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Chapter 2. Activating the Llama Stack Operator

You can activate the Llama Stack Operator on your OpenShift cluster by setting its managementState to Managed in the OpenShift AI Operator DataScienceCluster custom resource (CR). This setting enables Llama-based model serving without reinstalling or directly editing Operator subscriptions. You can edit the CR in the OpenShift web console or by using the OpenShift CLI (oc).

Note

As an alternative to following the steps in this procedure, you can activate the Llama Stack Operator from the OpenShift CLI (oc) by running the following command:

$ oc patch datasciencecluster <name> --type=merge -p {"spec":{"components":{"llamastackoperator":{"managementState":"Managed"}}}}

Replace <name> with your DataScienceCluster name, for example, default-dsc.

Prerequisites

You have installed OpenShift 4.17 or newer.
You have cluster administrator privileges.
You have installed the OpenShift CLI (oc) as described in the appropriate documentation for your cluster:
- Installing the OpenShift CLI for OpenShift Dedicated
- Installing the OpenShift CLI for Red Hat OpenShift Service on AWS (classic architecture)
You have installed the Red Hat OpenShift AI Operator on your cluster.
You have a DataScienceCluster custom resource in your environment; the default is default-dsc.
Your infrastructure supports GPU-enabled instance types, for example, g4dn.xlarge on AWS.
You have enabled GPU support in OpenShift AI, including installing 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 created a NodeFeatureDiscovery resource instance on your cluster, as described in Installing the Node Feature Discovery Operator and creating a NodeFeatureDiscovery instance in the NVIDIA documentation.
You have created a ClusterPolicy resource instance with default values on your cluster, as described in Creating the ClusterPolicy instance in the NVIDIA documentation.

Procedure

Log in to the OpenShift web console as a cluster administrator.
In the Administrator perspective, click Operators Installed Operators.
Click the Red Hat OpenShift AI Operator to open its details.
Click the Data Science Cluster tab.
On the DataScienceClusters page, click the default-dsc object.
Click the YAML tab.
An embedded YAML editor opens, displaying the configuration for the DataScienceCluster custom resource.
In the YAML editor, locate the spec.components section. If the llamastackoperator field does not exist, add it. Then, set the managementState field to Managed:
```
spec:
  components:
    llamastackoperator:
      managementState: Managed
```
Click Save to apply your changes.

Verification

After you activate the Llama Stack Operator, verify that it is running in your cluster:

In the OpenShift web console, click Workloads Pods.
From the Project list, select the redhat-ods-applications namespace.
Confirm that a pod with the label app.kubernetes.io/name=llama-stack-operator is displayed and has a status of Running.

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Chapter 2. Activating the Llama Stack Operator

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