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

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-dsc object.

5. Click the YAML tab.

   An embedded YAML editor opens showing the default custom resource (CR) for the DataScienceCluster object, similar to the following example:

   apiVersion: datasciencecluster.opendatahub.io/v1
   kind: DataScienceCluster
   metadata:
     name: default-dsc
   spec:
     components:
       codeflare:
         managementState: Removed
       dashboard:
         managementState: Removed
       datasciencepipelines:
         managementState: Removed
       kserve:
         managementState: Removed
       kueue:
         managementState: Removed
       llamastackoperator:
         managementState: Removed
       modelmeshserving:
         managementState: Removed
       ray:
         managementState: Removed
       trainingoperator:
         managementState: Removed
       trustyai:
         managementState: Removed
       workbenches:
         managementState: Removed
         workbenchNamespace: rhods-notebooks

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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:

   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 Installing the single-model serving platform.
   • If you have not enabled the KServe component (that is, you set the value of the managementState field to Removed), you must also disable the dependent Service Mesh component to avoid errors. See Disabling KServe dependencies.
   • To learn how to install the distributed workloads feature, see Installing the distributed workloads components.

7. Click Save.

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

8. If you are upgrading from OpenShift AI 2.19 or earlier, upgrade the Authorino Operator to the stable update channel, version 1.2.1 or later.

   1. Update Authorino to the latest available release in the tech-preview-v1 channel (1.1.2), if you have not done so already.

   2. Switch to the stable channel:

      1. Navigate to the Subscription settings of the Authorino Operator.
      2. Under Update channel, click on the highlighted tech-preview-v1.
      3. Change the channel to stable.
   3. Select the update option for Authorino 1.2.1.

Verification

1. Confirm that there is at least one 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 or your custom applications namespace.
   3. In the applications namespace, confirm that there are one or more running pods for each of the OpenShift AI components that you installed.

2. 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 status.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.

3. In the OpenShift AI dashboard, users can view the list of the installed OpenShift AI components, their corresponding source (upstream) components, and the versions of the installed components, as described in Viewing installed OpenShift AI components.