NCP-AIO Installation and Deployment Practice Question
An AI operations engineer is preparing a Kubernetes cluster to run GPU-accelerated inference workloads using the NVIDIA GPU Operator. The cluster nodes already have NVIDIA data center GPUs installed, and the engineer wants to avoid installing the driver manually on each node. Which component of the GPU Operator is responsible for automatically deploying the NVIDIA driver on worker nodes?
⚠ Common exam trap
A common mix-up: candidates confuse the NVIDIA Container Toolkit with the driver container; the toolkit exposes GPUs to containers but does not install the kernel driver.
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's driver container
The driver container within the GPU Operator automates the deployment and management of NVIDIA drivers on Kubernetes nodes. It runs as a DaemonSet and ensures the correct driver version is loaded without manual intervention. This simplifies operations and maintains consistency across the cluster, which is essential for AI workloads that depend on specific driver capabilities.
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 Device Plugin
Why it's wrong here
The NVIDIA Device Plugin is responsible for advertising GPU resources to the Kubernetes scheduler and handling device allocation. It does not install the driver. It assumes the driver and container runtime are already configured. While it is deployed by the GPU Operator, its role is resource management, not driver installation. Therefore, it does not fulfill the automation requirement for drivers.
- ✓
NVIDIA GPU Operator's driver container
Why this is correct
The GPU Operator includes a driver container that runs as a DaemonSet on GPU nodes. It compiles and loads the NVIDIA kernel driver inside a container, eliminating the need for manual host driver installation. This is the intended mechanism for automated driver deployment in Kubernetes environments, ensuring consistent driver versions across nodes without direct host modifications.
- ✗
NVIDIA DCGM Exporter
Why it's wrong here
DCGM Exporter collects and exposes GPU telemetry metrics for monitoring. It does not deploy drivers or manage GPU enablement. It requires a functioning driver and container runtime to gather metrics. In this scenario, the need is to automatically install the driver on nodes, which DCGM Exporter does not perform. It is a monitoring component, not a driver deployment tool.
- ✗
NVIDIA Container Toolkit
Why it's wrong here
The NVIDIA Container Toolkit enables container runtimes to expose GPUs to containers, but it does not install or manage the NVIDIA kernel driver on the host. It relies on a pre-installed driver. In this scenario, the engineer wants automatic driver deployment, which is outside the toolkit's scope. The toolkit is typically installed separately or managed by the GPU Operator as a supporting component.
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.