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Description
This issue follows up on this issue. These changes improve automation, reduce manual edits, and make the documentation less error-prone.
The documentation for the NVIDIA GPU Operator on Red Hat OpenShift Container Platform includes a chapter titled Installing the NVIDIA GPU Operator on OpenShift. I have two suggestions for improvement.
1. Suggestion for section: Installing the NVIDIA GPU Operator using the CLI
Current behavior: Steps 3–5 require manual edits for channel and starting CSV.
Suggested improvements:
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Step 3: Set CHANNEL dynamically (similar to step 9):
$ CHANNEL=$(oc get packagemanifest gpu-operator-certified -n openshift-marketplace -o jsonpath='{.status.defaultChannel}')Omit the example output and the redundant command in step 4.
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Step 4: Store the starting CSV in a variable:
$ STARTING_CSV=$(oc get packagemanifests/gpu-operator-certified -n openshift-marketplace -ojson | jq -r '.status.channels[] | select(.name == "'$CHANNEL'") | .currentCSV') -
Step 5: Use these variables when creating the subscription file:
$ cat <<EOF > nvidia-gpu-sub.yaml apiVersion: operators.coreos.com/v1alpha1 kind: Subscription metadata: name: gpu-operator-certified namespace: nvidia-gpu-operator spec: channel: $CHANNEL installPlanApproval: Manual name: gpu-operator-certified source: certified-operators sourceNamespace: openshift-marketplace startingCSV: $STARTING_CSV EOF
Omit the note about manually editing
channelandstartingCSV.
2. Suggestion for section: Create the cluster policy using the CLI (below "Create the ClusterPolicy instance")
Current behavior: No note about replacing the hardcoded starting CSV (gpu-operator-certified.v22.9.0).
Suggested improvement: If STARTING_CSV is stored as above, update the command:
$ oc get csv -n nvidia-gpu-operator $STARTING_CSV -ojsonpath={.metadata.annotations.alm-examples} | jq '.[0]' > clusterpolicy.jsonNote that to support zsh, .[0] must also be put in quotes.
Apply the same change in the other Create the cluster policy using the CLI section (below "Create the ClusterPolicy instance with NVIDIA vGPU").