This documentation page applies to deploying your own open source ClearML Server. It does not apply to ClearML Hosted Service users.
In v0.16, the Elasticsearch subsystem of Trains Server was upgraded from version 5.6 to version 7.6. This change necessitates the migration of the database contents to accommodate the change in index structure across the different versions.
This page provides the instructions to carry out the migration process. Follow this process if using Trains Server version 0.15 or older and are upgrading to ClearML Server.
The migration process makes use of a script that automatically performs the following:
- Backs up the existing Trains Server Elasticsearch data.
- Launches a pair of Elasticsearch 5 and Elasticsearch 7 migration containers.
- Copies the Elasticsearch indices using the migration containers.
- Terminates the migration containers.
- Renames the original data directory to avoid accidental reuse.
Once the migration process completes successfully, the data is no longer accessible to the older version of Trains Server, and ClearML Server needs to be installed.
- Read/write permissions for the default Trains Server data directory
/opt/clearml/dataand its subdirectories, or, if this default directory is not used, the permissions for the directory and subdirectories that are used.
- A minimum of 8GB system RAM.
- Minimum free disk space of at least 30% plus two times the size of the data.
- Python version >=2.7 or >=3.6, and Python accessible from the command-line as
To migrate the data:
If the Trains Server is up, shut it down:
Linux and macOSdocker-compose -f /opt/trains/docker-compose.yml down
Windowsdocker-compose -f c:\opt\trains\docker-compose-win10.yml down
Kuberneteskubectl delete -k overlays/current_version
Kubernetes using Helmhelm del --purge trains-serverkubectl delete namespace trains
For Kubernetes and Kubernetes using Helm, connect to the node in the Kubernetes cluster labeled
Download the migration package archive.curl -L -O https://github.com/allegroai/clearml-server/releases/download/0.16.0/trains-server-0.16.0-migration.zip
If the file needs to be downloaded manually, use this direct link: trains-server-0.16.0-migration.zip.
Extract the archive.unzip trains-server-0.16.0-migration.zip -d /opt/trains
Migrate the data.
Linux, macOS, and Windows - if managing own containers.
Run the migration script. If elevated privileges are used to run Docker (
sudoin Linux, or admin in Windows), then use elevated privileges to run the migration script.python elastic_upgrade.py [-s|--source <source_path>] [-t|--target <target_path>] [-n|--no-backup] [-p|--parallel]
The following optional command line parameters can be used to control the execution of the migration script:
<source_path>- The path to the Elasticsearch data directory in the current Trains Server deployment.
If not specified, uses the default value of
<target_path>- The path to the Elasticsearch data directory in the current Trains Server deployment.
If not specified, uses the default value of
no-backup- Skip creating a backup of the existing Elasticsearch data directory before performing the migration.
If not specified, takes on the default value of
parallel- Copy several indices in parallel to utilize more CPU cores. If not specified, parallel indexing is turned off.
trains-server-k8srepository and change to the new
trains-server-k8s/upgrade-elasticdirectory:git clone https://github.com/allegroai/clearml-server-k8s.git && cd clearml-server-k8s/upgrade-elastic
upgrade-elasticnamespace and deployments:kubectl apply -k overlays/current_version
Wait for the job to be completed. To check if it's completed, run:kubectl get jobs -n upgrade-elastic
Kubernetes using Helm
clearml-serverrepository to Helm client.helm repo add allegroai https://allegroai.github.io/clearml-server-helm/
clearml-serverrepository is now in the Helm client.helm search clearml
helm searchresults must include
upgrade-elastic-helmon the cluster:helm install allegroai/upgrade-elastic-helm --namespace=upgrade-elastic --name upgrade
namespaceis created in the cluster, and the upgrade is deployed in it.
Wait for the job to complete. To check if it completed, execute the following command:kubectl get jobs -n upgrade-elastic
To finish up:
- Verify the data migration
- Conclude the upgrade.
Upon successful completion, the migration script renames the original Trains Server directory, which contains the now migrated data, and prints a completion message:
All console output during the execution of the migration script is saved to a log file in the directory where the migration script executes:
If the migration script does not complete successfully, the migration script prints the error.
After verifying the data migration completed successfully, conclude the ClearML Server installation process.
For Linux or macOS, conclude with the steps in this section. For other deployment formats, see below.
Important: Upgrading from v0.14 or older
CLEARML_HOST_IPis not provided, then ClearML Agent Services will use the external public address of the ClearML Server.
CLEARML_AGENT_GIT_PASSare not provided, then ClearML Agent Services will not be able to access any private repositories for running service tasks.
For backwards compatibility, the environment variables
TRAINS_AGENT_GIT_PASS are supported.
We recommend backing up data and, if the configuration folder is not empty, backing up the configuration.
For example, if the data and configuration folders are in
/opt/trains, then archive all data into
~/trains_backup_data.tgz, and the 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 .
/opt/trainsand its subdirectories to
/opt/clearml.sudo mv /opt/trains /opt/clearml
Download the latest
docker-compose.ymlfile.curl https://raw.githubusercontent.com/allegroai/clearml-server/master/docker/docker-compose.yml -o /opt/clearml/docker-compose.yml
Startup ClearML Server. This automatically pulls the latest ClearML Server build.docker-compose -f /opt/clearml/docker-compose.yml pulldocker-compose -f /opt/clearml/docker-compose.yml up -d
If issues arise during the upgrade, see the FAQ page, How do I fix Docker upgrade errors?.
To conclude the upgrade for deployment formats other than Linux, follow their upgrade instructions: