Verify operator functionality: Worked Example — Kubernetes Integration (NVIDIA-Certified Professional: AI Networking)
Verifying NVIDIA Network Operator Functionality in Kubernetes: A Worked Example In the context of the NVIDIA-Certified Professional: AI Networking...
Verifying NVIDIA Network Operator Functionality in Kubernetes: A Worked Example
In the context of the NVIDIA-Certified Professional: AI Networking certification, a key task is to verify the proper deployment and functionality of the NVIDIA Network Operator within a Kubernetes environment. This operator manages RDMA and InfiniBand networking resources, critical for high-performance AI workloads.
Scenario Overview
You have deployed the NVIDIA Network Operator on a Kubernetes cluster to enable RDMA and InfiniBand capabilities. The next step is to verify that the operator is functioning correctly, ensuring that the cluster nodes are properly configured and the networking resources are available for AI workloads.
Step-by-Step Verification Process
- Check Operator Deployment Status
- Run the command to list the operator pods in the nvidia-network-operator namespace:kubectl get pods -n nvidia-network-operator
- Verify that the operator pod(s) are in the Running state without restarts or errors.
- Inspect Operator Logs
- Retrieve logs from the operator pod to confirm it has started successfully and is managing resources:kubectl logs -n nvidia-network-operator OPERATOR_POD_NAME
- Look for messages indicating successful reconciliation loops and resource management, such as configuring RDMA devices or InfiniBand interfaces.
- Verify Custom Resource Definitions (CRDs)
- List the NVIDIA network-related CRDs to ensure they are registered:kubectl get crds | grep nvidia
- Confirm that CRDs like NetworkNodePolicy or NetworkNodeState exist, which the operator uses to manage node configurations.
- Check Network Node States
- List the NetworkNodeState resources to verify node-level network configurations:kubectl get networknodestates -A
- Inspect the status of each node’s RDMA and InfiniBand interfaces to confirm they are properly initialized and ready.
- Validate RDMA and InfiniBand Interfaces on Nodes
- SSH into a Kubernetes worker node and run commands to check RDMA devices:ibv_devinfo or rdma link show
- Confirm that the expected InfiniBand devices are present and operational.
- Deploy a Test Pod with RDMA Access
- Create a pod that requests RDMA resources to verify that the operator correctly provisions these capabilities.
- Check pod status and logs to ensure it can access RDMA devices without errors.
Worked Example
Problem: After deploying the NVIDIA Network Operator, you want to verify it is functioning correctly on a Kubernetes cluster with three worker nodes.
Solution:
- Run kubectl get pods -n nvidia-network-operator and confirm the operator pod is Running with no restarts.
- Check logs with kubectl logs -n nvidia-network-operator nvidia-network-operator-abc123 and verify messages like "Reconciliation successful".
- List CRDs using kubectl get crds | grep nvidia and confirm presence of networknodestates.nvidia.com.
- Get node states: kubectl get networknodestates -A shows all three nodes with status Ready.
- SSH into a worker node and run ibv_devinfo to see InfiniBand devices listed.
- Deploy a test pod with RDMA access and confirm it runs successfully and can communicate over InfiniBand.
This step-by-step verification confirms the NVIDIA Network Operator is correctly deployed and managing RDMA and InfiniBand networking in Kubernetes, a critical skill for the NVIDIA-Certified Professional: AI Networking exam.
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