NCP-AIO Installation and Deployment Practice Question
A healthcare company is deploying NVIDIA AI Enterprise on a Kubernetes cluster to run medical imaging AI models. The cluster administrator needs to verify that the NVIDIA GPU Operator is installed and functioning correctly. Which command should the administrator use to check the status of the GPU Operator pods?
⚠ Common exam trap
The trap here is assuming that GPU Operator components reside in kube-system or that checking nodes alone is sufficient; the Operator uses its own namespace, and pod status is the definitive check.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
kubectl get pods -n gpu-operator
The NVIDIA GPU Operator deploys its components into the gpu-operator namespace. To verify that the Operator is installed and functioning, the administrator should list the pods in that namespace. This provides a quick overview of all related pods, such as the driver, container toolkit, and device plugin, and their current status.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
kubectl describe daemonset nvidia-device-plugin -n kube-system
Why it's wrong here
The device plugin is part of the GPU Operator, but it may not be in the kube-system namespace; the GPU Operator typically deploys it in the gpu-operator namespace. This command might fail or show incomplete information about the overall Operator status.
- ✗
kubectl logs -n gpu-operator nvidia-driver-daemonset
Why it's wrong here
This command attempts to view logs of a specific daemonset, but the daemonset name may vary, and it does not give a comprehensive view of all GPU Operator pods. The correct approach is to list all pods in the gpu-operator namespace.
- ✗
kubectl get nodes -o wide
Why it's wrong here
This command shows node status and IP addresses but does not provide details about GPU Operator pods. It may show if nodes are ready, but it does not confirm that the GPU Operator components are deployed and healthy.
- ✓
kubectl get pods -n gpu-operator
Why this is correct
The GPU Operator is typically deployed in the gpu-operator namespace. Running kubectl get pods -n gpu-operator lists all pods managed by the Operator, allowing the administrator to verify that components like the driver, container toolkit, and device plugin are running.
About these practice questions
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official NVIDIA exam blueprint
This NCP-AIO practice question is part of Courseiva's free NVIDIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the NCP-AIO exam.