L Server instance connected to that same database.if you deployed a kubernetes Metadata Store flavor (i.e. a MySQL database service deployed in Kubernetes), you can deploy a ZenML Server in the same Kubernetes cluster and connect it to that same database. However, ZenML will no longer provide the kubernetes Metadata Store flavor and you'll have to manage the Kubernetes MySQL database service deployment yourself going forward.

The ZenML Server inherits the same limitations that the Metadata Store had prior to ZenML 0.20.0:

it is not possible to use a local ZenML Server to track pipelines and pipeline runs that are running remotely in the cloud, unless the ZenML server is explicitly configured to be reachable from the cloud (e.g. by using a public IP address or a VPN connection).

using a remote ZenML Server to track pipelines and pipeline runs that are running locally is possible, but can have significant performance issues due to the network latency.

It is therefore recommended that you always use a ZenML deployment that is located as close as possible to and reachable from where your pipelines and step operators are running. This will ensure the best possible performance and usability.

👣 How to migrate pipeline runs from your old metadata stores

The zenml pipeline runs migrate CLI command is only available under ZenML versions [0.21.0, 0.21.1, 0.22.0]. If you want to migrate your existing ZenML runs from zenml<0.20.0 to zenml>0.22.0, please first upgrade to zenml==0.22.0 and migrate your runs as shown below, then upgrade to the newer version.

To migrate the pipeline run information already stored in an existing metadata store to the new ZenML paradigm, you can use the zenml pipeline runs migrate CLI command.

Before upgrading ZenML, make a backup of all metadata stores you want to migrate, then upgrade ZenML.