Red Hat Summit Red Hat SummitSupportConsoleDevelopersStart a trialContact

Chapter 3. Requirements for upgrading OpenShift AI

When upgrading OpenShift AI, you must complete the following tasks.

Check the components in the DataScienceCluster object

When you upgrade Red Hat OpenShift AI, the upgrade process automatically uses the values from the previous DataScienceCluster object.

After the upgrade, you should inspect the DataScienceCluster object and optionally update the status of any components as described in Updating the installation status of Red Hat OpenShift AI components by using the web console.

Note

New components are not automatically added to the DataScienceCluster object during upgrade. If you want to use a new component, you must manually edit the DataScienceCluster object to add the component entry.

Migrate from embedded Kueue to Red Hat build of Kueue

The embedded Kueue component for managing distributed workloads is deprecated. OpenShift AI now uses the Red Hat build of Kueue Operator to provide enhanced workload scheduling for distributed training, workbench, and model serving workloads.

Before upgrading OpenShift AI, check if your environment is using the embedded Kueue component by verifying the spec.components.kueue.managementState field in the DataScienceCluster custom resource. If the field is set to Managed, you must complete the migration to the Red Hat build of Kueue Operator to avoid controller conflicts and ensure continued support for queue-based workloads.

This migration requires OpenShift 4.18 or later. For more information, see Migrating to the Red Hat build of Kueue Operator.

Address KServe requirements

For the KServe component, which is used by the single-model serving platform to serve large models, you must meet the following requirements:

  • To fully install and use KServe, you must also install Operators for Red Hat OpenShift Serverless and Red Hat OpenShift Service Mesh and perform additional configuration. For more information, see Serving large models.
  • If you want to add an authorization provider for the single-model serving platform, you must install the Red Hat - Authorino Operator. For more information, see Adding an authorization provider for the single-model serving platform.

Address RAG dependencies

If you plan to deploy Retrieval-Augmented Generation (RAG) workloads by using Llama Stack, you must meet the following requirements:

  • You have GPU-enabled nodes available on your cluster and you have installed the Node Feature Discovery Operator and NVIDIA GPU Operator. For more information, see Installing the Node Feature Discovery Operator and Enabling NVIDIA GPUs.
  • You have access to storage for your model artifacts.
  • You have met the KServe installation prerequisites.

Verify Argo Workflows compatibility

If you use your own Argo Workflows instance for pipelines, verify that the installed version is compatible with this release of OpenShift AI. For details, see Supported Configurations.

Update workflows interacting with OdhDashboardConfig resource

Previously, cluster administrators used the groupsConfig option in the OdhDashboardConfig resource to manage the OpenShift groups (both administrators and non-administrators) that can access the OpenShift AI dashboard. Starting with OpenShift AI 2.17, this functionality has moved to the Auth resource. If you have workflows (such as GitOps workflows) that interact with OdhDashboardConfig, you must update them to reference the Auth resource instead.

Expand
Table 3.1. User management resource update
 OpenShift AI 2.16 and earlierOpenShift AI 2.17 and later

apiVersion

opendatahub.io/v1alpha

services.platform.opendatahub.io/v1alpha1

kind

OdhDashboardConfig

Auth

name

odh-dashboard-config

auth

Admin groups

spec.groupsConfig.adminGroups

spec.adminGroups

User groups

spec.groupsConfig.allowedGroups

spec.allowedGroups

Red Hat logoGithubredditYoutubeTwitter

Learn

Try, buy, & sell

Communities

About Red Hat Documentation

We help Red Hat users innovate and achieve their goals with our products and services with content they can trust. Explore our recent updates.

Making open source more inclusive

Red Hat is committed to replacing problematic language in our code, documentation, and web properties. For more details, see the Red Hat Blog.

About Red Hat

We deliver hardened solutions that make it easier for enterprises to work across platforms and environments, from the core datacenter to the network edge.

Theme

© 2026 Red HatBack to top