NCP-AIO Installation and Deployment Practice Question
An AI operations team is installing the NVIDIA GPU Operator on a Kubernetes cluster that uses a custom containerd configuration. They need to ensure that the GPU Operator can properly manage the container runtime. Which action should they take before installing the GPU Operator?
⚠ Common exam trap
The trap here is assuming the GPU Operator requires manual runtime configuration, when in fact it manages the runtime and conflicts can arise from pre-existing settings.
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
✓
Ensure that the containerd configuration does not already include conflicting NVIDIA runtime settings.
Before installing the GPU Operator, any pre-existing NVIDIA runtime configuration in containerd should be removed to avoid conflicts. The operator manages the runtime configuration itself, so manual settings can interfere. Other options like changing the default runtime or disabling containerd are incorrect because the operator integrates with the existing runtime rather than replacing or requiring manual overrides.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Label the nodes with the appropriate container runtime version.
Why it's wrong here
While node labels can provide information, the GPU Operator does not require manual labeling of the container runtime version to function. It discovers the runtime and configures it. Adding such labels is not a prerequisite and does not affect the operator's ability to manage the runtime.
- ✗
Set the default runtime in containerd to nvidia-container-runtime.
Why it's wrong here
The GPU Operator deploys the NVIDIA Container Toolkit and configures the runtime automatically. Manually setting the default runtime to nvidia-container-runtime is not required and can conflict with the operator's management. The operator expects to manage runtime configuration itself, so this step is unnecessary and potentially harmful.
- ✗
Disable the containerd systemd service and let the GPU Operator start its own runtime.
Why it's wrong here
The GPU Operator does not replace containerd; it configures the existing runtime to support NVIDIA GPUs. Disabling containerd would break the container runtime for the entire cluster and is not a supported action. The operator works with the installed containerd, not instead of it.
- ✓
Ensure that the containerd configuration does not already include conflicting NVIDIA runtime settings.
Why this is correct
The GPU Operator manages the NVIDIA Container Toolkit and runtime configuration. If containerd already has manually added NVIDIA runtime settings, these can conflict with the operator's configuration, leading to failures. It is best practice to remove any existing NVIDIA runtime configuration before installation so the operator can set it up cleanly.
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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.