Upgrading Red Hat OpenShift AI (Upgrading from Version 5.2 to Version 5.4)

If your environment includes services with a dependency on Red Hat OpenShift AI, you might need to upgrade the Red Hat OpenShift AI Operator before you upgrade IBM® Software Hub.

Upgrade phase

Updating your client workstation
Collecting required information
Preparing to run an upgrade in a restricted network
Preparing to run an upgrade from a private container registry
Preparing the cluster
Preparing to upgrade an instance
Upgrading an instance
Setting up IBM Software Hub

Who needs to complete this task?

Cluster administrator A cluster administrator must complete this task.

When do you need to complete this task?

One-time setup Complete this task if both of the following statements are true:

One or more of the following services are installed or will be installed on the cluster:

Service	Red Hat OpenShift AI
IBM Knowledge Catalog Premium	Required if you run the models on GPU. Not required if you run the models on: CPU A remote instance of watsonx.ai™
IBM Knowledge Catalog Standard	Required if you run the models on GPU. Not required if you run the models on: CPU A remote instance of watsonx.ai
Watson Speech services	Required only if you want to enable the enrichments feature.
watsonx.ai	Always required.
watsonx Assistant	Required only if you want to use features that require GPU.
watsonx™ BI	Always required.
watsonx Code Assistant™	Always required.
watsonx Code Assistant for Red Hat Ansible® Lightspeed	Always required.
watsonx Code Assistant for Z Agentic	Always required.
watsonx Code Assistant for Z Understand	Always required.
watsonx.data™ Premium	Always required.
watsonx.data integration	Required if you use the Unstructured Data Integration feature (`enableUnstructuredDataIntegration: true`).
watsonx.data intelligence	Required if one of the following statements are true: You run models for generative AI on local GPU You use the Unstructured Data Integration feature (`enableUnstructuredDataIntegration: true`), which requires local GPU
watsonx Orchestrate	Required if you run models locally. Not required if you use the AI gateway to access third-party models.

The version of IBM Software Hub that you are upgrading to requires a newer version of Red Hat OpenShift AI:
Release Red Hat OpenShift AI Version

5.4.0 (June 2026) 2.25.1

Release	Red Hat OpenShift AI Version
5.4.0 (June 2026)	2.25.1

Icon representing back up and restore Restore If you plan to restore IBM Software Hub to a different cluster, you must also complete this task on the target cluster.

About this task

The commands in this task upgrade Red Hat OpenShift AI with the minimum components needed to support IBM Software Hub services.

Procedure

Log in to Red Hat OpenShift Container Platform as a cluster administrator.
```
${OC_LOGIN}
```
Remember: OC_LOGIN is an alias for the oc login command.
Set the ODS_OPERATOR_NS environment variable to the name of the project where the Red Hat OpenShift AI Operator is installed.
The following command uses the recommended project: redhat-ods-operator.
```
export ODS_OPERATOR_NS=redhat-ods-operator
```
Set the CHANNEL_VERSION environment variable based on the version of Red Hat OpenShift AI that you are installing:
Version 2.25.1
```
export CHANNEL_VERSION=stable-2.25.1
```

Update the rhods-operator operator subscription:

cat << EOF | oc apply -f -
apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: rhods-operator
  namespace: ${ODS_OPERATOR_NS}
spec:
  name: rhods-operator
  channel: ${CHANNEL_VERSION}
  source: redhat-operators
  sourceNamespace: openshift-marketplace
  config:
     env:
        - name: "DISABLE_DSC_CONFIG"
EOF

The command returns the following message when the subscription is created:

subscription.operators.coreos.com/rhods-operator configured

Set the DSC_INIT_NAME environment variable to the name of the DSC Initialization (DSCInitialization) object.
The following command uses the default name: default-dsci.
```
export DSC_INIT_NAME=default-dsci
```
Tip: Run the following command to get the name of the DSC Initialization (DSCInitialization) object:
```
oc get dscinitialization
```

Update the DSC Initialization (DSCInitialization) object:

cat << EOF | oc apply -f -
apiVersion: dscinitialization.opendatahub.io/v1
kind: DSCInitialization
metadata:
 name: ${DSC_INIT_NAME}
spec:
 applicationsNamespace: redhat-ods-applications
 monitoring:
  managementState: Managed
  namespace: redhat-ods-monitoring
 serviceMesh:
  managementState: Removed
 trustedCABundle:
  managementState: Managed
  customCABundle: ""
EOF

Wait for the DSC Initialization object to be Ready.
To check the status of the object, run:
```
oc get dscinitialization
```
Set the DS_CLUSTER_NAME environment variable to the name of the Data Science Cluster (DataScienceCluster) object.
The following command uses the default name: default-dsc.
```
export DS_CLUSTER_NAME=default-dsc
```
Tip: Run the following command to get the name of the Data Science Cluster (DataScienceCluster) object:
```
oc get datasciencecluster
```

Update the Data Science Cluster (DataScienceCluster) object:

cat << EOF | oc apply -f -
apiVersion: datasciencecluster.opendatahub.io/v1
kind: DataScienceCluster
metadata:
  name: default-dsc
spec:
  components:
    codeflare:
      managementState: Removed
    dashboard:
      managementState: Removed
    datasciencepipelines:
      managementState: Removed
    kserve:
      managementState: Managed
      defaultDeploymentMode: RawDeployment
      serving:
        managementState: Removed
        name: knative-serving
    kueue:
      managementState: Removed
    modelmeshserving:
      managementState: Removed
    ray:
      managementState: Removed
    trainingoperator:
      managementState: Managed
    trustyai:
      managementState: Removed
    workbenches:
      managementState: Removed
EOF

The Red Hat OpenShift AI Operator manages the services that are listed as Managed and upgrades the services, if possible.

Wait for the Data Science Cluster object to be Ready.
To check the status of the object, run:
```
oc get datasciencecluster ${DS_CLUSTER_NAME} -o jsonpath='"{.status.phase}" {"\n"}'
```
Check the status of the pods in the redhat-ods-applications project:
```
oc get pods -n redhat-ods-applications
```
Ensure that the following pods are running:
- kserve-controller-manager
- kubeflow-training-operator
- odh-model-controller

Restart the Red Hat OpenShift AI Operator pod:

oc delete pod -n ${ODS_OPERATOR_NS} -l name=rhods-operator

Edit the inferenceservice-config configuration map in the redhat-ods-applications project:
1. Log in to the Red Hat OpenShift Container Platform web console as a cluster administrator.
2. From the navigation menu, select Workloads > ConfigMaps.
3. From the Project list, select redhat-ods-applications.
4. Click the inferenceservice-config resource. Then, open the YAML tab.
5. In the metadata.annotations section of the file, add opendatahub.io/managed: 'false'. For example:
```
metadata:
  annotations:
    internal.config.kubernetes.io/previousKinds: ConfigMap
    internal.config.kubernetes.io/previousNames: inferenceservice-config
    internal.config.kubernetes.io/previousNamespaces: opendatahub
    opendatahub.io/managed: 'false'
```
6. Find the following entry in the file:
```
"domainTemplate": "{{ .Name }}-{{ .Namespace }}.{{ .IngressDomain }}",
```
7. Update the value of the domainTemplate field to "example.com":
```
"domainTemplate": "example.com",
```
8. Click Save.

What to do next

Now that you've upgraded Red Hat OpenShift AI, you're ready to complete Upgrading Multicloud Object Gateway for IBM Software Hub (Upgrading from Version 5.2 to Version 5.4).