NCP-AIO Installation and Deployment Practice Question
An administrator is preparing to deploy an NVIDIA AI Enterprise solution on an OpenShift cluster. Which TWO steps must be completed to ensure the NVIDIA drivers are loaded correctly on the worker nodes?
⚠ Common exam trap
Candidates often overlook Node Feature Discovery (NFD), mistakenly assuming the GPU Operator alone can automatically detect hardware features on OpenShift worker nodes without NFD labeling.
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
✓
Deploy the NVIDIA GPU Operator via the OperatorHub.
On OpenShift, the NVIDIA GPU Operator leverages the Node Feature Discovery (NFD) and the Machine Config Operator to manage kernel modules. Ensuring these are configured correctly allows the driver container to load the proprietary NVIDIA kernel modules successfully. Proper node labeling is also required so the operator can target the correct hardware, ensuring that the driver is injected into the node's operating system environment during the boot process.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Deploy the NVIDIA GPU Operator via the OperatorHub.
Why this is correct
The OperatorHub provides the standard interface for managing lifecycle updates and dependencies within OpenShift. Deploying the GPU Operator from here automatically pulls in required dependencies like NFD, ensuring that the environment is correctly primed to handle the proprietary NVIDIA kernel modules and device plugin communication protocols.
- ✗
Manually install NVIDIA drivers on every host OS.
Why it's wrong here
Manual installation is discouraged in containerized environments like OpenShift because it bypasses the automated lifecycle management provided by the GPU Operator. Manual drivers are difficult to patch, prone to version mismatches with the container runtime, and do not persist across node reboots or OS updates automatically.
- ✓
Configure the Node Feature Discovery (NFD) operator.
Why this is correct
NFD is required to detect hardware capabilities, such as the specific GPU architecture present on worker nodes. The GPU Operator uses this information to determine the correct driver version and configuration settings to apply, ensuring that the kernel modules are compatible with the specific hardware detected during deployment.
- ✗
Install the NVIDIA Triton Inference Server.
Why it's wrong here
The inference server has no role in the low-level installation of system drivers or kernel-mode components. It is an application-layer service that relies on the drivers already being present, so attempting to use it for driver configuration would be ineffective and logically incorrect for infrastructure setup.
- ✗
Set the Kubernetes scheduler to 'AlwaysPull'.
Why it's wrong here
The scheduler's pull policy dictates how images are fetched from registries but does not influence driver loading or kernel module operations. Driver configuration is handled by the GPU Operator's daemonsets and host-path mounts, making image pull policies irrelevant to the successful installation of NVIDIA hardware software components.
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.