NCP-AIO Practice Questions: Install and Deploy Domain

Published: November 15, 2025 | 20 min read

Test your NCP-AIO knowledge with 10 practice questions from the Install and Deploy domain. Includes detailed explanations and answers.

NCP-AIO Practice Questions

Master the Install and Deploy Domain

Test your knowledge in the Install and Deploy domain with these 10 practice questions. Each question is designed to help you prepare for the NCP-AIO certification exam with detailed explanations to reinforce your learning.

Question 1

In the context of deploying NVIDIA Triton Inference Server, what is a critical step to ensure optimal performance?

A) Configuring the server to run on a single CPU core to reduce complexity.

B) Utilizing NVIDIA NGC containers to deploy pre-optimized models.

C) Disabling GPU acceleration to avoid compatibility issues.

D) Running multiple inference servers on the same node to maximize GPU usage.

Show Answer & Explanation

Correct Answer: B

Explanation: Utilizing NVIDIA NGC containers to deploy pre-optimized models is critical for ensuring optimal performance when deploying NVIDIA Triton Inference Server. These containers are specifically optimized for NVIDIA GPUs, providing better performance and ease of deployment. Running on a single CPU core would limit performance, disabling GPU acceleration would negate the benefits of using Triton, and running multiple servers on the same node could lead to resource contention.

Question 2

You are tasked with integrating an NVIDIA AI platform into an existing Kubernetes environment. What is the first step you should take?

A) Deploy the NVIDIA GPU Operator to manage GPU resources.

B) Install Triton Inference Server on each node.

C) Configure MIG on all GPUs to optimize resource usage.

D) Set up a separate Kubernetes cluster dedicated to AI workloads.

Show Answer & Explanation

Correct Answer: A

Explanation: Deploying the NVIDIA GPU Operator is the first step to ensure Kubernetes can manage GPU resources effectively. Options B and C are subsequent actions, and D is unnecessary if integration into an existing cluster is the goal.

Question 3

What is a best practice for managing configuration changes in an NVIDIA AI platform deployment?

A) Making changes directly on the production environment for faster implementation.

B) Using version control systems to track and manage configuration changes.

C) Avoiding documentation of changes to maintain flexibility.

D) Implementing changes during peak usage hours to ensure immediate feedback.

Show Answer & Explanation

Correct Answer: B

Explanation: Using version control systems to track and manage configuration changes is a best practice as it allows for rollback in case of issues, provides a history of changes, and promotes collaboration among team members.

Question 4

Which of the following configuration management tools would be most appropriate for automating the deployment of NVIDIA AI software across a large cluster?

A) Ansible

B) Docker Compose

C) Systemd

D) Bash scripts

Show Answer & Explanation

Correct Answer: A

Explanation: Ansible is a powerful configuration management tool that can automate the deployment and configuration of software across multiple nodes in a cluster, making it ideal for deploying NVIDIA AI software. Docker Compose is more suited for single-node setups. Systemd is a service manager, not a configuration tool. Bash scripts can automate tasks but lack the sophistication and scalability of Ansible.

Question 5

You are tasked with deploying an AI application on an NVIDIA-powered Kubernetes cluster. Which strategy should you use to ensure that the application can scale horizontally while efficiently utilizing GPU resources?

A) Deploy the application as a single monolithic container with all dependencies.

B) Use Kubernetes Horizontal Pod Autoscaler with NVIDIA MIG to partition GPUs for scalable workloads.

C) Configure multiple replicas of the application, each with exclusive access to a full GPU.

D) Implement a custom scheduler to manage GPU allocation for each pod.

Show Answer & Explanation

Correct Answer: B

Explanation: Using Kubernetes Horizontal Pod Autoscaler with NVIDIA MIG (Multi-Instance GPU) allows for efficient partitioning of GPUs, enabling scalable workloads while maximizing resource utilization. Option A does not support horizontal scaling. Option C is less efficient in terms of resource utilization. Option D is unnecessary as Kubernetes with GPU Operator can handle scheduling efficiently.

Question 6

Which of the following best practices should be followed when deploying an NVIDIA AI platform to ensure scalability?

A) Hard-code resource limits for all containers.

B) Use Helm charts to manage application deployments.

C) Deploy applications directly on the host OS for performance.

D) Limit the number of nodes to simplify management.

Show Answer & Explanation

Correct Answer: B

Explanation: Using Helm charts allows for scalable and manageable application deployments in Kubernetes environments. Hard-coding resources (A) and deploying directly on the host (C) reduce flexibility, while limiting nodes (D) contradicts scalability.

Question 7

What is a critical first step when preparing an NVIDIA AI platform for deployment in a data center environment?

A) Configuring the network switches to prioritize AI traffic.

B) Ensuring the data center has adequate power and cooling for GPU hardware.

C) Installing the latest version of the operating system on all nodes.

D) Setting up a dedicated storage solution for AI data.

Show Answer & Explanation

Correct Answer: B

Explanation: Ensuring adequate power and cooling is crucial for the reliable operation of GPU hardware in a data center. Without this, the hardware may overheat or fail. Options A, C, and D are important but secondary to ensuring the physical environment can support the deployment.

Question 8

Which method is most effective for ensuring that updates to the NVIDIA AI platform do not disrupt existing workloads?

A) Performing updates during peak usage times to minimize downtime.

B) Testing updates in a staging environment before applying them to production.

C) Applying updates directly to the production environment for immediate effect.

D) Disabling all workloads during updates to avoid conflicts.

Show Answer & Explanation

Correct Answer: B

Explanation: Testing updates in a staging environment helps identify potential issues before they affect production, ensuring stability. Option A increases the risk of disruption. Option C is risky without prior testing. Option D is unnecessarily disruptive.

Question 9

Which of the following is a best practice for managing configuration changes in a multi-node AI platform deployment?

A) Apply configuration changes directly to each node individually.

B) Use a configuration management tool like Ansible or Puppet.

C) Reboot all nodes after applying configuration changes.

D) Manually document changes to ensure consistency.

Show Answer & Explanation

Correct Answer: B

Explanation: Using a configuration management tool like Ansible or Puppet automates the process of applying configuration changes, ensuring consistency and reducing human error. Option A is inefficient, Option C is not always necessary, and Option D is prone to errors and omissions.

Question 10

When deploying an NVIDIA AI platform in a hybrid cloud environment, which factor is crucial to ensure seamless integration and operation?

A) Deploying the same number of nodes in both on-premises and cloud environments.

B) Ensuring consistent software versions and configurations across environments.

C) Using different orchestration tools for on-premises and cloud deployments.

D) Limiting the use of cloud resources to reduce complexity.

Show Answer & Explanation

Correct Answer: B

Explanation: Ensuring consistent software versions and configurations across both on-premises and cloud environments is crucial for seamless integration and operation, as it prevents compatibility issues and ensures consistent performance.

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About NCP-AIO Certification

The NCP-AIO certification validates your expertise in install and deploy and other critical domains. Our comprehensive practice questions are carefully crafted to mirror the actual exam experience and help you identify knowledge gaps before test day.

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