.append(group)
+            if sum(map(len, groups)) >= self.MAX_AGGS_ELEMENTS_COUNT:
+                yield list(itertools.chain(*groups))
+                groups = []
+
+        if groups:
+            yield list(itertools.chain(*groups))
+
+        return
+
     def _run_get_scalar_metrics_as_parallel(
         self,
         company_id: str,
@@ -126,21 +167,25 @@ class EventMetrics:
         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,
-                    )
+        intervals = list(
+            itertools.chain.from_iterable(
+                zip(itertools.repeat(i), self._split_metrics_by_max_aggs_count(tms))
+                for i, tms in intervals
+            )
+        )
+        max_concurrency = config.get("services.events.max_metrics_concurrency", 4)
+        with ThreadPoolExecutor(max_workers=max_concurrency) as pool:
+            metrics = itertools.chain.from_iterable(
+                pool.map(
+                    partial(get_func, task_ids=task_ids, es_index=es_index, key=key),
+                    intervals,
                 )
             )
 
         ret = defaultdict(dict)
         for metric_key, metric_values in metrics:
             ret[metric_key].update(metric_values)
+
         return ret
 
     def _get_metric_intervals(
@@ -310,7 +355,13 @@ class EventMetrics:
                     "variants": {
                         "terms": {"field": "variant", "size": self.MAX_VARIANTS_COUNT},
                         "aggs": {
-                            "tasks": {"terms": {"field": "task"}, "aggs": aggregation}
+                            "tasks": {
+                                "terms": {
+                                    "field": "task",
+                                    "size": self.MAX_TASKS_COUNT,
+                                },
+                                "aggs": aggregation,
+                            }
                         },
                     }
                 },
@@ -396,3 +447,50 @@ class EventMetrics:
                 ]
             }
         }
+
+    def get_tasks_metrics(
+        self, company_id, task_ids: Sequence, event_type: EventType
+    ) -> Sequence[Tuple]:
+        """
+        For the requested tasks return all the metrics that
+        reported events of the requested types
+        """
+        es_index = EventMetrics.get_index_name(company_id, event_type.value)
+        if not self.es.indices.exists(es_index):
+            return [(tid, []) for tid in task_ids]
+
+        max_concurrency = config.get("services.events.max_metrics_concurrency", 4)
+        with ThreadPoolExecutor(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, routing=task_id)
+
+        return [
+            metric["key"]
+            for metric in safe_get(es_res, "aggregations/metrics/buckets", default=[])
+        ]

server/bll/event/log_events_iterator.py

@@ -0,0 +1,169 @@
+from typing import Optional, Tuple, Sequence
+
+import attr
+from elasticsearch import Elasticsearch
+from jsonmodels.fields import StringField, 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 timing_context import TimingContext
+
+
+class LogEventsScrollState(Base, JsonSerializableMixin):
+    id: str = StringField(required=True)
+    task: str = StringField(required=True)
+    last_min_timestamp: Optional[int] = IntField()
+    last_max_timestamp: Optional[int] = IntField()
+
+    def reset(self):
+        """Reset the scrolling state """
+        self.last_min_timestamp = self.last_max_timestamp = None
+
+
+@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"
+
+    @property
+    def state_expiration_sec(self):
+        return config.get(
+            f"services.events.events_retrieval.state_expiration_sec", 3600
+        )
+
+    def __init__(self, redis: StrictRedis, es: Elasticsearch):
+        self.es = es
+        self.cache_manager = RedisCacheManager(
+            state_class=LogEventsScrollState,
+            redis=redis,
+            expiration_interval=self.state_expiration_sec,
+        )
+
+    def get_task_events(
+        self,
+        company_id: str,
+        task_id: str,
+        batch_size: int,
+        navigate_earlier: bool = True,
+        refresh: bool = False,
+        state_id: str = None,
+    ) -> TaskEventsResult:
+        es_index = EventMetrics.get_index_name(company_id, self.EVENT_TYPE)
+        if not self.es.indices.exists(es_index):
+            return TaskEventsResult()
+
+        def init_state(state_: LogEventsScrollState):
+            state_.task = task_id
+
+        def validate_state(state_: LogEventsScrollState):
+            """
+            Checks that the task id stored in the state
+            is equal to the one passed with the current call
+            Refresh the state if requested
+            """
+            if state_.task != task_id:
+                raise errors.bad_request.InvalidScrollId(
+                    "Task stored in the state does not match the passed one",
+                    scroll_id=state_.id,
+                )
+            if refresh:
+                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 = TaskEventsResult(next_scroll_id=state.id)
+            res.events, res.total_events = self._get_events(
+                es_index=es_index,
+                batch_size=batch_size,
+                navigate_earlier=navigate_earlier,
+                state=state,
+            )
+            return res
+
+    def _get_events(
+        self,
+        es_index,
+        batch_size: int,
+        navigate_earlier: bool,
+        state: LogEventsScrollState,
+    ) -> 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": state.task}},
+            "sort": {"timestamp": "desc" if navigate_earlier else "asc"},
+        }
+
+        if navigate_earlier and state.last_min_timestamp is not None:
+            es_req["search_after"] = [state.last_min_timestamp]
+        elif not navigate_earlier and state.last_max_timestamp is not None:
+            es_req["search_after"] = [state.last_max_timestamp]
+
+        with translate_errors_context(), TimingContext("es", "get_task_events"):
+            es_result = self.es.search(index=es_index, body=es_req, routing=state.task)
+            hits = es_result["hits"]["hits"]
+            hits_total = es_result["hits"]["total"]
+            if not hits:
+                return [], hits_total
+
+            events = [hit["_source"] for hit in hits]
+            if navigate_earlier:
+                state.last_max_timestamp = events[0]["timestamp"]
+                state.last_min_timestamp = events[-1]["timestamp"]
+            else:
+                state.last_min_timestamp = events[0]["timestamp"]
+                state.last_max_timestamp = events[-1]["timestamp"]
+
+            # 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": state.task}},
+                            {"term": {"timestamp": events[-1]["timestamp"]}},
+                        ]
+                    }
+                },
+            }
+            es_result = self.es.search(index=es_index, body=es_req, routing=state.task)
+            hits = es_result["hits"]["hits"]
+            if not hits or len(hits) < 2:
+                # if only one element is returned for the last timestamp
+                # then it is already present in the events
+                return events, hits_total
+
+            last_events = [hit["_source"] for hit in es_result["hits"]["hits"]]
+            already_present_ids = set(ev["_id"] for ev in events)
+
+            # return the list merged from original query results +
+            # leftovers from the last timestamp
+            return (
+                [
+                    *events,
+                    *(ev for ev in last_events if ev["_id"] not in already_present_ids),
+                ],
+                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,
+                    "interval": f"{interval}ms",
                     "min_doc_count": 1,
                 }
             }
@@ -150,7 +150,7 @@ class ISOTimeKey(ScalarKey):
             self.name: {
                 "date_histogram": {
                     "field": "timestamp",
-                    "interval": interval,
+                    "interval": f"{interval}ms",
                     "min_doc_count": 1,
                     "format": "strict_date_time",
                 }

server/bll/organization/__init__.py

@@ -0,0 +1,85 @@
+from typing import Sequence
+
+from mongoengine import Q
+
+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__)
+
+
+class OrgBLL:
+    _tags_field = "tags"
+    _system_tags_field = "system_tags"
+    _settings_prefix = "services.organization"
+
+    def __init__(self, redis=None):
+        self.redis = redis or redman.connection("apiserver")
+
+    @property
+    def _tags_cache_expiration_seconds(self):
+        return config.get(
+            f"{self._settings_prefix}.tags_cache.expiration_seconds", 3600
+        )
+
+    @staticmethod
+    def _get_tags_cache_key(company, field: str, filter_: Sequence[str] = None):
+        filter_str = "_".join(filter_) if filter_ else ""
+        return f"{field}_{company}_{filter_str}"
+
+    @staticmethod
+    def _get_tags_from_db(company, field, filter_: Sequence[str] = None) -> set:
+        query = Q(company=company)
+        if filter_:
+            query &= GetMixin.get_list_field_query("system_tags", filter_)
+
+        tags = set()
+        for cls_ in (Task, Model):
+            tags |= set(cls_.objects(query).distinct(field))
+        return tags
+
+    def get_tags(
+        self, company, include_system: bool = False, filter_: Sequence[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,
+            *([self._system_tags_field] if include_system else []),
+        ]
+        redis_keys = [self._get_tags_cache_key(company, f, 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, filter_))
+                self.redis.setex(
+                    key,
+                    time=self._tags_cache_expiration_seconds,
+                    value=json.dumps(tags),
+                )
+            ret[field] = tags
+
+        return ret
+
+    def update_org_tags(self, company, tags=None, system_tags=None, reset=False):
+        """
+        Updates system tags. If reset is set then both tags and system_tags
+        are recalculated. Otherwise only those that are not 'None'
+        """
+        if reset or tags is not None:
+            self.redis.delete(self._get_tags_cache_key(company, self._tags_field))
+        if reset or system_tags is not None:
+            self.redis.delete(
+                self._get_tags_cache_key(company, self._system_tags_field)
+            )

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

@@ -161,7 +161,7 @@ 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 +1,305 @@
+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 utilities 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)}*",
+            doc_type="stat",
+            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/__init__.py

@@ -4,4 +4,5 @@ from .utils import (
     update_project_time,
     validate_status_change,
     split_by,
+    ParameterKeyEscaper,
 )

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/task_bll.py

@@ -1,41 +1,64 @@
-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 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
 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 services.utils import validate_tags
 from timing_context import TimingContext
-from utilities.threads_manager import ThreadsManager
-from .utils import ChangeStatusRequest, validate_status_change
+from utilities.dicts import deep_merge
+from .utils import ChangeStatusRequest, validate_status_change, ParameterKeyEscaper
+
+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
@@ -145,30 +168,96 @@ 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,
+        execution_overrides: Optional[dict] = None,
+        validate_references: bool = False,
+    ) -> Task:
+        validate_tags(tags, system_tags)
+        task = cls.get_by_id(company_id=company_id, task_id=task_id)
+        execution_dict = task.execution.to_proper_dict() if task.execution else {}
+        execution_model_overriden = False
+        if execution_overrides:
+            parameters = execution_overrides.get("parameters")
+            if parameters is not None:
+                execution_overrides["parameters"] = {
+                    ParameterKeyEscaper.escape(k): v for k, v in parameters.items()
+                }
+            execution_dict = deep_merge(execution_dict, execution_overrides)
+            execution_model_overriden = execution_overrides.get("model") is not None
 
-        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,
+            )
+            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()
+            org_bll.update_org_tags(company_id, tags=tags, system_tags=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 +297,7 @@ 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 +315,8 @@ 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 +328,8 @@ 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:
         """
@@ -249,17 +340,33 @@ 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:
+            for path, value in last_scalar_values:
                 extra_updates[op_path("set", *path)] = value
                 if path[-1] == "value":
                     extra_updates[op_path("min", *path[:-1], "min_value")] = value
                     extra_updates[op_path("max", *path[:-1], "max_value")] = 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 +480,7 @@ 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=(
@@ -412,56 +519,95 @@ 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(
@@ -502,10 +648,7 @@ 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 +656,10 @@ class TaskBLL(object):
 
         if result:
             total = int(result.get("total", -1))
-            results = [r["_id"] for r in result.get("results", [])]
+            results = [
+                ParameterKeyEscaper.unescape(r["_id"])
+                for r in result.get("results", [])
+            ]
             remaining = max(0, total - (len(results) + page * page_size))
 
         return total, remaining, results

server/bll/task/utils.py

@@ -3,6 +3,7 @@ from typing import TypeVar, Callable, Tuple, Sequence
 
 import attr
 import six
+from boltons.dictutils import OneToOne
 
 from apierrors import errors
 from database.errors import translate_errors_context
@@ -171,3 +172,26 @@ def split_by(
         [item for cond, item in applied if cond],
         [item for cond, item in applied if not cond],
     )
+
+
+class ParameterKeyEscaper:
+    _mapping = OneToOne({".": "%2E", "$": "%24"})
+
+    @classmethod
+    def escape(cls, value):
+        """ Quote a parameter key """
+        value = value.strip().replace("%", "%%")
+        for c, r in cls._mapping.items():
+            value = value.replace(c, r)
+        return value
+
+    @classmethod
+    def _unescape(cls, value):
+        for c, r in cls._mapping.inv.items():
+            value = value.replace(c, r)
+        return value
+
+    @classmethod
+    def unescape(cls, value):
+        """ Unquote a quoted parameter key """
+        return "%".join(map(cls._unescape, value.split("%%")))

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(
@@ -64,3 +66,8 @@ 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
@@ -22,10 +23,9 @@ from database.model.auth import User
 from database.model.company import Company
 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 +33,9 @@ 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:
@@ -223,7 +223,7 @@ 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(
@@ -396,7 +396,7 @@ 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/config/basic.py

@@ -47,7 +47,7 @@ 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 +57,7 @@ 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 +77,7 @@ 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

@@ -34,6 +34,12 @@
         aggregate {
             allow_disk_use: true
         }
+
+        pre_populate {
+            enabled: false
+            zip_file: "/path/to/export.zip"
+            fail_on_error: false
+        }
     }
 
     auth {
@@ -101,4 +107,18 @@
         # 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

@@ -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/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/tasks.conf

@@ -1,7 +1,14 @@
 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
+}

server/config/info.py

@@ -1,28 +1,43 @@
 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")

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}")
 

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

@@ -43,6 +43,7 @@ class Role(object):
 
 
 class Credentials(EmbeddedDocument):
+    meta = {"strict": False}
     key = StringField(required=True)
     secret = StringField(required=True)
     last_used = DateTimeField()
@@ -52,7 +53,7 @@ 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

@@ -1,9 +1,9 @@
 import re
 from collections import namedtuple
 from functools import reduce
-from typing import Collection, Sequence, Union
+from typing import Collection, Sequence, Union, Optional
 
-from boltons.iterutils import first
+from boltons.iterutils import first, bucketize
 from dateutil.parser import parse as parse_datetime
 from mongoengine import Q, Document, ListField, StringField
 from pymongo.command_cursor import CommandCursor
@@ -34,7 +34,12 @@ 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 +65,7 @@ class ProperDictMixin(object):
 
 class GetMixin(PropsMixin):
     _text_score = "$text_score"
-
+    _projection_key = "projection"
     _ordering_key = "order_by"
     _search_text_key = "search_text"
 
@@ -71,6 +76,8 @@ class GetMixin(PropsMixin):
     }
     MultiFieldParameters = namedtuple("MultiFieldParameters", "pattern fields")
 
+    _field_collation_overrides = {}
+
     class QueryParameterOptions(object):
         def __init__(
             self,
@@ -91,11 +98,48 @@ 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 +206,7 @@ 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 +250,47 @@ 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 +345,26 @@ 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 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 +484,12 @@ class GetMixin(PropsMixin):
         )
 
     @classmethod
-    def _get_many_no_company(cls, query, parameters=None, override_projection=None):
+    def _get_many_no_company(
+        cls: Union["GetMixin", Document],
+        query,
+        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
@@ -445,6 +540,8 @@ 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.
 
@@ -485,6 +582,16 @@ 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]
@@ -578,7 +685,13 @@ 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 +708,10 @@ 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 +726,7 @@ 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)
 
 
 def validate_id(cls, company, **kwargs):
@@ -632,5 +748,5 @@ 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 +13,61 @@ 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", "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
+    )

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
 
 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 +36,7 @@ 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()

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
@@ -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 +84,7 @@ class Artifact(EmbeddedDocument):
     display_data = SafeSortedListField(ListField(UnionField((int, float, str))))
 
 
-class Execution(EmbeddedDocument):
+class Execution(EmbeddedDocument, ProperDictMixin):
     test_split = IntField(default=0)
     parameters = SafeDictField(default=dict)
     model = StringField(reference_field="Model")
@@ -94,9 +100,26 @@ 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):
+    _field_collation_overrides = {
+        "execution.parameters.": {"locale": "en_US", "numericOrdering": True},
+        "last_metrics.": {"locale": "en_US", "numericOrdering": True}
+    }
+
     meta = {
         "db_alias": Database.backend,
         "strict": strict,
@@ -104,6 +127,13 @@ 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 +158,12 @@ 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 +182,14 @@ 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)
     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))

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/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

@@ -10,7 +10,11 @@ from pathlib import Path
 from requests.adapters import HTTPAdapter
 from requests.packages.urllib3.util.retry import Retry
 
-HERE = Path(__file__).parent
+HERE = Path(__file__).resolve().parent
+
+session = requests.Session()
+adapter = HTTPAdapter(max_retries=Retry(5, backoff_factor=0.5))
+session.mount('http://', adapter)
 
 
 def apply_mappings_to_host(host: str):
@@ -20,10 +24,6 @@ def apply_mappings_to_host(host: str):
             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,

server/elastic/initialize.py

@@ -0,0 +1,27 @@
+from furl import furl
+
+from config import config
+from elastic.apply_mappings import apply_mappings_to_host
+from es_factory import get_cluster_config
+
+log = config.logger(__file__)
+
+
+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)

server/elastic/mappings/events.json

@@ -1,7 +1,7 @@
 {
   "template": "events-*",
   "settings": {
-    "number_of_shards": 5
+    "number_of_shards": 1
   },
   "mappings": {
     "_default_": {

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
 
 
@@ -46,12 +53,14 @@ 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]
 
@@ -63,13 +72,13 @@ 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 +1,65 @@
+from pathlib import Path
+
+from config import config
+from database.model.auth import Role
+from service_repo.auth.fixed_user import FixedUser
+from .migration import _apply_migrations
+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 init_mongo_data():
+    try:
+        empty_dbs = _apply_migrations(log)
+
+        _ensure_uuid()
+
+        company_id = _ensure_company(log)
+
+        _ensure_default_queue(company_id)
+
+        if empty_dbs and config.get("apiserver.mongo.pre_populate.enabled", False):
+            zip_file = config.get("apiserver.mongo.pre_populate.zip_file")
+            if not zip_file or not Path(zip_file).is_file():
+                msg = f"Failed pre-populating database: invalid zip file {zip_file}"
+                if config.get("apiserver.mongo.pre_populate.fail_on_error", False):
+                    log.error(msg)
+                    raise ValueError(msg)
+                else:
+                    log.warning(msg)
+            else:
+
+                user_id = _ensure_backend_user(
+                    "__allegroai__", company_id, "Allegro.ai"
+                )
+
+                PrePopulate.import_from_zip(zip_file, user_id=user_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()
+            for user in FixedUser.from_config():
+                try:
+                    ensure_fixed_user(user, company_id, 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 +1,86 @@
+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 _apply_migrations(log: Logger) -> bool:
+    """
+    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 = not any(
+        get_db(alias).collection_names()
+        for alias in database.utils.get_options(Database)
+    )
+
+    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"}
+
+    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")
+
+    return empty_dbs

server/mongo/initialize/pre_populate.py

@@ -0,0 +1,153 @@
+import importlib
+from collections import defaultdict
+from datetime import datetime
+from os.path import splitext
+from typing import List, Optional, Any, Type, Set, Dict
+from zipfile import ZipFile, ZIP_BZIP2
+
+import mongoengine
+from tqdm import tqdm
+
+
+class PrePopulate:
+    @classmethod
+    def export_to_zip(
+        cls, filename: str, experiments: List[str] = None, projects: List[str] = None
+    ):
+        with ZipFile(filename, mode="w", compression=ZIP_BZIP2) as zfile:
+            cls._export(zfile, experiments, projects)
+
+    @classmethod
+    def import_from_zip(cls, filename: str, user_id: str = None):
+        with ZipFile(filename) as zfile:
+            cls._import(zfile, user_id)
+
+    @staticmethod
+    def _resolve_type(
+        cls: Type[mongoengine.Document], ids: Optional[List[str]]
+    ) -> List[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: List[str] = None, projects: List[str] = None
+    ) -> Dict[Type[mongoengine.Document], Set[mongoengine.Document]]:
+        from database.model.project import Project
+        from database.model.task.task import Task
+
+        entities = defaultdict(set)
+
+        if projects:
+            print("Reading projects...")
+            entities[Project].update(cls._resolve_type(Project, projects))
+            print("--> Reading project experiments...")
+            objs = Task.objects(
+                project__in=list(set(filter(None, (p.id for p in entities[Project]))))
+            )
+            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)
+
+        return entities
+
+    @classmethod
+    def _cleanup_task(cls, task):
+        from database.model.task.task import TaskStatus
+
+        task.completed = None
+        task.started = None
+        if task.execution:
+            task.execution.model = None
+            task.execution.model_desc = None
+            task.execution.model_labels = None
+        if task.output:
+            task.output.model = None
+
+        task.status = TaskStatus.created
+        task.comment = "Auto generated by Allegro.ai"
+        task.created = datetime.utcnow()
+        task.last_iteration = 0
+        task.last_update = task.created
+        task.status_changed = task.created
+        task.status_message = ""
+        task.status_reason = ""
+        task.user = ""
+
+    @classmethod
+    def _cleanup_entity(cls, entity_cls, entity):
+        from database.model.task.task import Task
+        if entity_cls == Task:
+            cls._cleanup_task(entity)
+
+    @classmethod
+    def _export(
+        cls, writer: ZipFile, experiments: List[str] = None, projects: List[str] = None
+    ):
+        entities = cls._resolve_entities(experiments, projects)
+
+        for cls_, items in entities.items():
+            if not items:
+                continue
+            filename = f"{cls_.__module__}.{cls_.__name__}.json"
+            print(f"Writing {len(items)} items into {writer.filename}:{filename}")
+            with writer.open(filename, "w") as f:
+                f.write("[\n".encode("utf-8"))
+                last = len(items) - 1
+                for i, item in enumerate(items):
+                    cls._cleanup_entity(cls_, item)
+                    f.write(item.to_json().encode("utf-8"))
+                    if i != last:
+                        f.write(",".encode("utf-8"))
+                    f.write("\n".encode("utf-8"))
+                f.write("]\n".encode("utf-8"))
+
+    @staticmethod
+    def _import(reader: ZipFile, user_id: str = None):
+        for file_info in reader.filelist:
+            full_name = splitext(file_info.orig_filename)[0]
+            print(f"Reading {reader.filename}:{full_name}...")
+            module_name, _, class_name = full_name.rpartition(".")
+            module = importlib.import_module(module_name)
+            cls_: Type[mongoengine.Document] = getattr(module, class_name)
+
+            with reader.open(file_info) as f:
+                for item in tqdm(
+                    f.readlines(),
+                    desc=f"Writing {cls_.__name__.lower()}s into database",
+                    unit="doc",
+                ):
+                    item = (
+                        item.decode("utf-8")
+                        .strip()
+                        .lstrip("[")
+                        .rstrip("]")
+                        .rstrip(",")
+                        .strip()
+                    )
+                    if not item:
+                        continue
+                    doc = cls_.from_json(item)
+                    if user_id is not None and hasattr(doc, "user"):
+                        doc.user = user_id
+                    doc.save(force_insert=True)

server/mongo/initialize/user.py

@@ -0,0 +1,79 @@
+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):
+    ensure_credentials = {"key", "secret"}.issubset(user_data)
+    if ensure_credentials:
+        user = AuthUser.objects(
+            credentials__match=Credentials(
+                key=user_data["key"], secret=user_data["secret"]
+            )
+        ).first()
+        if user:
+            if revoke:
+                user.credentials = []
+                user.save()
+            return user.id
+
+    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(key=user_data["key"], secret=user_data["secret"])] if not revoke else []
+        if ensure_credentials
+        else None,
+    )
+
+    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, company_id: str, log: Logger):
+    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, log=log)
+
+    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()

server/mongo/initialize/util.py

@@ -0,0 +1,40 @@
+from logging import Logger
+from uuid import uuid4
+
+from bll.queue import QueueBLL
+from config import config
+from config.info import get_default_company
+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(log: Logger):
+    company_id = get_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_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/redis_manager.py

@@ -2,21 +2,23 @@ import threading
 from os import getenv
 from time import sleep
 
-from apierrors.errors.server_error import ConfigError, GeneralError
-from config import config
+from boltons.iterutils import first
 from redis import StrictRedis
 from redis.sentinel import Sentinel, SentinelConnectionPool
 
+from apierrors.errors.server_error import ConfigError, GeneralError
+from config import config
+
 log = config.logger(__file__)
 
-OVERRIDE_HOST_ENV_KEY = "REDIS_SERVICE_HOST"
-OVERRIDE_PORT_ENV_KEY = "REDIS_SERVICE_PORT"
+OVERRIDE_HOST_ENV_KEY = ("TRAINS_REDIS_SERVICE_HOST", "REDIS_SERVICE_HOST")
+OVERRIDE_PORT_ENV_KEY = ("TRAINS_REDIS_SERVICE_PORT", "REDIS_SERVICE_PORT")
 
-OVERRIDE_HOST = getenv(OVERRIDE_HOST_ENV_KEY)
+OVERRIDE_HOST = first(filter(None, map(getenv, OVERRIDE_HOST_ENV_KEY)))
 if OVERRIDE_HOST:
     log.info(f"Using override redis 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 redis port {OVERRIDE_PORT}")
 

server/requirements.txt

@@ -1,30 +1,30 @@
-six
-Flask>=0.12.2
-elasticsearch>=5.0.0,<6.0.0
-pyhocon>=0.3.35
-requests>=2.13.0
-arrow>=0.10.0
-pymongo==3.6.1  # 3.7 has a bug multiple users logged in
-Flask-Cors>=3.0.5
-Flask-Compress>=1.4.0
-mongoengine==0.16.2
-jsonmodels>=2.3
-pyjwt>=1.3.0
-gunicorn>=19.7.1
-Jinja2==2.10
-python-rapidjson>=0.6.3
-jsonschema>=2.6.0
-dpath>=1.4.2
-funcsigs==1.0.2
-luqum>=0.7.2
-typing>=3.6.4
 attrs>=19.1.0
-nested_dict>=1.61
-related>=0.7.2
-validators>=0.12.4
-fastjsonschema>=2.8
 boltons>=19.1.0
-semantic_version>=2.6.0,<3
+dpath>=1.4.2,<2.0
+elasticsearch>=5.0.0,<6.0.0
+fastjsonschema>=2.8
+Flask-Compress>=1.4.0
+Flask-Cors>=3.0.5
+Flask>=0.12.2
+funcsigs==1.0.2
 furl>=2.0.0
-redis>=2.10.5
+gunicorn>=19.7.1
 humanfriendly==4.18
+Jinja2==2.10
+jsonmodels>=2.3
+jsonschema>=2.6.0
+luqum>=0.7.2
+mongoengine==0.19.1
+nested_dict>=1.61
+psutil>=5.6.5
+pyhocon>=0.3.35
+pyjwt>=1.3.0
+pymongo==3.10.1
+python-rapidjson>=0.6.3
+redis>=2.10.5
+related>=0.7.2
+requests>=2.13.0
+semantic_version>=2.8.0,<3
+six
+tqdm
+validators>=0.12.4

server/schema/services/events.conf

@@ -171,6 +171,30 @@
                 critical
             ]
         }
+        event_type_enum {
+            type: string
+            enum: [
+                training_stats_scalar
+                training_stats_vector
+                training_debug_image
+                plot
+                log
+            ]
+        }
+        task_metric {
+            type: object
+            required: [task, metric]
+            properties {
+                task {
+                    description: "Task ID"
+                    type: string
+                }
+                metric {
+                    description: "Metric name"
+                    type: string
+                }
+            }
+        }
         task_log_event {
             description: """A log event associated with a task."""
             type: object
@@ -234,6 +258,7 @@
                 properties {
                     added { type: integer }
                     errors { type: integer }
+                    errors_info { type: object }
                 }
             }
         }
@@ -319,6 +344,84 @@
                 }
             }
         }
+        "2.7" {
+            description: "Get the debug image events for the requested amount of iterations per each task's metric"
+            request {
+                type: object
+                required: [
+                    metrics
+                ]
+                properties {
+                    metrics {
+                        type: array
+                        items { "$ref": "#/definitions/task_metric" }
+                        description: "List metrics for which the envents will be retreived"
+                    }
+                    iters {
+                        type: integer
+                        description: "Max number of latest iterations for which to return debug images"
+                    }
+                    navigate_earlier {
+                        type: boolean
+                        description: "If set then events are retreived from latest iterations to earliest ones. Otherwise from earliest iterations to the latest. The default is True"
+                    }
+                    refresh {
+                        type: boolean
+                        description: "If set then scroll will be moved to the latest iterations. The default is False"
+                    }
+                    scroll_id {
+                        type: string
+                        description: "Scroll ID of previous call (used for getting more results)"
+                    }
+                }
+            }
+            response {
+                type: object
+                properties {
+                    metrics {
+                        type: array
+                        items: { type: object }
+                        description: "Debug image events grouped by task metrics and iterations"
+                    }
+                    scroll_id {
+                        type: string
+                        description: "Scroll ID for getting more results"
+                    }
+                }
+            }
+        }
+    }
+    get_task_metrics{
+        "2.7": {
+            description: "For each task, get a list of metrics for which the requested event type was reported"
+            request {
+                type: object
+                required: [
+                    tasks
+                ]
+                properties {
+                    tasks {
+                        type: array
+                        items { type: string }
+                        description: "Task IDs"
+                    }
+                    event_type {
+                        "description": "Event type"
+                        "$ref": "#/definitions/event_type_enum"
+                    }
+                }
+            }
+            response {
+                type: object
+                properties {
+                    metrics {
+                        type: array
+                        items { type: object }
+                        description: "List of task with their metrics"
+                    }
+                }
+            }
+        }
     }
     get_task_log {
         "1.5" {
@@ -427,6 +530,59 @@
                 }
             }
         }
+//        "2.7" {
+//            description: "Get 'log' events for this task"
+//            request {
+//                type: object
+//                required: [
+//                    task
+//                ]
+//                properties {
+//                    task {
+//                        type: string
+//                        description: "Task ID"
+//                    }
+//                    batch_size {
+//                        type: integer
+//                        description: "The amount of log events to return"
+//                    }
+//                    navigate_earlier {
+//                        type: boolean
+//                        description: "If set then log events are retreived from the latest to the earliest ones (in timestamp descending order). Otherwise from the earliest to the latest ones (in timestamp ascending order). The default is True"
+//                    }
+//                    refresh {
+//                        type: boolean
+//                        description: "If set then scroll will be moved to the latest logs (if 'navigate_earlier' is set to True) or to the earliest (otherwise)"
+//                    }
+//                    scroll_id {
+//                        type: string
+//                        description: "Scroll ID of previous call (used for getting more results)"
+//                    }
+//                }
+//            }
+//            response {
+//                type: object
+//                properties {
+//                    events {
+//                        type: array
+//                        items { type: object }
+//                        description: "Log items list"
+//                    }
+//                    returned {
+//                        type: integer
+//                        description: "Number of log events returned"
+//                    }
+//                    total {
+//                        type: number
+//                        description: "Total number of log events available for this query"
+//                    }
+//                    scroll_id {
+//                        type: string
+//                        description: "Scroll ID for getting more results"
+//                    }
+//                }
+//            }
+//        }
     }
     get_task_events {
         "2.1" {
@@ -455,7 +611,7 @@
                     }
                     batch_size {
                         type: integer
-                        description: "Number of events to return each time"
+                        description: "Number of events to return each time (default 500)"
                     }
                     event_type {
                         type: string

server/schema/services/models.conf

@@ -159,6 +159,11 @@
                         description: "Get only models whose name matches this pattern (python regular expression syntax)"
                         type: string
                     }
+                    user {
+                        description: "List of user IDs used to filter results by the model's creating user"
+                        type: array
+                        items { type: string }
+                    }
                     ready {
                         description: "Indication whether to retrieve only models that are marked ready If not supplied returns both ready and not-ready projects."
                         type: boolean
@@ -261,7 +266,7 @@
                         type: string
                     }
                     uri {
-                        description: "URI for the model"
+                        description: "URI for the model. Exactly one of uri or override_model_id is a required."
                         type: string
                     }
                     name {
@@ -283,7 +288,7 @@
                         items {type: string}
                     }
                     override_model_id {
-                        description: "Override model ID. If provided, this model is updated in the task."
+                        description: "Override model ID. If provided, this model is updated in the task. Exactly one of override_model_id or uri is required."
                         type: string
                     }
                     iteration {
@@ -324,7 +329,6 @@
                 required: [
                     uri
                     name
-                    labels
                 ]
                 properties {
                     uri {

server/schema/services/organization.conf

@@ -0,0 +1,43 @@
+_description: "This service provides organization level operations"
+
+get_tags {
+  "2.8" {
+    description: "Get all the user and system tags used for the company tasks and models"
+    request {
+      type: object
+      properties {
+        include_system {
+          description: "If set to 'true' then the list of the system tags is also returned. The default value is 'false'"
+          type: boolean
+          default: false
+        }
+        filter {
+          description: "Filter on entities to collect tags from"
+          type: object
+          properties {
+            system_tags {
+              description: "The list of system tag values to filter by. Use 'null' value to specify empty tags. Use '__Snot' value to specify that the following value should be excluded"
+              type: array
+              items {type: string}
+            }
+          }
+        }
+      }
+    }
+    response {
+      type: object
+      properties {
+        tags {
+          description: "The list of unique tag values"
+          type: array
+          items {type: string}
+        }
+        system_tags {
+          description: "The list of unique system tag values. Returned only if 'include_system' is set to 'true' in the request"
+          type: array
+          items {type: string}
+        }
+      }
+    }
+  }
+}

server/schema/services/server.conf

@@ -3,6 +3,25 @@ _default {
     internal: true
     allow_roles: ["root", "system"]
 }
+get_stats {
+    "2.1" {
+        description: "Get the server collected statistics."
+        request {
+            type: object
+            properties {
+                interval {
+                    description: "The period for statistics collection in seconds."
+                    type: long
+                }
+            }
+        }
+        response {
+            type: object
+            properties: {
+            }
+        }
+    }
+}
 config {
     "2.1" {
         description: "Get server configuration. Secure section is not returned."
@@ -50,6 +69,17 @@ info {
             }
         }
     }
+    "2.8": ${info."2.1"} {
+        response {
+            type: object
+            properties {
+                uid {
+                    description: "Server UID"
+                    type: string
+                }
+            }
+        }
+    }
 }
 endpoints {
     "2.1" {
@@ -66,3 +96,44 @@ endpoints {
         }
     }
 }
+report_stats_option {
+    allow_roles = [ "*" ]
+    "2.4" {
+        description: "Get or set the report statistics option per-company"
+        request {
+            type: object
+            properties {
+                enabled {
+                    description: "If provided, sets the report statistics option (true/false)"
+                    type: boolean
+                }
+            }
+        }
+        response {
+            type: object
+            properties {
+                enabled {
+                    description: "Returns the current report stats option value"
+                    type: boolean
+                }
+                enabled_time {
+                    description: "If enabled, returns the time at which option was enabled"
+                    type: string
+                    format: date-time
+                }
+                enabled_version {
+                    description: "If enabled, returns the server version at the time option was enabled"
+                    type: string
+                }
+                enabled_user {
+                    description: "If enabled, returns Id of the user who enabled the option"
+                    type: string
+                }
+                current_version {
+                    description: "Returns the current server version"
+                    type: string
+                }
+            }
+        }
+    }
+}

server/schema/services/tasks.conf

@@ -254,6 +254,15 @@ _definitions {
         enum: [
             training
             testing
+            inference
+            data_processing
+            application
+            monitor
+            controller
+            optimizer
+            service
+            qc
+            custom
         ]
     }
     last_metrics_event {
@@ -475,7 +484,11 @@ get_all {
                     minimum: 1
                 }
                 order_by {
-                    description: "List of field names to order by. When search_text is used, '@text_score' can be used as a field representing the text score of returned documents. Use '-' prefix to specify descending order. Optional, recommended when using page"
+                    description: """List of field names to order by. When search_text is used,
+                    '@text_score' can be used as a field representing the text score of returned documents.
+                    Use '-' prefix to specify descending order. Optional, recommended when using page.
+                    If the first order field is a hyper parameter or metric then string values are ordered
+                    according to numeric ordering rules where applicable"""
                     type: array
                     items { type: string }
                 }
@@ -550,6 +563,89 @@ get_all {
         }
     }
 }
+get_types {
+    "2.8" {
+        description: "Get the list of task types used in the specified projects"
+        request {
+            type: object
+            properties {
+                projects {
+                    description: "The list of projects which tasks will be analyzed. If not passed or empty then all the company and public tasks will be analyzed"
+                    type: array
+                    items: {type: string}
+                }
+            }
+        }
+        response {
+            type: object
+            properties {
+                types {
+                    description: "Unique list of the task types used in the requested projects"
+                    type: array
+                    items: {type: string}
+                }
+            }
+        }
+    }
+}
+clone {
+    "2.5" {
+        description: "Clone an existing task"
+        request {
+            type: object
+            required: [ task ]
+            properties {
+                task {
+                    description: "ID of the task"
+                    type: string
+                }
+                new_task_name {
+                    description: "The name of the cloned task. If not provided then taken from the original task"
+                    type: string
+                }
+                new_task_comment {
+                    description: "The comment of the cloned task. If not provided then taken from the original task"
+                    type: string
+                }
+                new_task_tags {
+                    description: "The user-defined tags of the cloned task. If not provided then taken from the original task"
+                    type: array
+                    items { type: string }
+                }
+                new_task_system_tags {
+                    description: "The system tags of the cloned task. If not provided then empty"
+                    type: array
+                    items { type: string }
+                }
+                new_task_parent {
+                    description: "The parent of the cloned task. If not provided then taken from the original task"
+                    type: string
+                }
+                new_task_project {
+                    description: "The project of the cloned task. If not provided then taken from the original task"
+                    type: string
+                }
+                execution_overrides {
+                    description: "The execution params for the cloned task. The params not specified are taken from the original task"
+                    "$ref": "#/definitions/execution"
+                }
+                validate_references {
+                    description: "If set to 'false' then the task fields that are copied from the original task are not validated. The default is false."
+                    type: boolean
+                }
+            }
+        }
+        response {
+            type: object
+            properties {
+                id {
+                    description: "ID of the new task"
+                    type: string
+                }
+            }
+        }
+    }
+}
 create {
     "2.1" {
         description: "Create a new task"
@@ -847,6 +943,11 @@ reset {
             properties.force = ${_references.force_arg} {
                 description: "If not true, call fails if the task status is 'completed'"
             }
+            properties.clear_all {
+                description: "Clear script and execution sections completely"
+                type: boolean
+                default: false
+            }
         } ${_references.status_change_request}
         response {
             type: object
@@ -1304,4 +1405,40 @@ ping {
             additionalProperties: false
         }
     }
+}
+
+add_or_update_artifacts {
+    "2.6" {
+        description: """ Update an existing artifact (search by key/mode) or add a new one """
+        request {
+            type: object
+            required: [ task, artifacts ]
+            properties {
+                task {
+                    description: "Task ID"
+                    type: string
+                }
+                artifacts {
+                    description: "Artifacts to add or update"
+                    type: array
+                    items { "$ref": "#/definitions/artifact" }
+                }
+            }
+        }
+        response {
+            type: object
+            properties {
+                added {
+                    description: "Keys of artifacts added"
+                    type: array
+                    items { type: string }
+                }
+                updated {
+                    description: "Keys of artifacts updated"
+                    type: array
+                    items { type: string }
+                }
+            }
+        }
+    }
 }

server/schema/services/users.conf

@@ -145,6 +145,19 @@ get_all_ex {
     internal: true
     "2.1": ${get_all."2.1"} {
     }
+    "2.8": ${get_all."2.1"} {
+        request {
+            type: object
+            properties {
+                active_in_projects {
+                    description: "List of project IDs. If provided, return only users that were active in these projects. If empty list is provided, return users that were active in all projects"
+                    type: array
+                    items { type: string }
+                }
+            }
+        }
+    }
+
 }
 
 get_all {

server/server.py

@@ -1,3 +1,4 @@
+import atexit
 from argparse import ArgumentParser
 
 from flask import Flask, request, Response
@@ -7,15 +8,17 @@ from werkzeug.exceptions import BadRequest
 
 import database
 from apierrors.base import BaseError
+from bll.statistics.stats_reporter import StatisticsReporter
 from config import config
+from elastic.initialize import init_es_data
+from mongo.initialize import init_mongo_data
 from service_repo import ServiceRepo, APICall
 from service_repo.auth import AuthType
 from service_repo.errors import PathParsingError
 from timing_context import TimingContext
-from utilities import json
-from init_data import init_es_data, init_mongo_data
 from updates import check_updates_thread
-
+from utilities import json
+from utilities.threads_manager import ThreadsManager
 
 app = Flask(__name__, static_url_path="/static")
 CORS(app, **config.get("apiserver.cors"))
@@ -38,6 +41,14 @@ log.info(f"Exposed Services: {' '.join(ServiceRepo.endpoint_names())}")
 
 
 check_updates_thread.start()
+StatisticsReporter.start()
+
+
+def graceful_shutdown():
+    ThreadsManager.terminating = True
+
+
+atexit.register(graceful_shutdown)
 
 
 @app.before_first_request
@@ -57,7 +68,9 @@ def before_request():
         content, content_type = ServiceRepo.handle_call(call)
         headers = {}
         if call.result.filename:
-            headers["Content-Disposition"] = f"attachment; filename={call.result.filename}"
+            headers[
+                "Content-Disposition"
+            ] = f"attachment; filename={call.result.filename}"
 
         if call.result.headers:
             headers.update(call.result.headers)
@@ -71,7 +84,9 @@ def before_request():
                 if value is None:
                     response.set_cookie(key, "", expires=0)
                 else:
-                    response.set_cookie(key, value, **config.get("apiserver.auth.cookies"))
+                    response.set_cookie(
+                        key, value, **config.get("apiserver.auth.cookies")
+                    )
 
         return response
     except Exception as ex:

server/service_repo/apicall.py

@@ -21,6 +21,8 @@ JSON_CONTENT_TYPE = "application/json"
 class DataContainer(object):
     """ Data container that supports raw data (dict or a list of batched dicts) and a data model """
 
+    null_schema_validator: SchemaValidator = SchemaValidator(None)
+
     def __init__(self, data=None, batched_data=None):
         if data and batched_data:
             raise ValueError("data and batched data are not supported simultaneously")
@@ -28,7 +30,7 @@ class DataContainer(object):
         self._data = None
         self._data_model = None
         self._data_model_cls = None
-        self._schema_validator: SchemaValidator = SchemaValidator(None)
+        self._schema_validator: SchemaValidator = self.null_schema_validator
         # use setter to properly initialize data
         self.data = data
         self.batched_data = batched_data
@@ -255,6 +257,7 @@ class MissingIdentity(Exception):
 class APICall(DataContainer):
     HEADER_AUTHORIZATION = "Authorization"
     HEADER_REAL_IP = "X-Real-IP"
+    HEADER_FORWARDED_FOR = "X-Forwarded-For"
     """ Standard headers """
 
     _transaction_headers = ("X-Trains-Trx",)
@@ -382,8 +385,13 @@ class APICall(DataContainer):
 
     @property
     def real_ip(self):
-        real_ip = self.get_header(self.HEADER_REAL_IP)
-        return real_ip or self._remote_addr or "untrackable"
+        """ Obtain visitor's IP address """
+        return (
+                self.get_header(self.HEADER_FORWARDED_FOR)
+                or self.get_header(self.HEADER_REAL_IP)
+                or self._remote_addr
+                or "untrackable"
+        )
 
     @property
     def failed(self):

server/service_repo/auth/fixed_user.py

@@ -5,27 +5,45 @@ from typing import Sequence, TypeVar
 import attr
 
 from config import config
+from config.info import get_default_company
 
 T = TypeVar("T", bound="FixedUser")
 
 
+class FixedUsersError(Exception):
+    pass
+
+
 @attr.s(auto_attribs=True)
 class FixedUser:
     username: str
     password: str
     name: str
+    company: str = get_default_company()
 
     def __attrs_post_init__(self):
-        self.user_id = hashlib.md5(f"{self.username}:{self.password}".encode()).hexdigest()
+        self.user_id = hashlib.md5(f"{self.company}:{self.username}".encode()).hexdigest()
 
     @classmethod
     def enabled(cls):
         return config.get("apiserver.auth.fixed_users.enabled", False)
 
+    @classmethod
+    def validate(cls):
+        if not cls.enabled():
+            return
+        users = cls.from_config()
+        if len({user.username for user in users}) < len(users):
+            raise FixedUsersError(
+                "Duplicate user names found in fixed users configuration"
+            )
+
     @classmethod
     @lru_cache()
     def from_config(cls) -> Sequence[T]:
-        return [cls(**user) for user in config.get("apiserver.auth.fixed_users.users", [])]
+        return [
+            cls(**user) for user in config.get("apiserver.auth.fixed_users.users", [])
+        ]
 
     @classmethod
     @lru_cache()

server/service_repo/endpoint.py

@@ -1,5 +1,6 @@
+from enum import Enum
 from typing import Callable, Sequence, Text
-
+from boltons.iterutils import remap
 from jsonmodels import models
 from jsonmodels.errors import FieldNotSupported
 
@@ -87,7 +88,14 @@ class Endpoint(object):
             Provided data_model schema if available
             """
             try:
-                return data_model.to_json_schema()
+                res = data_model.to_json_schema()
+
+                def visit(path, key, value):
+                    if isinstance(value, Enum):
+                        value = str(value)
+                    return key, value
+
+                return remap(res, visit=visit)
             except (FieldNotSupported, TypeError):
                 return str(data_model.__name__)
 

server/service_repo/service_repo.py

@@ -9,6 +9,7 @@ import jsonmodels.models
 import timing_context
 from apierrors import APIError
 from apierrors.errors.bad_request import RequestPathHasInvalidVersion
+from api_version import __version__ as _api_version_
 from config import config
 from service_repo.base import PartialVersion
 from .apicall import APICall
@@ -34,7 +35,7 @@ class ServiceRepo(object):
     """If the check is set, parsing will fail for endpoint request with the version that is grater than the current 
     maximum """
 
-    _max_version = PartialVersion("2.4")
+    _max_version = PartialVersion(".".join(_api_version_.split(".")[:2]))
     """ Maximum version number (the highest min_version value across all endpoints) """
 
     _endpoint_exp = (
@@ -166,7 +167,7 @@ class ServiceRepo(object):
             return
 
         assert isinstance(endpoint, Endpoint)
-        call.actual_endpoint_version: PartialVersion = endpoint.min_version
+        call.actual_endpoint_version = endpoint.min_version
         call.requires_authorization = endpoint.authorize
         return endpoint
 

server/service_repo/validators.py

@@ -52,7 +52,7 @@ def validate_all(call: APICall, endpoint: Endpoint):
 
 def validate_role(endpoint, call):
     try:
-        if not endpoint.allows(call.identity.role):
+        if endpoint.authorize and not endpoint.allows(call.identity.role):
             raise errors.forbidden.RoleNotAllowed(role=call.identity.role, allowed=endpoint.allow_roles)
     except MissingIdentity:
         pass

server/services/events.py

@@ -2,12 +2,16 @@ import itertools
 from collections import defaultdict
 from operator import itemgetter
 
-import six
-
 from apierrors import errors
 from apimodels.events import (
     MultiTaskScalarMetricsIterHistogramRequest,
     ScalarMetricsIterHistogramRequest,
+    DebugImagesRequest,
+    DebugImageResponse,
+    MetricEvents,
+    IterationEvents,
+    TaskMetricsRequest,
+    LogEventsRequest,
 )
 from bll.event import EventBLL
 from bll.event.event_metrics import EventMetrics
@@ -23,10 +27,10 @@ event_bll = EventBLL()
 def add(call: APICall, company_id, req_model):
     data = call.data.copy()
     allow_locked = data.pop("allow_locked", False)
-    added, batch_errors = event_bll.add_events(
+    added, err_count, err_info = event_bll.add_events(
         company_id, [data], call.worker, allow_locked_tasks=allow_locked
     )
-    call.result.data = dict(added=added, errors=len(batch_errors))
+    call.result.data = dict(added=added, errors=err_count, errors_info=err_info)
     call.kpis["events"] = 1
 
 
@@ -36,13 +40,13 @@ def add_batch(call: APICall, company_id, req_model):
     if events is None or len(events) == 0:
         raise errors.bad_request.BatchContainsNoItems()
 
-    added, batch_errors = event_bll.add_events(company_id, events, call.worker)
-    call.result.data = dict(added=added, errors=len(batch_errors))
+    added, err_count, err_info = event_bll.add_events(company_id, events, call.worker)
+    call.result.data = dict(added=added, errors=err_count, errors_info=err_info)
     call.kpis["events"] = len(events)
 
 
 @endpoint("events.get_task_log", required_fields=["task"])
-def get_task_log(call, company_id, req_model):
+def get_task_log_v1_5(call, company_id, req_model):
     task_id = call.data["task"]
     task_bll.assert_exists(company_id, task_id, allow_public=True)
     order = call.data.get("order") or "desc"
@@ -90,6 +94,29 @@ def get_task_log_v1_7(call, company_id, req_model):
     )
 
 
+# uncomment this once the front end is ready
+# @endpoint("events.get_task_log", min_version="2.7", request_data_model=LogEventsRequest)
+# def get_task_log(call, company_id, req_model: LogEventsRequest):
+#     task_id = req_model.task
+#     task_bll.assert_exists(company_id, task_id, allow_public=True)
+#
+#     res = event_bll.log_events_iterator.get_task_events(
+#         company_id=company_id,
+#         task_id=task_id,
+#         batch_size=req_model.batch_size,
+#         navigate_earlier=req_model.navigate_earlier,
+#         refresh=req_model.refresh,
+#         state_id=req_model.scroll_id,
+#     )
+#
+#     call.result.data = dict(
+#         events=res.events,
+#         returned=len(res.events),
+#         total=res.total_events,
+#         scroll_id=res.next_scroll_id,
+#     )
+
+
 @endpoint("events.download_task_log", required_fields=["task"])
 def download_task_log(call, company_id, req_model):
     task_id = call.data["task"]
@@ -211,7 +238,7 @@ def vector_metrics_iter_histogram(call, company_id, req_model):
 @endpoint("events.get_task_events", required_fields=["task"])
 def get_task_events(call, company_id, _):
     task_id = call.data["task"]
-    batch_size = call.data.get("batch_size")
+    batch_size = call.data.get("batch_size", 500)
     event_type = call.data.get("event_type")
     scroll_id = call.data.get("scroll_id")
     order = call.data.get("order") or "asc"
@@ -299,7 +326,7 @@ def multi_task_scalar_metrics_iter_histogram(
     call, company_id, req_model: MultiTaskScalarMetricsIterHistogramRequest
 ):
     task_ids = req_model.tasks
-    if isinstance(task_ids, six.string_types):
+    if isinstance(task_ids, str):
         task_ids = [s.strip() for s in task_ids.split(",")]
     # Note, bll already validates task ids as it needs their names
     call.result.data = dict(
@@ -394,7 +421,7 @@ def get_task_plots_v1_7(call, company_id, req_model):
 
     task_bll.assert_exists(call.identity.company, task_id, allow_public=True)
     # events, next_scroll_id, total_events = event_bll.get_task_events(
-    #     company_id, task_id,
+    #     company, task_id,
     #     event_type="plot",
     #     sort=[{"iter": {"order": "desc"}}],
     #     last_iter_count=iters,
@@ -453,7 +480,7 @@ def get_debug_images_v1_7(call, company_id, req_model):
 
     task_bll.assert_exists(call.identity.company, task_id, allow_public=True)
     # events, next_scroll_id, total_events = event_bll.get_task_events(
-    #     company_id, task_id,
+    #     company, task_id,
     #     event_type="training_debug_image",
     #     sort=[{"iter": {"order": "desc"}}],
     #     last_iter_count=iters,
@@ -481,7 +508,7 @@ def get_debug_images_v1_7(call, company_id, req_model):
 
 
 @endpoint("events.debug_images", min_version="1.8", required_fields=["task"])
-def get_debug_images(call, company_id, req_model):
+def get_debug_images_v1_8(call, company_id, req_model):
     task_id = call.data["task"]
     iters = call.data.get("iters") or 1
     scroll_id = call.data.get("scroll_id")
@@ -507,6 +534,53 @@ def get_debug_images(call, company_id, req_model):
     )
 
 
+@endpoint(
+    "events.debug_images",
+    min_version="2.7",
+    request_data_model=DebugImagesRequest,
+    response_data_model=DebugImageResponse,
+)
+def get_debug_images(call, company_id, req_model: DebugImagesRequest):
+    tasks = set(m.task for m in req_model.metrics)
+    task_bll.assert_exists(call.identity.company, task_ids=tasks, allow_public=True)
+    result = event_bll.debug_images_iterator.get_task_events(
+        company_id=company_id,
+        metrics=[(m.task, m.metric) for m in req_model.metrics],
+        iter_count=req_model.iters,
+        navigate_earlier=req_model.navigate_earlier,
+        refresh=req_model.refresh,
+        state_id=req_model.scroll_id,
+    )
+
+    call.result.data_model = DebugImageResponse(
+        scroll_id=result.next_scroll_id,
+        metrics=[
+            MetricEvents(
+                task=task,
+                metric=metric,
+                iterations=[
+                    IterationEvents(iter=iteration["iter"], events=iteration["events"])
+                    for iteration in iterations
+                ],
+            )
+            for (task, metric, iterations) in result.metric_events
+        ],
+    )
+
+
+@endpoint("events.get_task_metrics", request_data_model=TaskMetricsRequest)
+def get_tasks_metrics(call: APICall, company_id, req_model: TaskMetricsRequest):
+    task_bll.assert_exists(
+        call.identity.company, task_ids=req_model.tasks, allow_public=True
+    )
+    res = event_bll.metrics.get_tasks_metrics(
+        company_id, task_ids=req_model.tasks, event_type=req_model.event_type
+    )
+    call.result.data = {
+        "metrics": [{"task": task, "metrics": metrics} for (task, metrics) in res]
+    }
+
+
 @endpoint("events.delete_for_task", required_fields=["task"])
 def delete_for_task(call, company_id, req_model):
     task_id = call.data["task"]

server/services/models.py

@@ -12,6 +12,7 @@ from apimodels.models import (
     PublishModelResponse,
     ModelTaskPublishResponse,
 )
+from bll.organization import OrgBLL
 from bll.task import TaskBLL
 from config import config
 from database.errors import translate_errors_context
@@ -29,51 +30,34 @@ from services.utils import conform_tag_fields, conform_output_tags
 from timing_context import TimingContext
 
 log = config.logger(__file__)
-get_all_query_options = Model.QueryParameterOptions(
-    pattern_fields=("name", "comment"),
-    fields=("ready",),
-    list_fields=(
-        "tags",
-        "system_tags",
-        "framework",
-        "uri",
-        "id",
-        "project",
-        "task",
-        "parent",
-    ),
-)
+org_bll = OrgBLL()
 
 
 @endpoint("models.get_by_id", required_fields=["model"])
-def get_by_id(call):
-    assert isinstance(call, APICall)
+def get_by_id(call: APICall, company_id, _):
     model_id = call.data["model"]
 
     with translate_errors_context():
         models = Model.get_many(
-            company=call.identity.company,
+            company=company_id,
             query_dict=call.data,
             query=Q(id=model_id),
             allow_public=True,
         )
         if not models:
             raise errors.bad_request.InvalidModelId(
-                "no such public or company model",
-                id=model_id,
-                company=call.identity.company,
+                "no such public or company model", id=model_id, company=company_id,
             )
         conform_output_tags(call, models[0])
         call.result.data = {"model": models[0]}
 
 
 @endpoint("models.get_by_task_id", required_fields=["task"])
-def get_by_task_id(call):
-    assert isinstance(call, APICall)
+def get_by_task_id(call: APICall, company_id, _):
     task_id = call.data["task"]
 
     with translate_errors_context():
-        query = dict(id=task_id, company=call.identity.company)
+        query = dict(id=task_id, company=company_id)
         task = Task.get(_only=["output"], **query)
         if not task:
             raise errors.bad_request.InvalidTaskId(**query)
@@ -84,13 +68,11 @@ def get_by_task_id(call):
 
         model_id = task.output.model
         model = Model.objects(
-            Q(id=model_id) & get_company_or_none_constraint(call.identity.company)
+            Q(id=model_id) & get_company_or_none_constraint(company_id)
         ).first()
         if not model:
             raise errors.bad_request.InvalidModelId(
-                "no such public or company model",
-                id=model_id,
-                company=call.identity.company,
+                "no such public or company model", id=model_id, company=company_id,
             )
         model_dict = model.to_proper_dict()
         conform_output_tags(call, model_dict)
@@ -98,31 +80,27 @@ def get_by_task_id(call):
 
 
 @endpoint("models.get_all_ex", required_fields=[])
-def get_all_ex(call: APICall):
+def get_all_ex(call: APICall, company_id, _):
     conform_tag_fields(call, call.data)
     with translate_errors_context():
         with TimingContext("mongo", "models_get_all_ex"):
             models = Model.get_many_with_join(
-                company=call.identity.company,
-                query_dict=call.data,
-                allow_public=True,
-                query_options=get_all_query_options,
+                company=company_id, query_dict=call.data, allow_public=True
             )
         conform_output_tags(call, models)
         call.result.data = {"models": models}
 
 
 @endpoint("models.get_all", required_fields=[])
-def get_all(call: APICall):
+def get_all(call: APICall, company_id, _):
     conform_tag_fields(call, call.data)
     with translate_errors_context():
         with TimingContext("mongo", "models_get_all"):
             models = Model.get_many(
-                company=call.identity.company,
+                company=company_id,
                 parameters=call.data,
                 query_dict=call.data,
                 allow_public=True,
-                query_options=get_all_query_options,
             )
         conform_output_tags(call, models)
         call.result.data = {"models": models}
@@ -146,13 +124,18 @@ create_fields = {
 
 def parse_model_fields(call, valid_fields):
     fields = parse_from_call(call.data, valid_fields, Model.get_fields())
-    conform_tag_fields(call, fields)
+    conform_tag_fields(call, fields, validate=True)
     return fields
 
 
+def _update_org_tags(company, fields: dict):
+    org_bll.update_org_tags(
+        company, tags=fields.get("tags"), system_tags=fields.get("system_tags")
+    )
+
+
 @endpoint("models.update_for_task", required_fields=["task"])
-def update_for_task(call, company_id, _):
-    assert isinstance(call, APICall)
+def update_for_task(call: APICall, company_id, _):
     task_id = call.data["task"]
     uri = call.data.get("uri")
     iteration = call.data.get("iteration")
@@ -195,7 +178,9 @@ def update_for_task(call, company_id, _):
 
             if task.output and task.output.model:
                 # model exists, update
-                res = _update_model(call, model_id=task.output.model).to_struct()
+                res = _update_model(
+                    call, company_id, model_id=task.output.model
+                ).to_struct()
                 res.update({"id": task.output.model, "created": False})
                 call.result.data = res
                 return
@@ -218,6 +203,7 @@ def update_for_task(call, company_id, _):
                 **fields,
             )
             model.save()
+            _update_org_tags(company_id, fields)
 
         TaskBLL.update_statistics(
             task_id=task_id,
@@ -234,48 +220,46 @@ def update_for_task(call, company_id, _):
     request_data_model=CreateModelRequest,
     response_data_model=CreateModelResponse,
 )
-def create(call, company, req_model):
-    assert isinstance(call, APICall)
-    assert isinstance(req_model, CreateModelRequest)
-    identity = call.identity
+def create(call: APICall, company_id, req_model: CreateModelRequest):
 
     if req_model.public:
-        company = ""
+        company_id = ""
 
     with translate_errors_context():
 
         project = req_model.project
         if project:
-            validate_id(Project, company=company, project=project)
+            validate_id(Project, company=company_id, project=project)
 
         task = req_model.task
         req_data = req_model.to_struct()
         if task:
-            validate_task(call, req_data)
+            validate_task(company_id, req_data)
 
         fields = filter_fields(Model, req_data)
-        conform_tag_fields(call, fields)
+        conform_tag_fields(call, fields, validate=True)
 
         # create and save model
         model = Model(
             id=database.utils.id(),
-            user=identity.user,
-            company=company,
+            user=call.identity.user,
+            company=company_id,
             created=datetime.utcnow(),
             **fields,
         )
         model.save()
+        _update_org_tags(company_id, fields)
 
         call.result.data_model = CreateModelResponse(id=model.id, created=True)
 
 
-def prepare_update_fields(call, fields):
+def prepare_update_fields(call, company_id, fields: dict):
     fields = fields.copy()
     if "uri" in fields:
         # clear UI cache if URI is provided (model updated)
         fields["ui_cache"] = fields.pop("ui_cache", {})
     if "task" in fields:
-        validate_task(call, fields)
+        validate_task(company_id, fields)
 
     if "labels" in fields:
         labels = fields["labels"]
@@ -290,33 +274,36 @@ def prepare_update_fields(call, fields):
 
         invalid_keys = find_other_types(labels.keys(), str)
         if invalid_keys:
-            raise errors.bad_request.ValidationError("labels keys must be strings", keys=invalid_keys)
+            raise errors.bad_request.ValidationError(
+                "labels keys must be strings", keys=invalid_keys
+            )
 
         invalid_values = find_other_types(labels.values(), int)
         if invalid_values:
-            raise errors.bad_request.ValidationError("labels values must be integers", values=invalid_values)
+            raise errors.bad_request.ValidationError(
+                "labels values must be integers", values=invalid_values
+            )
 
-    conform_tag_fields(call, fields)
+    conform_tag_fields(call, fields, validate=True)
     return fields
 
 
-def validate_task(call, fields):
-    Task.get_for_writing(company=call.identity.company, id=fields["task"], _only=["id"])
+def validate_task(company_id, fields: dict):
+    Task.get_for_writing(company=company_id, id=fields["task"], _only=["id"])
 
 
 @endpoint("models.edit", required_fields=["model"], response_data_model=UpdateResponse)
-def edit(call: APICall):
-    identity = call.identity
+def edit(call: APICall, company_id, _):
     model_id = call.data["model"]
 
     with translate_errors_context():
-        query = dict(id=model_id, company=identity.company)
+        query = dict(id=model_id, company=company_id)
         model = Model.objects(**query).first()
         if not model:
             raise errors.bad_request.InvalidModelId(**query)
 
         fields = parse_model_fields(call, create_fields)
-        fields = prepare_update_fields(call, fields)
+        fields = prepare_update_fields(call, company_id, fields)
 
         for key in fields:
             field = getattr(model, key, None)
@@ -331,47 +318,44 @@ def edit(call: APICall):
                 fields[key] = d
 
         iteration = call.data.get("iteration")
-        task_id = model.task or fields.get('task')
+        task_id = model.task or fields.get("task")
         if task_id and iteration is not None:
             TaskBLL.update_statistics(
-                task_id=task_id,
-                company_id=identity.company,
-                last_iteration_max=iteration,
+                task_id=task_id, company_id=company_id, last_iteration_max=iteration,
             )
 
         if fields:
             updated = model.update(upsert=False, **fields)
+            if updated:
+                _update_org_tags(company_id, fields)
             conform_output_tags(call, fields)
             call.result.data_model = UpdateResponse(updated=updated, fields=fields)
         else:
             call.result.data_model = UpdateResponse(updated=0)
 
 
-def _update_model(call: APICall, model_id=None):
-    identity = call.identity
+def _update_model(call: APICall, company_id, model_id=None):
     model_id = model_id or call.data["model"]
 
     with translate_errors_context():
         # get model by id
-        query = dict(id=model_id, company=identity.company)
+        query = dict(id=model_id, company=company_id)
         model = Model.objects(**query).first()
         if not model:
             raise errors.bad_request.InvalidModelId(**query)
 
-        data = prepare_update_fields(call, call.data)
+        data = prepare_update_fields(call, company_id, call.data)
 
         task_id = data.get("task")
         iteration = data.get("iteration")
         if task_id and iteration is not None:
             TaskBLL.update_statistics(
-                task_id=task_id,
-                company_id=identity.company,
-                last_iteration_max=iteration,
+                task_id=task_id, company_id=company_id, last_iteration_max=iteration,
             )
 
-        updated_count, updated_fields = Model.safe_update(
-            call.identity.company, model.id, data
-        )
+        updated_count, updated_fields = Model.safe_update(company_id, model.id, data)
+        if updated_count:
+            _update_org_tags(company_id, updated_fields)
         conform_output_tags(call, updated_fields)
         return UpdateResponse(updated=updated_count, fields=updated_fields)
 
@@ -379,8 +363,8 @@ def _update_model(call: APICall, model_id=None):
 @endpoint(
     "models.update", required_fields=["model"], response_data_model=UpdateResponse
 )
-def update(call):
-    call.result.data_model = _update_model(call)
+def update(call, company_id, _):
+    call.result.data_model = _update_model(call, company_id)
 
 
 @endpoint(
@@ -388,31 +372,29 @@ def update(call):
     request_data_model=PublishModelRequest,
     response_data_model=PublishModelResponse,
 )
-def set_ready(call: APICall, company, req_model: PublishModelRequest):
+def set_ready(call: APICall, company_id, req_model: PublishModelRequest):
     updated, published_task_data = TaskBLL.model_set_ready(
         model_id=req_model.model,
-        company_id=company,
+        company_id=company_id,
         publish_task=req_model.publish_task,
-        force_publish_task=req_model.force_publish_task
+        force_publish_task=req_model.force_publish_task,
     )
 
     call.result.data_model = PublishModelResponse(
         updated=updated,
-        published_task=ModelTaskPublishResponse(
-            **published_task_data
-        ) if published_task_data else None
+        published_task=ModelTaskPublishResponse(**published_task_data)
+        if published_task_data
+        else None,
     )
 
 
 @endpoint("models.delete", required_fields=["model"])
-def update(call):
-    assert isinstance(call, APICall)
-    identity = call.identity
+def update(call: APICall, company_id, _):
     model_id = call.data["model"]
     force = call.data.get("force", False)
 
     with translate_errors_context():
-        query = dict(id=model_id, company=identity.company)
+        query = dict(id=model_id, company=company_id)
         model = Model.objects(**query).only("id", "task").first()
         if not model:
             raise errors.bad_request.InvalidModelId(**query)
@@ -445,4 +427,6 @@ def update(call):
                 )
 
         del_count = Model.objects(**query).delete()
+        if del_count:
+            org_bll.update_org_tags(company_id, reset=True)
         call.result.data = dict(deleted=del_count > 0)

server/services/organization.py

@@ -0,0 +1,13 @@
+from apimodels.organization import TagsRequest
+from bll.organization import OrgBLL
+from service_repo import endpoint, APICall
+
+org_bll = OrgBLL()
+
+
+@endpoint("organization.get_tags", request_data_model=TagsRequest)
+def get_tags(call: APICall, company, request: TagsRequest):
+    filter_ = request.filter.system_tags if request.filter else None
+    call.result.data = org_bll.get_tags(
+        company, include_system=request.include_system, filter_=filter_
+    )

server/services/projects.py

@@ -33,8 +33,7 @@ create_fields = {
 }
 
 get_all_query_options = Project.QueryParameterOptions(
-    pattern_fields=("name", "description"),
-    list_fields=("tags", "system_tags", "id"),
+    pattern_fields=("name", "description"), list_fields=("tags", "system_tags", "id"),
 )
 
 
@@ -58,10 +57,10 @@ def get_by_id(call):
         call.result.data = {"project": project_dict}
 
 
-def make_projects_get_all_pipelines(project_ids, specific_state=None):
+def make_projects_get_all_pipelines(company_id, project_ids, specific_state=None):
     archived = EntityVisibility.archived.value
 
-    def ensure_system_tags():
+    def ensure_valid_fields():
         """
         Make sure system tags is always an array (required by subsequent $in in archived_tasks_cond
         """
@@ -73,14 +72,20 @@ def make_projects_get_all_pipelines(project_ids, specific_state=None):
                         "then": [],
                         "else": "$system_tags",
                     }
-                }
+                },
+                "status": {"$ifNull": ["$status", "unknown"]},
             }
         }
 
     status_count_pipeline = [
         # count tasks per project per status
-        {"$match": {"project": {"$in": project_ids}}},
-        ensure_system_tags(),
+        {
+            "$match": {
+                "company": {"$in": [None, "", company_id]},
+                "project": {"$in": project_ids},
+            }
+        },
+        ensure_valid_fields(),
         {
             "$group": {
                 "_id": {
@@ -149,11 +154,12 @@ def make_projects_get_all_pipelines(project_ids, specific_state=None):
         # only count run time for these types of tasks
         {
             "$match": {
-                "type": {"$in": ["training", "testing", "annotation"]},
+                "type": {"$in": ["training", "testing"]},
+                "company": {"$in": [None, "", company_id]},
                 "project": {"$in": project_ids},
             }
         },
-        ensure_system_tags(),
+        ensure_valid_fields(),
         {
             # for each project
             "$group": group_step
@@ -192,7 +198,7 @@ def get_all_ex(call: APICall):
 
         ids = [project["id"] for project in projects]
         status_count_pipeline, runtime_pipeline = make_projects_get_all_pipelines(
-            ids, specific_state=specific_state
+            call.identity.company, ids, specific_state=specific_state
         )
 
         default_counts = dict.fromkeys(get_options(TaskStatus), 0)
@@ -202,7 +208,7 @@ def get_all_ex(call: APICall):
 
         status_count = defaultdict(lambda: {})
         key = itemgetter(EntityVisibility.archived.value)
-        for result in Task.aggregate(*status_count_pipeline):
+        for result in Task.aggregate(status_count_pipeline):
             for k, group in groupby(sorted(result["counts"], key=key), key):
                 section = (
                     EntityVisibility.archived if k else EntityVisibility.active
@@ -216,7 +222,7 @@ def get_all_ex(call: APICall):
 
         runtime = {
             result["_id"]: {k: v for k, v in result.items() if k != "_id"}
-            for result in Task.aggregate(*runtime_pipeline)
+            for result in Task.aggregate(runtime_pipeline)
         }
 
     def safe_get(obj, path, default=None):
@@ -268,7 +274,7 @@ def create(call):
 
     with translate_errors_context():
         fields = parse_from_call(call.data, create_fields, Project.get_fields())
-        conform_tag_fields(call, fields)
+        conform_tag_fields(call, fields, validate=True)
         now = datetime.utcnow()
         project = Project(
             id=database.utils.id(),
@@ -305,7 +311,7 @@ def update(call: APICall):
         fields = parse_from_call(
             call.data, create_fields, Project.get_fields(), discard_none_values=False
         )
-        conform_tag_fields(call, fields)
+        conform_tag_fields(call, fields, validate=True)
         fields["last_update"] = datetime.utcnow()
         with TimingContext("mongo", "projects_update"):
             updated = project.update(upsert=False, **fields)

server/services/queues.py

@@ -58,7 +58,9 @@ def get_all(call: APICall):
 
 @endpoint("queues.create", min_version="2.4", request_data_model=CreateRequest)
 def create(call: APICall, company_id, request: CreateRequest):
-    tags, system_tags = conform_tags(call, request.tags, request.system_tags)
+    tags, system_tags = conform_tags(
+        call, request.tags, request.system_tags, validate=True
+    )
     queue = queue_bll.create(
         company_id=company_id, name=request.name, tags=tags, system_tags=system_tags
     )
@@ -73,7 +75,7 @@ def create(call: APICall, company_id, request: CreateRequest):
 )
 def update(call: APICall, company_id, req_model: UpdateRequest):
     data = call.data_model_for_partial_update
-    conform_tag_fields(call, data)
+    conform_tag_fields(call, data, validate=True)
     updated, fields = queue_bll.update(
         company_id=company_id, queue_id=req_model.queue, **data
     )
@@ -212,7 +214,9 @@ def get_queue_metrics(
                 dates=data["date"],
                 avg_waiting_times=data["avg_waiting_time"],
                 queue_lengths=data["queue_length"],
-            ) if data else QueueMetrics(queue=queue)
+            )
+            if data
+            else QueueMetrics(queue=queue)
             for queue, data in queue_dicts.items()
         ]
     )

server/services/server/__init__.py

@@ -1,10 +1,26 @@
+from datetime import datetime
+
 from pyhocon.config_tree import NoneValue
 
+from apierrors import errors
+from apimodels.server import ReportStatsOptionRequest, ReportStatsOptionResponse
+from bll.statistics.stats_reporter import StatisticsReporter
 from config import config
 from config.info import get_version, get_build_number, get_commit_number
+from database.errors import translate_errors_context
+from database.model import Company
+from database.model.company import ReportStatsOption
+from database.model.settings import Settings, SettingKeys
 from service_repo import ServiceRepo, APICall, endpoint
 
 
+@endpoint("server.get_stats")
+def get_stats(call: APICall):
+    call.result.data = StatisticsReporter.get_statistics(
+        company_id=call.identity.company
+    )
+
+
 @endpoint("server.config")
 def get_config(call: APICall):
     path = call.data.get("path")
@@ -43,3 +59,42 @@ def info(call: APICall):
         "build": get_build_number(),
         "commit": get_commit_number(),
     }
+
+
+@endpoint("server.info", min_version="2.8")
+def info_2_8(call: APICall):
+    info(call)
+    call.result.data["uid"] = Settings.get_by_key(SettingKeys.server__uuid)
+
+
+@endpoint(
+    "server.report_stats_option",
+    request_data_model=ReportStatsOptionRequest,
+    response_data_model=ReportStatsOptionResponse,
+)
+def report_stats(call: APICall, company: str, request: ReportStatsOptionRequest):
+    if not StatisticsReporter.supported:
+        result = ReportStatsOptionResponse(supported=False)
+    else:
+        enabled = request.enabled
+        with translate_errors_context():
+            query = Company.objects(id=company)
+            if enabled is None:
+                stats_option = query.first().defaults.stats_option
+            else:
+                stats_option = ReportStatsOption(
+                    enabled=enabled,
+                    enabled_time=datetime.utcnow(),
+                    enabled_version=get_version(),
+                    enabled_user=call.identity.user,
+                )
+                updated = query.update(defaults__stats_option=stats_option)
+                if not updated:
+                    raise errors.server_error.InternalError(
+                        f"Failed setting report_stats to {enabled}"
+                    )
+        data = stats_option.to_mongo()
+        data["current_version"] = get_version()
+        result = ReportStatsOptionResponse(**data)
+
+    call.result.data_model = result