NCP-AIO Administration Practice Question
An administrator manages an NVIDIA AI Enterprise cluster and needs to enforce GPU resource quotas across multiple Kubernetes namespaces. Which NVIDIA component should be configured to enforce these quotas?
⚠ Common exam trap
The trap here is assuming that NVIDIA GPU Operator or Base Command Manager enforces GPU quotas, when quota enforcement is actually a Kubernetes-native function.
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
✓
Kubernetes ResourceQuota with extended resources
Kubernetes ResourceQuota is the native mechanism to limit aggregate resource consumption per namespace, including extended resources like nvidia.com/gpu. When the NVIDIA device plugin advertises GPUs, administrators can define a ResourceQuota specifying a maximum for nvidia.com/gpu, thereby enforcing GPU quotas. Other NVIDIA tools focus on deployment, management, or monitoring and do not provide quota enforcement.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Kubernetes ResourceQuota with extended resources
Why this is correct
Kubernetes ResourceQuota objects can limit the aggregate quantity of extended resources, such as nvidia.com/gpu, that can be requested within a namespace. By defining a ResourceQuota that specifies a maximum for nvidia.com/gpu, the administrator can enforce GPU quotas across namespaces. This is the native Kubernetes mechanism for quota enforcement and works in conjunction with the NVIDIA device plugin that advertises GPUs as extended resources.
- ✗
NVIDIA DCGM Exporter
Why it's wrong here
DCGM Exporter collects GPU telemetry metrics and exposes them for monitoring systems like Prometheus. It provides visibility into GPU utilization, memory, and other metrics, but it does not enforce resource quotas. Quota enforcement is a control-plane function, not a monitoring function, so DCGM Exporter cannot restrict GPU usage per namespace.
- ✗
NVIDIA Base Command Manager
Why it's wrong here
Base Command Manager is a cluster management tool for provisioning, monitoring, and managing AI workloads on bare-metal or virtualized clusters. It does not directly enforce Kubernetes namespace quotas. While it can help with cluster-wide resource allocation, it operates at a different layer and does not integrate with Kubernetes ResourceQuota objects, so it is not the right choice for this specific requirement.
- ✗
NVIDIA GPU Operator
Why it's wrong here
The GPU Operator automates the deployment and lifecycle management of NVIDIA software components such as drivers, container runtimes, and device plugins on Kubernetes. It does not enforce per-namespace GPU quotas; that is handled by Kubernetes ResourceQuota objects. While the Operator ensures GPUs are schedulable, it does not manage quota enforcement, so it is not the correct component here.
About these practice questions
This NCP-AIO question is part of Courseiva's 309-question bank — original exam-style content with full explanations and wrong-answer analysis, never real exam questions or exam dumps. Learn why practice questions differ from exam dumps →
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.