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NVIDIA AI Operations NCP-AIO Exam

Attempt the NVIDIA-Certified Professional practice test and solve real exam-like NCP-AIO questions to prepare efficiently and increase your chances of success. Our NVIDIA NCP-AIO practice questions match the actual AI Operations exam format, helping you enhance confidence and improve performance. With our NCP-AIO practice exam software, you can analyze your performance, identify weak areas, and work on them effectively to boost your final NVIDIA-Certified Professional exam score.

Vendor:	NVIDIA
Exam Name:	AI Operations
Registration Code:	NCP-AIO
Related Certification:	NVIDIA-Certified Professional Certification
Exam Audience:	NVIDIA System Administrators and AI Infrastructure Engineers,

Total Questions

Last Updated

28-05-2026

Exam Duration

90 MINUTES

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Question: 1

Your organization is running multiple AI models on a single A100 GPU using MIG in a multi-tenant environment. One of the tenants reports a performance issue, but you notice that other tenants are unaffected.

What feature of MIG ensures that one tenant's workload does not impact others?

AHardware-level isolation of memory, cache, and compute resources for each instance.

BDynamic resource allocation based on workload demand.

CShared memory access across all instances.

DAutomatic scaling of instances based on workload size.

Answer: A

Explanation:

Comprehensive and Detailed Explanation From Exact Extract:

NVIDIA's Multi-Instance GPU (MIG) technology provides hardware-level isolation of critical GPU resources such as memory, cache, and compute units for each GPU instance. This ensures that workloads running in one instance are fully isolated and cannot interfere with the performance of workloads in other instances, supporting multi-tenancy without contention.

Question: 2

You are setting up a Kubernetes cluster on NVIDIA DGX systems using BCM, and you need to initialize the control-plane nodes.

What is the most important step to take before initializing these nodes?

ASet up a load balancer before initializing any control-plane node.

BDisable swap on all control-plane nodes before initializing them.

CEnsure that Docker is installed and running on all control-plane nodes.

DConfigure each control-plane node with its own external IP address.

Answer: B

Explanation:

Comprehensive and Detailed Explanation From Exact Extract:

Disabling swap on all control-plane nodes is a critical prerequisite before initializing Kubernetes control-plane nodes. Kubernetes requires swap to be disabled to maintain performance and stability. Failure to disable swap can cause kubeadm initialization to fail or lead to unpredictable cluster behavior.

Question: 3

A new researcher needs access to GPU resources but should not have permission to modify cluster settings or manage other users.

What role should you assign them in Run:ai?

AL1 Researcher

BDepartment Administrator

CApplication Administrator

DResearch Manager

Answer: A

Explanation:

Comprehensive and Detailed Explanation From Exact Extract:

In Run:ai, roles are assigned based on levels of permissions. The L1 Researcher role is designed for users who need access to GPU resources for running jobs and experiments but should not have administrative rights over cluster settings or other users. This role ensures researchers can use resources without affecting cluster configurations or user management. Other roles like Department Administrator, Application Administrator, or Research Manager have broader privileges, including managing users and settings, which are not appropriate for the new researcher's requirements.

Question: 4

Which of the following correctly identifies the key components of a Kubernetes cluster and their roles?

AThe control plane consists of the kube-apiserver, etcd, kube-scheduler, and kube-controller-manager, while worker nodes run kubelet and kube-proxy.

BWorker nodes manage the kube-apiserver and etcd, while the control plane handles all container runtimes.

CThe control plane is responsible for running all application containers, while worker nodes manage network traffic through etcd.

DThe control plane includes the kubelet and kube-proxy, and worker nodes are responsible for running etcd and the scheduler.

Answer: A

Explanation:

Comprehensive and Detailed Explanation From Exact Extract:

In Kubernetes architecture, the control plane is composed of several core components including the kube-apiserver, etcd (the cluster's key-value store), kube-scheduler, and kube-controller-manager. These manage the overall cluster state, scheduling, and orchestration of workloads. The worker nodes are responsible for running the actual containers and include the kubelet (agent that communicates with the control plane) and kube-proxy (handles network routing for services). Other options incorrectly assign these components or roles.

Question: 5

You are using BCM for configuring an active-passive high availability (HA) cluster for a firewall system. To ensure seamless failover, what is one best practice related to session synchronization between the active and passive nodes?

AConfigure both nodes with different zone names to avoid conflicts during failover.

BUse heartbeat network for session synchronization between active and passive nodes.

CEnsure that both nodes use different firewall models for redundancy.

DSet up manual synchronization procedures to transfer session data when needed.

Answer: B

Explanation:

Comprehensive and Detailed Explanation From Exact Extract:

A best practice for active-passive HA clusters, such as for firewall systems managed via BCM, is to use a heartbeat network to synchronize session state data between active and passive nodes. This real-time synchronization allows the passive node to take over seamlessly in case the active node fails, maintaining session continuity and minimizing downtime. Configuring different zone names or firewall models can cause incompatibility, and manual synchronization is prone to errors and delays.

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