Chapter 4. Configuring pipelines with your own Argo Workflows instance

Procedure

1. Log in to the OpenShift web console as a cluster administrator.
2. In the OpenShift console, click Operators Installed Operators.
3. Search for the Red Hat OpenShift AI Operator, and then click the Operator name to open the Operator details page.
4. Click the Data Science Cluster tab.
5. Click the default instance name (for example, default-dsc) to open the instance details page.
6. Click the YAML tab to show the instance specifications.

7. Disable the embedded Argo Workflows controllers that are managed by the OpenShift AI Operator:

   1. In the spec.components section, set the value of the managementState field for the aipipelines component to Managed.

   2. In the spec.components.aipipelines section, set the value of the managementState field for argoWorkflowsControllers to Removed, as shown in the following example:

      Example aipipelines specification

      # ...
      spec:
        components:
          aipipelines:
            argoWorkflowsControllers:
              managementState: Removed
            managementState: Managed
      # ...

      Copy to Clipboard Toggle word wrap

8. Click Save to apply your changes.
9. Install and configure a compatible version of Argo Workflows on your cluster. For compatible version information, see Supported Configurations for 3.x. For installation information, see the Argo Workflows Installation documentation.

Verification

1. On the Details tab of the DataScienceCluster instance (for example, default-dsc), verify that AIPipelinesReady has a Status of True.

2. Verify that the ds-pipeline-workflow-controller pod does not exist:

   1. Go to Workloads Pods.
   2. Search for the ds-pipeline-workflow-controller pod.
   3. Verify that this pod does not exist. The absence of this pod confirms that the embedded Argo Workflows controller is disabled.