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Generate a Helm-based NVIDIA GPU Operator install script for EKS clusters whose GPU node group uses the AWS GPU-optimized AMI. Use after eks-nodes and before eks-validate.
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| name | eks-gpu-operator |
| description | Generate a Helm-based NVIDIA GPU Operator install script for EKS clusters whose GPU node group uses the AWS GPU-optimized AMI. Use after eks-nodes and before eks-validate. |
| version | 1.0.0 |
| author | NVIDIA Omniverse Streaming |
| tags | ["aws","eks","gpu-operator","helm"] |
| tools | ["Shell","Read","Write"] |
Generate generated/<cluster-name>-gpu-operator.sh, a bash script that
installs or upgrades NVIDIA GPU Operator on an existing EKS cluster.
Terraform must not install GPU Operator. Keep the Helm release outside Terraform state.
CLUSTER_NAMEami_type = "AL2023_x86_64_NVIDIA" or a reviewed custom GPU AMI
with driver and container toolkit already installed| Input | Default |
|---|---|
CLUSTER_NAME | required |
GPU_OPERATOR_VERSION | 25.3.1 |
The AWS infra path uses EKS GPU-optimized AMIs. Those AMIs already provide the NVIDIA driver and container toolkit, so install GPU Operator with:
driver.enabled=false
toolkit.enabled=false
operator.defaultRuntime=containerd
GPU Operator still installs Kubernetes GPU operands such as device plugin, DCGM, node feature discovery, and validators.
Generate this script shape:
#!/bin/bash
set -euo pipefail
: "${CLUSTER_NAME:?Set CLUSTER_NAME before running}"
GPU_OPERATOR_VERSION="${GPU_OPERATOR_VERSION:-25.3.1}"
kubectl --context "$CLUSTER_NAME" get nodes >/dev/null
helm repo add nvidia https://helm.ngc.nvidia.com/nvidia --force-update
helm repo update nvidia
tmpdir="$(mktemp -d)"
cleanup() {
rm -rf "$tmpdir"
}
trap cleanup EXIT
helm pull nvidia/gpu-operator \
--version "$GPU_OPERATOR_VERSION" \
--untar \
--untardir "$tmpdir"
kubectl --context "$CLUSTER_NAME" create namespace gpu-operator \
--dry-run=client -o yaml | kubectl --context "$CLUSTER_NAME" apply -f -
kubectl --context "$CLUSTER_NAME" apply -f "$tmpdir/gpu-operator/crds"
helm upgrade --install gpu-operator nvidia/gpu-operator \
--kube-context "$CLUSTER_NAME" \
--namespace gpu-operator \
--version "$GPU_OPERATOR_VERSION" \
--set operator.defaultRuntime=containerd \
--set driver.enabled=false \
--set toolkit.enabled=false \
--wait \
--timeout 20m
For stack destroy, remove GPU Operator before Terraform destroys the cluster:
helm uninstall gpu-operator \
--kube-context "$CLUSTER_NAME" \
--namespace gpu-operator \
--wait --timeout 5m || true
kubectl --context "$CLUSTER_NAME" delete namespace gpu-operator --ignore-not-found
| Error | Cause | Fix |
|---|---|---|
nvidia-driver-daemonset shows ErrImagePull | GPU Operator is trying to install a driver on plain AL2023 | Use ami_type = "AL2023_x86_64_NVIDIA", label GPU nodes with nvidia.com/gpu.deploy.driver=false, and set driver.enabled=false, toolkit.enabled=false. |
GPU node is Ready but has no nvidia.com/gpu allocatable value | GPU Operator operands are not ready or the GPU node group is scaled to zero | Scale the GPU node group to at least one node, wait for gpu-operator pods, then re-check allocatable resources. |
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