Manage

Learn how to upgrade your server to a new version of ZenML for the different deployment options.

The way to upgrade your ZenML server depends a lot on how you deployed it. However, there are some best practices that apply in all cases. Before you upgrade, check out the best practices for upgrading ZenML guide.

In general, upgrade your ZenML server as soon as you can once a new version is released. New versions come with a lot of improvements and fixes from which you can benefit.

Docker

To upgrade to a new version with docker, you have to delete the existing container and then run the new version of the zenml-server image.

Check that your data is persisted (either on persistent storage or on an external MySQL instance) before doing this.

Optionally also perform a backup before the upgrade.

• Delete the existing ZenML container, for example like this:

  # find your container ID
  docker ps

  # stop the container
  docker stop <CONTAINER_ID>
  
  # remove the container
  docker rm <CONTAINER_ID>

• Deploy the version of the zenml-server image that you want to use. Find all versions here.

  docker run -it -d -p 8080:8080 --name <CONTAINER_NAME> zenmldocker/zenml-server:<VERSION>

Kubernetes with Helm

Important Considerations After Upgrading

• Downgrading is not supported: Downgrading the server to an older version is not supported and can lead to unexpected behavior.

• Client-server version alignment: The version of the Python client that connects to the server should be kept at the same version as the server.

• Recreate snapshots: After upgrading your ZenML server, you need to recreate any snapshots that you were using. Snapshots are tied to specific server versions and will often not work correctly after an upgrade.