Alauda AI

Install Workbench

In Alauda AI 2.8.x, Workbench is normally installed and managed by Alauda AI. Enable the workbench component in the cluster-scoped default AmlCluster; you do not need to upload the Workbench Operator package, install the Operator separately, or create a Workbench custom resource manually.

TOC

PrerequisitesEnable WorkbenchVerification

Prerequisites

  • Alauda AI is installed on the target cluster. See Install Alauda AI.
  • The target cluster has sufficient resources for Workbench workloads.
  • Optional: Alauda Service Mesh (Istio) is required only for the Elyra Kubeflow Pipelines run-URL redirect. Istio integration is disabled by default.

Enable Workbench

In Administrator view:

  1. Open Marketplace > OperatorHub.
  2. Select the target cluster and open Alauda AI.
  3. Open the All Instances tab and edit the default AmlCluster instance.
  4. Set spec.components.workbench.managementState to Managed.
  5. Save the AmlCluster instance and wait for Workbench to become ready.

You can apply the component setting in the AmlCluster YAML:

spec:
  components:
    workbench:
      managementState: Managed
      values:
        global:
          istio:
            enabled: false

Set spec.components.workbench.values.global.istio.enabled to true only when the target cluster runs Alauda Service Mesh and you need Elyra-generated KFP run URLs to redirect through the Kubeflow Istio ingress gateway.

NOTE

The default workbench state is Unmanaged, so Workbench is not installed until you explicitly set the component to Managed. For normal deployments, use Managed and let Alauda AI install and reconcile Workbench.

Verification

Check the AmlCluster status:

kubectl get amlcluster default

The resource should report Phase=Ready and Reason=Reconciled. You can also verify the Workbench resources created by Alauda AI:

# The Workbench instance is ready.
kubectl get workbench -A

# The workspace controller is available.
kubectl -n kubeflow get deploy workspace-controller-controller-manager

# Built-in IDE templates are registered.
kubectl get workspacekind

After the deployment is ready, open Alauda AI and confirm that Workbench appears and that you can open the Workbench list.