Chapter 2. Enabling the model registry component


Before data scientists in your organization can work with the model registry feature, you must enable the modelregistry component in OpenShift AI.

Prerequisites

Procedure

  1. In the OpenShift console, click Operators Installed Operators.
  2. Search for the Red Hat OpenShift AI Operator version 2.14+, and then click the Operator name to open the Operator details page.
  3. Click the Data Science Cluster tab.
  4. Click the default instance name (for example, default-dsc) to open the instance details page.
  5. Click the YAML tab to show the instance specifications.
  6. Find the spec.components section, and then add or update it to include the following modelregistry component entry, with the managementState field set to Managed, and the registriesNamespace field set to rhoai-model-registries:

     modelregistry:
        managementState: Managed
        registriesNamespace: rhoai-model-registries
    Copy to Clipboard Toggle word wrap
  7. Click Save.

Verification

  • Confirm that the model registry namespace was created successfully:

    1. In the OpenShift console, click Home Projects.
    2. Confirm that the rhoai-model-registries namespace appears in the Projects drop-down list.
  • Check the status of the model-registry-operator-controller-manager pod:

    1. In the OpenShift console, from the Project list, select redhat-ods-applications.
    2. Click Workloads Deployments.
    3. Search for the model-registry-operator-controller-manager deployment.
    4. Check the status:

      1. Click the deployment name to open the deployment details page.
      2. Click the Pods tab.
      3. View the pod status.

        When the status of the model-registry-operator-controller-manager-<pod-id> pod is Running, the pod is ready to use.

Next step

OpenShift AI administrators can create, delete, and manage permissions for model registries. For more information, see Managing model registries.

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