Red Hat build of MicroShift

Install the Red Hat OpenShift AI RPM

To use AI models in MicroShift deployments, install the Red Hat OpenShift AI (Red Hat OpenShift AI Self-Managed) RPM with a new MicroShift installation. You can also install the RPM on an existing MicroShift instance if you restart the system.

The microshift-ai-model-serving RPM contains manifests that deploy kserve, with the raw deployment mode enabled, and ServingRuntimes objects in the redhat-ods-applications namespace.

Red Hat OpenShift AI is a Technology Preview feature only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs) and might not be functionally complete. Red Hat does not recommend using them in production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.

For more information about the support scope of Red Hat Technology Preview features, see Technology Preview Features Support Scope.

Prerequisites

The system requirements for installing MicroShift have been met.
You have root user access to your machine.
The OpenShift CLI (oc) is installed.
You configured your LVM VG with the capacity needed for the PVs of your workload.
You have the RAM and disk space required for your AI model.
You configured the required accelerators, hardware, operating system, and MicroShift to provide the resources your model needs.
Your AI model is ready to use.

Procedure

Install the MicroShift AI-model-serving RPM package by running the following command:
```
$ sudo dnf install microshift-ai-model-serving
```
As a root user, restart the MicroShift service by entering the following command:
```
$ sudo systemctl restart microshift
```

Optional: Install the release information package by running the following command:

$ sudo dnf install microshift-ai-model-serving-release-info

The microshift-ai-model-serving-release-info RPM contains a JSON file with image references useful for offline procedures or deploying a copy of a ServingRuntime custom resource (CR) to your namespace during a bootc image build.

Verification

Verify that the kserve pod is running in the redhat-ods-applications namespace by entering the following command:

$ oc get pods -n redhat-ods-applications

Example output

NAME                                        READY   STATUS    RESTARTS   AGE
kserve-controller-manager-7fc9fc688-kttmm   1/1     Running   0          1h

Next steps

Create a namespace for your AI model.
Package your model into an OCI image.
Configure a model-serving runtime.
Verify that your model is ready for inferencing.
Make requests against the model server.