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Requirements for upgrading {productname-short}

This section describes the tasks that you should complete when upgrading {productname-short}.

Check the components in the DataScienceCluster object

When you upgrade to version {vernum}, the upgrade process automatically uses the values from the DataScienceCluster object in the previous version.

After the upgrade, you should inspect the {vernum} DataScienceCluster object and optionally update the status of any components as described in Installing Open Data Hub components.

Note

New components are not automatically added to the DataScienceCluster object during upgrade. If you want to use a new component, you must manually edit the DataScienceCluster object to add the component entry.

Recreate existing pipeline runs

When you upgrade to version {vernum}, any existing pipeline runs that you created in version 1 continue to refer to the previous version’s image (as expected).

You must delete the pipeline runs (not the pipelines) and create new pipeline runs. The pipeline runs that you create in version {vernum} correctly refer to the version {vernum} image.

For more information about pipeline runs, see Managing pipeline runs.

Address KServe requirements

For KServe (single-model serving platform), you must meet these requirements:

  • Install dependent Operators, including the Red Hat OpenShift Serverless and Red Hat OpenShift Service Mesh Operators. For more information, see Serving large models.

  • After the upgrade, you must inspect the default DataScienceCluster object and verify that the value of the managementState field for the kserve component is Managed.

  • In {productname-long} version 1, the KServe component is a Limited Availability feature. If you enabled the kserve component and created models in version 1, then after you upgrade to version {vernum}, you must update some {productname-short} resources as follows:

    1. Log in to the {openshift-platform} console as a cluster administrator:

      $ oc login

    2. Update the DSC Initialization resource:

      $ oc patch $(oc get dsci -A -oname) --type='json' -p='[{"op": "replace", "path": "/spec/serviceMesh/managementState", "value":"Unmanaged"}]'

    3. Update the Data Science Cluster resource:

      $ oc patch $(oc get dsc -A -oname) --type='json' -p='[{"op": "replace", "path": "/spec/components/kserve/serving/managementState", "value":"Unmanaged"}]'

    4. Update the InferenceServices CRD:

      $ oc patch crd inferenceservices.serving.kserve.io --type=json -p='[{"op": "remove", "path": "/spec/conversion"}]'

    5. Optionally, restart the Operator pod.

  • If you deployed a model by using KServe in {productname-short} version 1, when you upgrade to version {vernum} the model does not automatically appear in the {productname-short} dashboard. To update the dashboard view, redeploy the model by using the {productname-short} dashboard.