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Chapter 4. Updating the installation status of Red Hat OpenShift AI components by using the web console

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The following procedure shows how to use the OpenShift web console to update the installation status of components of Red Hat OpenShift AI on your OpenShift cluster.

Important

When your OpenShift AI version upgrades from a previous minor version, the upgrade process uses the settings from the previous DataScienceCluster object.

The following procedure describes how to edit the DataScienceCluster object:

  • Change the installation status of the existing Red Hat OpenShift AI components
  • Add additional components to the DataScienceCluster object that were not available in the previous version of OpenShift AI.

Prerequisites

  • Red Hat OpenShift AI is installed as an Add-on to your Red Hat OpenShift cluster.
  • You have cluster administrator privileges for your OpenShift cluster.

Procedure

  1. Log in to the OpenShift web console as a cluster administrator.
  2. In the web console, click Operators Installed Operators and then click the Red Hat OpenShift AI Operator.
  3. Click the Data Science Cluster tab.
  4. On the DataScienceClusters page, click the default object.

  5. Click the YAML tab.

    An embedded YAML editor opens showing the custom resource (CR) file for the DataScienceCluster object.

  6. In the spec.components section of the CR, for each OpenShift AI component shown, set the value of the managementState field to either Managed or Removed. These values are defined as follows:

    Note

    If a component shows with the component-name: {} format in the spec.components section of the CR, the component is not installed.

    Managed
    The Operator actively manages the component, installs it, and tries to keep it active. The Operator will upgrade the component only if it is safe to do so.
    Removed
    The Operator actively manages the component but does not install it. If the component is already installed, the Operator will try to remove it.
    Important
    • To learn how to install the KServe component, which is used by the single-model serving platform to serve large models, see Serving large models.
    • If they are not already present in the CR file, you can install the CodeFlare, KubeRay, and Kueue components by adding the codeflare, ray, and kueue entries to the spec.components section of the CR and setting the managementState field for the components to Managed.
    • To learn how to configure the distributed workloads feature that uses the CodeFlare, KubeRay, and Kueue components, see Configuring distributed workloads.

  7. Click Save.

    For any components that you updated, OpenShift AI initiates a rollout that affects all pods to use the updated image.

Verification

  • Confirm that there is a running pod for each component:

    1. In the OpenShift web console, click Workloads Pods.
    2. In the Project list at the top of the page, select redhat-ods-applications.
    3. In the applications namespace, confirm that there are running pods for each of the OpenShift AI components that you installed.

  • Confirm the status of all installed components:

    1. In the OpenShift web console, click Operators Installed Operators.
    2. Click the Red Hat OpenShift AI Operator.
    3. Click the Data Science Cluster tab and select the DataScienceCluster object called default-dsc.
    4. Select the YAML tab.

    5. In the installedComponents section, confirm that the components you installed have a status value of true.

      Note

      If a component shows with the component-name: {} format in the spec.components section of the CR, the component is not installed.

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