NCP-AIO Installation and Deployment Practice Question
An administrator is deploying NVIDIA AI Enterprise on a bare-metal cluster. Which component must be installed first to ensure proper communication between the Kubernetes scheduler and the underlying GPU hardware?
⚠ Common exam trap
Candidates often think monitoring tools or device plugins must be installed individually first, overlooking that the GPU Operator automates and manages all underlying subcomponents.
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
✓
NVIDIA GPU Operator
The NVIDIA GPU Operator is essential for automating the management of all NVIDIA software components in Kubernetes. By installing it first, the administrator ensures that the device plugin, monitoring tools, and drivers are correctly configured. This foundation is critical for scheduling GPU-accelerated pods, as the Kubernetes scheduler requires the device plugin to advertise available GPU resources to the cluster's API server, enabling seamless workload orchestration across the infrastructure.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
NVIDIA Triton Inference Server
Why it's wrong here
The Triton Inference Server is a model serving platform, not an infrastructure management component. Deploying it before the necessary drivers and device plugins would result in pods failing to initialize because they cannot access the physical GPU hardware or the required NVIDIA container runtime libraries for execution.
- ✓
NVIDIA GPU Operator
Why this is correct
The GPU Operator automates the installation of the NVIDIA driver, the Kubernetes device plugin, the DCGM monitoring agent, and other necessary components. Establishing this layer first ensures the cluster is GPU-aware and that the scheduler can effectively identify and assign physical resources to incoming application workloads.
- ✗
NVIDIA NeMo Framework
Why it's wrong here
NeMo is a high-level generative AI framework used for training and development, not for cluster-level infrastructure orchestration. Installing it without the underlying drivers and device plugins would prevent the framework from utilizing GPU acceleration, rendering the AI training environment completely non-functional and unable to detect compute resources.
- ✗
NVIDIA Base Command Manager
Why it's wrong here
While Base Command Manager assists in cluster management, it is not the primary mechanism for Kubernetes-level GPU hardware scheduling. The GPU Operator is specifically designed for Kubernetes native integration, providing the necessary drivers and device plugins required for pods to successfully request and access physical NVIDIA GPUs.
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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.