Chapter 4. Updating the installation status of Red Hat OpenShift AI components by using the web console
You can use the OpenShift web console to update the installation status of components of Red Hat OpenShift AI on your OpenShift cluster.
If you upgraded OpenShift AI, the upgrade process automatically used the values of the previous version’s DataScienceCluster
object. New components are not automatically added to the DataScienceCluster
object.
After upgrading OpenShift AI:
-
Inspect the default
DataScienceCluster
object to check and optionally update themanagementState
status of the existing components. -
Add any new components to the
DataScienceCluster
object.
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
- Log in to the OpenShift web console as a cluster administrator.
-
In the web console, click Operators
Installed Operators and then click the Red Hat OpenShift AI Operator. - Click the Data Science Cluster tab.
-
On the DataScienceClusters page, click the
default
object. 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 modelmeshserving: managementState: Removed ray: managementState: Removed trainingoperator: managementState: Removed trustyai: managementState: Removed workbenches: managementState: Removed
In the
spec.components
section of the CR, for each OpenShift AI component shown, set the value of themanagementState
field to eitherManaged
orRemoved
. 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 toRemoved
), 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.
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:
-
In the OpenShift web console, click Workloads
Pods. -
In the Project list at the top of the page, select
redhat-ods-applications
. - In the applications namespace, confirm that there are running pods for each of the OpenShift AI components that you installed.
-
In the OpenShift web console, click Workloads
Confirm the status of all installed components:
-
In the OpenShift web console, click Operators
Installed Operators. - Click the Red Hat OpenShift AI Operator.
-
Click the Data Science Cluster tab and select the
DataScienceCluster
object calleddefault-dsc
. - Select the YAML tab.
In the
installedComponents
section, confirm that the components you installed have a status value oftrue
.NoteIf a component shows with the
component-name: {}
format in thespec.components
section of the CR, the component is not installed.
-
In the OpenShift web console, click Operators