Part 3: Provision

What Will You Do

In this part of the self-paced exercise, you will provision an Amazon EKS cluster with a GPU node group based on a declarative cluster specification

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Step 1: Cluster Spec

• Open Terminal (on macOS/Linux) or Command Prompt (Windows) and navigate to the folder where you forked the Git repository
• Navigate to the folder "/getstarted/gpueks/cluster"

The "eks-gpu.yaml" file contains the declarative specification for our Amazon EKS Cluster.

Cluster Details

The following items may need to be updated/customized if you made changes to these or used alternate names.

• cluster name: "demo-gpueks"
• cloud provider: "eks
• project: "default project"
• AWS Region: us-west-1 region
• One regular node group (with t3.large instance type)
• One GPU node group (with g4dn.xlarge instance type)

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Step 2: Provision Cluster

• Navigate to the "cluster" sub folder
• Type the command

rctl apply -f eks-gpu.yaml

If there are no errors, you will be presented with a "Task ID" that you can use to check progress/status. Note that this step requires creation of infrastructure in your AWS account and can take ~20-30 minutes to complete.

{
  "taskset_id": "z24zlmy",
  "operations": [
    {
      "operation": "NodegroupCreation",
      "resource_name": "gpu-nodegroup",
      "status": "PROVISION_TASK_STATUS_PENDING"
    },
    {
      "operation": "NodegroupCreation",
      "resource_name": "t3-nodegroup",
      "status": "PROVISION_TASK_STATUS_PENDING"
    },
    {
      "operation": "ClusterCreation",
      "resource_name": "demo-gpueks",
      "status": "PROVISION_TASK_STATUS_PENDING"
    }
  ],
  "comments": "The status of the operations can be fetched using taskset_id",
  "status": "PROVISION_TASKSET_STATUS_PENDING"
}

• Navigate to the project in your Org
• Click on Infrastructure -> Clusters. You should see something like the following

• Click on the cluster name to monitor progress

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Step 3: Verify Cluster

Once provisioning is complete, you should see a healthy cluster in the web console

• Click on the kubectl link and type the following command

kubectl get nodes

You should see something like the following

NAME                                            STATUS   ROLES    AGE     VERSION
ip-192-168-139-38.us-west-1.compute.internal    Ready    <none>   5m28s   v1.21.5-eks-bc4871b
ip-192-168-168-241.us-west-1.compute.internal   Ready    <none>   5m28s   v1.21.5-eks-bc4871b

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Step 4: Verify GPU Operator

Now, let us verify whether the Nvidia GPU Operator's resources are operational on the EKS cluster

• Click on the kubectl link and type the following command

kubectl get po -n nvidia

You should see something like the following

NAME                                                          READY   STATUS    RESTARTS   AGE
gpu-operator-857dbb9945-jfnqk                                 1/1     Running   0          4h21m
gpu-operator-node-feature-discovery-master-6f698554df-jvht5   1/1     Running   0          4h21m
gpu-operator-node-feature-discovery-worker-9pw8c              1/1     Running   0          118m
gpu-operator-node-feature-discovery-worker-bzvt5              1/1     Running   0          9m56s

The GPU Operator will automatically add "required labels" to the GPU enabled worker nodes.

• Click on nodes and expand the node that belongs to the "gpu" node group

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Recap

Congratulations! At this point, you have successfully configured and provisioned an Amazon EKS cluster with a GPU node group in your AWS account using the RCTL CLI. You are now ready to move on to the next step where you will deploy a "GPU Workload" and review the integrated "GPU Dashboards"

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