NCP-AIO Installation and Deployment Practice Question
Which TWO of the following are prerequisites for installing the NVIDIA Container Toolkit on a Linux host?
⚠ Common exam trap
Candidates select guest OS configurations or specific AI frameworks, forgetting that container toolkits strictly depend on low-level host drivers and runtimes.
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
✓
A compatible NVIDIA driver already installed on the host.
To successfully deploy the NVIDIA Container Toolkit, the host must have a functional NVIDIA driver and a container runtime like Docker or containerd. These prerequisites ensure that the runtime has a target to interface with and can correctly map host-side GPU resources into the container namespace. Without these core components, the toolkit cannot bridge the gap between physical hardware and isolated containerized processes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
A compatible NVIDIA driver already installed on the host.
Why this is correct
The NVIDIA driver acts as the kernel-mode component that communicates with the hardware. The container toolkit is essentially a wrapper that relies on this driver to provide GPU access to containers. Without a working driver, the toolkit has no hardware interface to pass through to containers.
- ✗
The latest version of the CUDA Toolkit installed in every container.
Why it's wrong here
While many containers use CUDA, the container toolkit does not require the full CUDA toolkit to be installed inside each container image. The toolkit's primary job is mapping the host-side NVIDIA user-mode libraries into the container, so the container image only needs the necessary runtime libraries.
- ✓
A container runtime such as Docker or containerd.
Why this is correct
The NVIDIA Container Toolkit is designed to integrate specifically with OCI-compliant container runtimes. These runtimes are responsible for the actual execution of containers, and the toolkit modifies their specification to include the NVIDIA GPU devices and drivers during the container startup sequence.
- ✗
An active subscription to NVIDIA AI Enterprise.
Why it's wrong here
The NVIDIA Container Toolkit is an open-source tool and does not require an NVIDIA AI Enterprise subscription for basic functionality. While AI Enterprise offers support and optimized containers, the toolkit itself is freely available and functional for any hardware supported by the NVIDIA driver.
- ✗
A pre-configured Kubernetes cluster with Helm.
Why it's wrong here
The toolkit is a fundamental component for running GPU containers and is not restricted to Kubernetes deployments. It can be installed on standalone Docker or containerd hosts. Kubernetes support via the NVIDIA Device Plugin is an additional layer, but not a prerequisite for the base toolkit installation.
About these practice questions
Courseiva writes every NCP-AIO question from scratch — 309 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or 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.