Deploying Trains Server: Linux and macOS

Trains is now ClearML

This documentation applies to the legacy Trains versions. For the latest documentation, see ClearML.

Trains is now ClearML

This documentation applies to the legacy Trains versions. For the latest documentation, see ClearML.

Deploy the Trains Server in Linux or macOS using our prebuilt Docker image.

Trains on Docker Hub

For Trains docker images, including previous versions, see Trains in Docker Hub. However, pulling the Trains Docker image directly is not required. We provide a docker compose YAML file that does this for you. The docker compose file is included in the instructions on this page.

Prerequisites

For Linux users only:

  • Your Linux distribution must support Docker. For more information, see this explanation in the Docker documentation.
  • You must be logged in as a user with sudo privileges.
  • Use bash for all command-line instructions in this installation.
  • The ports 8080, 8081, and 8008 must be available for the Trains Server services.

Deploying

Securing deployment

By default, Trains Server deploys as an open network. To restrict Trains Server access, follow the instructions in the Network and security section, on the "Configuring Trains Server" page.

To launch your Trains Server on Linux or macOS:

  1. Install Docker. The instructions depend upon your operating system:

  2. Verify the Docker CE installation. Execute the command:

    docker run hello-world

    The expected is output is:

    Hello from Docker!
This message shows that your installation appears to be working correctly.
To generate this message, Docker took the following steps:

1. The Docker client contacted the Docker daemon.
2. The Docker daemon pulled the "hello-world" image from the Docker Hub. (amd64)
3. The Docker daemon created a new container from that image which runs the executable that produces the output you are currently reading.
4. The Docker daemon streamed that output to the Docker client, which sent it to your terminal.

  3. For macOS, only, increase the memory allocation in Docker Desktop to 8GB.

    1. In your top status bar, click the Docker icon.
    2. Click Preferences, Resources, Advanced, and then set the memory to at least 8192.
    3. Click Apply.

  4. For Linux, only, install docker-compose. Execute the following commands (for more information, see Install Docker Compose in the Docker documentation): 

    sudo curl -L "https://github.com/docker/compose/releases/latest/download/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose

  5. Increase vm.max_map_count for Elasticsearch in Docker. Execute the following commands, depending upon your operating system:

    • 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

  6. Remove any previous installation of Trains Server.

    This clears all existing Trains SDK databases.

    sudo rm -R /opt/trains/

  7. Create local directories for the databases and storage.

    sudo mkdir -p /opt/trains/data/elastic_7
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

  8. For macOS, only, do the following:

    1. Open the Docker app.

    2. Select Preferences.

    3. On the File Sharing tab, add /opt/trains.

  9. Grant access to the Dockers, depending upon your operating system.

    • Linux:

      sudo chown -R 1000:1000 /opt/trains

    • macOS:

      sudo chown -R $(whoami):staff /opt/trains

  10. Download the Trains Server docker-compose YAML file.

    sudo curl https://raw.githubusercontent.com/allegroai/trains-server/master/docker-compose.yml -o /opt/trains/docker-compose.yml

  11. For Linux only, configure the Trains Agent Services. If TRAINS_HOST_IP is not provided, then Trains Agent Services will use the external public address of the Trains Server. If TRAINS_AGENT_GIT_USER / TRAINS_AGENT_GIT_PASS are not provided, then Trains Agent Services will not be able to access any private repositories for running service tasks.

    export TRAINS_HOST_IP=server_host_ip_here
export TRAINS_AGENT_GIT_USER=git_username_here
export TRAINS_AGENT_GIT_PASS=git_password_here

  12. Run docker-compose with the downloaded configuration file.

    docker-compose -f /opt/trains/docker-compose.yml up -d

Your server is now running on http://localhost:8080.

Port mapping

After deploying Trains Server, the services expose the following ports:

  • Web server on port 8080
  • API server on port 8008
  • File server on port 8081

Restarting

To restart your Trains Server Docker deployment:

  • To restart Trains Server, first stop and then restart the Docker containers by executing the following commands:
    docker-compose -f /opt/trains/docker-compose.yml down
docker-compose -f /opt/trains/docker-compose.yml up -d

Upgrading

Important: Upgrading from v0.14 or older

For Linux only, if you are upgrading from Trains Server v0.14 or older, configure the Trains Agent Services

  • If TRAINS_HOST_IP is not provided, then Trains Agent Services will use the external public address of the Trains Server.
  • If TRAINS_AGENT_GIT_USER / TRAINS_AGENT_GIT_PASS are not provided, then Trains Agent Services will not be able to access any private repositories for running service tasks.
    export TRAINS_HOST_IP=server_host_ip_here
export TRAINS_AGENT_GIT_USER=git_username_here
export TRAINS_AGENT_GIT_PASS=git_password_here

To upgrade your Trains Server Docker deployment:

  1. Shutdown Trains Server. Executing the following command (which assumes the configuration file is in the environment path).

    docker-compose -f docker-compose.yml down

  2. If you are upgrading from Trains Server version 0.15 or older, a data migration is required before you upgrade. First follow these data migration instructions, and then continue this upgrade.

  3. We recommend backing up your data and, if your configuration folder is not empty, backing up your configuration.

  4. Download the latest docker-compose.yml file.

    curl https://raw.githubusercontent.com/allegroai/trains-server/master/docker-compose.yml -o /opt/trains/docker-compose.yml

  5. Startup Trains Server. This automatically pulls the latest Trains Server build.

    docker-compose -f /opt/trains/docker-compose.yml pull
docker-compose -f /opt/trains/docker-compose.yml up -d

If issues arise during your upgrade, see the FAQ page, How do I fix Docker upgrade errors?.

Backing up and restoring data and configuration

The commands in this section are an example of how to backup and restore your data and configuration .

If your data and configuration folders are in /opt/trains, then archive all data into ~/trains_backup_data.tgz, and your configuration into ~/trains_backup_config.tgz:

sudo tar czvf ~/trains_backup_data.tgz -C /opt/trains/data .
sudo tar czvf ~/trains_backup_config.tgz -C /opt/trains/config .

If you need to restore your data and configuration:

  1. Verify you have the backup files.
  2. Execute the following commands:
    sudo rm -fR /opt/trains/data/* /opt/trains/config/*
sudo tar -xzf ~/trains_backup_data.tgz -C /opt/trains/data
sudo tar -xzf ~/trains_backup_config.tgz -C /opt/trains/config

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