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Upgrade to v0.12
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allegroai
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README.md
163
README.md
@ -11,7 +11,7 @@
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The **trains-server** is the backend service infrastructure for [TRAINS](https://github.com/allegroai/trains).
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It allows multiple users to collaborate and manage their experiments.
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By default, TRAINS is set up to work with the TRAINS demo server, which is open to anyone and resets periodically.
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By default, TRAINS is set up to work with the TRAINS demo server, which is open to anyone and resets periodically.
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In order to host your own server, you will need to install **trains-server** and point TRAINS to it.
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**trains-server** contains the following components:
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@ -23,9 +23,9 @@ In order to host your own server, you will need to install **trains-server** and
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* Locally-hosted file server for storing images and models making them easily accessible using the Web-App
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You can quickly setup your **trains-server** using:
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- [Docker Installation](#installation)
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- [Docker Installation](#installation)
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- Pre-built Amazon [AWS image](#aws)
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- [Kubernetes Helm](https://github.com/allegroai/trains-server-helm#trains-server-for-kubernetes-clusters-using-helm)
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- [Kubernetes Helm](https://github.com/allegroai/trains-server-helm#trains-server-for-kubernetes-clusters-using-helm)
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or manual [Kubernetes installation](https://github.com/allegroai/trains-server-k8s#trains-server-for-kubernetes-clusters)
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@ -36,80 +36,81 @@ You can quickly setup your **trains-server** using:
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**trains-server** has two supported configurations:
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- Single IP (domain) with the following open ports
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- Web application on port 8080
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- Web application on port 8080
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- API service on port 8008
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- File storage service on port 8081
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- Sub-Domain configuration with default http/s ports (80 or 443)
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- Web application on sub-domain: app.\*.\*
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- API service on sub-domain: api.\*.\*
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- File storage service on sub-domain: files.\*.\*
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## Install / Upgrade - AWS <a name="aws"></a>
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Use one of our pre-installed Amazon Machine Images for easy deployment in AWS.
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Use one of our pre-installed Amazon Machine Images for easy deployment in AWS.
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For details and instructions, see [TRAINS-server: AWS pre-installed images](docs/install_aws.md).
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## Docker Installation - Linux, Mac OS X <a name="installation"></a>
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Use our pre-built Docker image for easy deployment in Linux and Mac OS X.
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Use our pre-built Docker image for easy deployment in Linux and Mac OS X.
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For Windows, we recommend installing our pre-built Docker image on a Linux virtual machine.
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Latest docker images can be found [here](https://hub.docker.com/r/allegroai/trains).
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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))
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Make sure port 8080/8081/8008 are available for the `trains-server` services
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Make sure port 8080/8081/8008 are available for the `trains-server` services
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Increase vm.max_map_count for `ElasticSearch` docker
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```bash
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echo "vm.max_map_count=262144" > /tmp/99-trains.conf
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sudo mv /tmp/99-trains.conf /etc/sysctl.d/99-trains.conf
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sudo sysctl -w vm.max_map_count=262144
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sudo service docker restart
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```
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```
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1. Create local directories for the databases and storage.
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```bash
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sudo mkdir -p /opt/trains/data/elastic
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sudo mkdir -p /opt/trains/data/mongo/db
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sudo mkdir -p /opt/trains/data/mongo/configdb
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sudo mkdir -p /opt/trains/data/redis
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sudo mkdir -p /opt/trains/logs
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sudo mkdir -p /opt/trains/data/fileserver
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sudo mkdir -p /opt/trains/config
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```
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```
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Linux
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```bash
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$ sudo chown -R 1000:1000 /opt/trains
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```
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Mac OS X
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```bash
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```bash
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$ sudo chown -R $(whoami):staff /opt/trains
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```
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1. Clone the [trains-server](https://github.com/allegroai/trains-server) repository and change directories to the new **trains-server** directory.
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```bash
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```bash
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$ git clone https://github.com/allegroai/trains-server.git
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$ cd trains-server
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```
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1. Launch the Docker containers <a name="launch-docker"></a>
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* Automatically with docker-compose (details: [Linux/Ubuntu](docs/faq.md#ubuntu), [OS X](docs/faq.md#mac-osx))
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```bash
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```bash
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$ docker-compose up
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```
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* Manually, see [Launching Docker Containers Manually](docs/docker_setup.md#launch) for instructions.
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1. Your server is now running on [http://localhost:8080](http://localhost:8080) and the following ports are available:
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* Web server on port `8080`
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* API server on port `8008`
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* File server on port `8081`
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@ -126,12 +127,12 @@ By default anyone can login to the **trains-server** Web-App.
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You can configure the **trains-server** to allow only a specific set of users to access the system.
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Enable this feature by placing `apiserver.conf` file under `/opt/trains/config`.
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Sample fixed user configuration file `/opt/trains/config/apiserver.conf`:
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auth {
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# Fixed users login credetials
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# Fixed users login credetials
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# No other user will be able to login
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fixed_users {
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enabled: true
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@ -149,12 +150,12 @@ Sample fixed user configuration file `/opt/trains/config/apiserver.conf`:
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]
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}
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}
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To apply the `apiserver.conf` changes, you must restart the *trains-apiserver* (docker) (see [Restarting trains-server](#restart-server)).
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### Configuring the Non-Responsive Experiments Watchdog
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The non-responsive experiment watchdog, monitors experiments that were not updated for a given period of time,
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The non-responsive experiment watchdog, monitors experiments that were not updated for a given period of time,
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and marks them as `aborted`. The watchdog is always active with a default of 7200 seconds (2 hours) of inactivity threshold.
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To change the watchdog's timeouts, place a `services.conf` file under `/opt/trains/config`.
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@ -165,7 +166,7 @@ Sample watchdog configuration file `/opt/trains/config/services.conf`:
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non_responsive_tasks_watchdog {
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# In-progress tasks that haven't been updated for at least 'value' seconds will be stopped by the watchdog
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threshold_sec: 7200
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# Watchdog will sleep for this number of seconds after each cycle
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watch_interval_sec: 900
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}
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@ -181,38 +182,38 @@ To restart the **trains-server**, you must first stop and remove the containers,
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$ docker-compose down
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$ docker-compose up
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1. Manually restarting dockers [instructions](docs/docker_setup.md#launch).
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## Configuring **TRAINS** client
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Once you have installed the **trains-server**, make sure to configure **TRAINS** [client](https://github.com/allegroai/trains)
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Once you have installed the **trains-server**, make sure to configure **TRAINS** [client](https://github.com/allegroai/trains)
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to use your locally installed server (and not the demo server).
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- Run the `trains-init` command for an interactive setup
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- Run the `trains-init` command for an interactive setup
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- Or manually edit `~/trains.conf` file, making sure the `api_server` value is configured correctly, for example:
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api {
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# API server on port 8008
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api_server: "http://localhost:8008"
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# web_server on port 8080
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web_server: "http://localhost:8080"
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# file server on port 8081
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files_server: "http://localhost:8081"
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}
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* Notice that if you setup **trains-server** in a sub-domain configuration, there is no need to specify a port number,
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* Notice that if you setup **trains-server** in a sub-domain configuration, there is no need to specify a port number,
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it will be inferred from the http/s scheme.
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See [Installing and Configuring TRAINS](https://github.com/allegroai/trains#configuration) for more details.
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## What next?
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Now that the **trains-server** is installed, and TRAINS is configured to use it,
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you can [use](https://github.com/allegroai/trains#using-trains) TRAINS in your experiments and view them in the web server,
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Now that the **trains-server** is installed, and TRAINS is configured to use it,
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you can [use](https://github.com/allegroai/trains#using-trains) TRAINS in your experiments and view them in the web server,
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for example http://localhost:8080
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## Upgrading <a name="upgrade"></a>
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@ -221,15 +222,29 @@ We are constantly updating, improving and adding to the **trains-server**.
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New releases will include new pre-built Docker images.
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When we release a new version and include a new pre-built Docker image for it, upgrade as follows:
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1. Shut down and remove each of your Docker instances using the following commands:
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* Upgrading your docker-compose installation
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* Using Docker-Compose
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```bash
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$ docker-compose down
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```
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* Shut down the docker containers
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```bash
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$ docker-compose down
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```
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* We highly recommend backing up your data directory before upgrading
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(see **Step ii** in the Manual Docker upgrade)
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* Manual Docker launching
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* Spin up the docker containers, it will automatically pull the latest trains-server build
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```bash
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$ docker-compose up
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```
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* In case of a docker error: "... The container name "/trains-???" is already in use by ..."
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Try removing deprecated images with:
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```bash
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$ docker rm -f $(docker ps -a -q)
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```
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* Manual Docker upgrade
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1. Shut down and remove each of your Docker instances using the following commands:
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```bash
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$ sudo docker stop <docker-name>
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@ -240,37 +255,39 @@ When we release a new version and include a new pre-built Docker image for it, u
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* `trains-elastic`
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* `trains-mongo`
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* `trains-redis`
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* `trains-fileserver`
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* `trains-apiserver`
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* `trains-webserver`
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2. We highly recommend backing up your data directory!. A simple way to do that is using `tar`:
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For example, if your data directory is `/opt/trains`, use the following command:
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```bash
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$ sudo tar czvf ~/trains_backup.tgz /opt/trains/data
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```
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This backups all data to an archive in your home directory.
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To restore this example backup, use the following command:
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```bash
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$ sudo rm -R /opt/trains/data
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$ sudo tar -xzf ~/trains_backup.tgz -C /opt/trains/data
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```
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3. Pull the new **trains-server** docker image using the following command:
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```bash
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$ sudo docker pull allegroai/trains:latest
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```
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2. We highly recommend backing up your data directory!. A simple way to do that is using `tar`:
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If you wish to pull a different version, replace `latest` with the required version number, for example:
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```bash
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$ sudo docker pull allegroai/trains:0.10.1
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```
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4. Launch the newly released Docker image (see [Launching Docker Containers](#launch-docker)).
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For example, if your data directory is `/opt/trains`, use the following command:
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```bash
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$ sudo tar czvf ~/trains_backup.tgz /opt/trains/data
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```
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This backups all data to an archive in your home directory.
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To restore this example backup, use the following command:
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```bash
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$ sudo rm -R /opt/trains/data
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$ sudo tar -xzf ~/trains_backup.tgz -C /opt/trains/data
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```
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3. Pull the new **trains-server** docker image using the following command:
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```bash
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$ sudo docker pull allegroai/trains:latest
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```
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If you wish to pull a different version, replace `latest` with the required version number, for example:
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```bash
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$ sudo docker pull allegroai/trains:0.11.0
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```
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4. Launch the newly released Docker image (see [Launching Docker Containers](#launch-docker)).
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## Community & Support
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@ -286,9 +303,9 @@ Additionally, you can always find us at *trains@allegro.ai*
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[Server Side Public License v1.0](https://github.com/mongodb/mongo/blob/master/LICENSE-Community.txt)
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**trains-server** relies on both [MongoDB](https://github.com/mongodb/mongo) and [ElasticSearch](https://github.com/elastic/elasticsearch).
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With the recent changes in both MongoDB's and ElasticSearch's OSS license, we feel it is our responsibility as a
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With the recent changes in both MongoDB's and ElasticSearch's OSS license, we feel it is our responsibility as a
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member of the community to support the projects we love and cherish.
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We believe the cause for the license change in both cases is more than just,
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We believe the cause for the license change in both cases is more than just,
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and chose [SSPL](https://www.mongodb.com/licensing/server-side-public-license) because it is the more general and flexible of the two licenses.
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This is our way to say - we support you guys!
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@ -1,6 +1,6 @@
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# TRAINS-server: Using Docker Pre-Built Images
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The pre-built Docker image for the **trains-server** is the quickest way to get started with your own **TRAINS** server.
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The pre-built Docker image for the **trains-server** is the quickest way to get started with your own **TRAINS** server.
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You can also build the entire **trains-server** architecture using the code available in the [trains-server](https://github.com/allegroai/trains-server) repository.
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@ -61,6 +61,7 @@ For example, if your data directory is `/opt/trains`, then use the following com
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sudo mkdir -p /opt/trains/data/elastic
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sudo mkdir -p /opt/trains/data/mongo/db
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sudo mkdir -p /opt/trains/data/mongo/configdb
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sudo mkdir -p /opt/trains/data/redis
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sudo mkdir -p /opt/trains/logs
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sudo mkdir -p /opt/trains/data/fileserver
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sudo mkdir -p /opt/trains/config
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@ -78,24 +79,28 @@ If your data directory is not `/opt/trains`, then in the five `docker run` comma
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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
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1. Launch the **trains-mongo** Docker container.
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1. Launch the **trains-mongo** Docker container.
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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
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1. Launch the **trains-fileserver** Docker container.
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1. Launch the **trains-redis** Docker container.
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sudo docker run -d --restart="always" --name="trains-redis" -v /opt/trains/data/redis:/data --network="host" redis:5.0
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1. Launch the **trains-fileserver** Docker container.
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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
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1. Launch the **trains-apiserver** Docker container.
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1. Launch the **trains-apiserver** Docker container.
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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
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1. Launch the **trains-webserver** Docker container.
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1. Launch the **trains-webserver** Docker container.
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sudo docker run -d --restart="always" --name="trains-webserver" -p 8080:80 allegroai/trains:latest webserver
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1. Your server is now running on [http://localhost:8080](http://localhost:8080) and the following ports are available:
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* API server on port `8008`
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* Web server on port `8080`
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* File server on port `8081`
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@ -21,6 +21,27 @@ The minimum recommended instance type is **t3a.large**
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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**.
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### Upgrading AMI's to v0.12
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**Including the automatically updated AMI**
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Version 0.12 introduced an additional REDIS docker to the trains-server setup.
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AMI upgrading instructions:
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1. SSH to the EC2 machine running one of the `Latest Version AMI's`
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2. Execute the following bash commands
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```bash
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sudo bash
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echo "" >> /usr/bin/start_or_update_server.sh
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echo "sudo mkdir -p \${datadir}/redis" >> /usr/bin/start_or_update_server.sh
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echo "sudo docker stop trains-redis || true && sudo docker rm -v trains-redis || true" >> /usr/bin/start_or_update_server.sh
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echo "echo never | sudo tee -a /sys/kernel/mm/transparent_hugepage/enabled" >> /usr/bin/start_or_update_server.sh
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echo "sudo sysctl vm.overcommit_memory=1" >> /usr/bin/start_or_update_server.sh
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echo "sudo docker run -d --restart=always --name=trains-redis -v \${datadir}/redis:/data --network=host redis:5 redis-server" >> /usr/bin/start_or_update_server.sh
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```
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3. Reboot the EC2 machine
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## Released versions
|
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The following sections provide a list containing AMI Image ID per region for each released **trains-server** version.
|
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@ -28,22 +49,40 @@ The following sections provide a list containing AMI Image ID per region for eac
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### Latest Version AMI <a name="autoupdate"></a>
|
||||
**For easier upgrades: The following AMI automatically update to the latest release every reboot**
|
||||
|
||||
* **eu-north-1** : ami-05d0d39ba39c93781
|
||||
* **ap-south-1** : ami-01ae99e1c27e0490a
|
||||
* **eu-west-3** : ami-01b156f8c7dd38121
|
||||
* **eu-west-2** : ami-01b80d5a23b8847fb
|
||||
* **eu-west-1** : ami-0524891495168c944
|
||||
* **ap-northeast-2** : ami-0594f00619bea922f
|
||||
* **ap-northeast-1** : ami-0d97b860be6f71a9f
|
||||
* **sa-east-1** : ami-0b0889651918730b8
|
||||
* **ca-central-1** : ami-040c641b2f71082b1
|
||||
* **ap-southeast-1** : ami-00a57be01d39ff964
|
||||
* **ap-southeast-2** : ami-066dcf2cc155b6ec1
|
||||
* **eu-central-1** : ami-0bb64c4bdecebc0a9
|
||||
* **us-east-2** : ami-04addd0766ebb8f46
|
||||
* **us-west-1** : ami-0ea895789568bb537
|
||||
* **us-west-2** : ami-07ae3d0dedfdb2278
|
||||
* **us-east-1** : ami-07fe3993427800995
|
||||
* **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
|
||||
|
||||
### 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
|
||||
|
||||
### v0.11.0
|
||||
* **eu-north-1** : ami-0cbe338f058018c97
|
||||
|
||||
Loading…
Reference in New Issue
Block a user