NCP-AIO 시험 - NVIDIA실제시험문제와 답 - 300문항

Question No : 1

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?

A.Configure both nodes with different zone names to avoid conflicts during failover.
B.Use heartbeat network for session synchronization between active and passive nodes.
C.Ensure that both nodes use different firewall models for redundancy.
D.Set up manual synchronization procedures to transfer session data when needed.

정답:
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 touse a heartbeat networkto 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.

Question No : 2

You are a Solutions Architect designing a data center infrastructure for a cloud-based AI application that requires high-performance networking, storage, and security. You need to choose a software framework to program the NVIDIA BlueField DPUs that will be used in the infrastructure. The framework must support the development of custom applications and services, as well as enable tailored solutions for specific workloads. Additionally, the framework should allow for the integration of storage services such as NVMe over Fabrics (NVMe-oF) and elastic block storage.
Which framework should you choose?

A.NVIDIA TensorRT
B.NVIDIA CUDA
C.NVIDIA NSight
D.NVIDIA DOCA

정답:
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
NVIDIADOCA (Data Center Infrastructure-on-a-Chip Architecture) is the software framework designed to program NVIDIA BlueField DPUs (Data Processing Units). DOCA provides libraries, APIs, and tools to develop custom applications, enabling users to offload, accelerate, and secure data center infrastructure functions on BlueField DPUs.
DOCA supports integration with key data center services including storage protocols such asNVMe over Fabrics (NVMe-oF), elastic block storage, and network security and telemetry. It enables tailored solutions optimized for specific workloads and high-performance infrastructure demands.
TensorRT is focused on AI inference optimization.
CUDA is NVIDIA’s GPU programming model for general-purpose GPU computing, not for DPUs.
NSight is a development environment for debugging and profiling NVIDIA GPUs.
Therefore,NVIDIA DOCAis the correct framework for programming BlueField DPUs in a data center environment requiring custom application development and advanced storage/networking integration.

Question No : 3

A system administrator is troubleshooting a Docker container that crashes unexpectedly due to a segmentation fault. They want to generate and analyze core dumps to identify the root cause of the crash.
Why would generating core dumps be a critical step in troubleshooting this issue?

A.Core dumps prevent future crashes by stopping any further execution of the faulty process.
B.Core dumps provide real-time logs that can be used to monitor ongoing application performance.
C.Core dumps restore the process to its previous state, often fixing the error-causing crash.
D.Core dumps capture the memory state of the process at the time of the crash.

정답:
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
Core dumps capture thememory state of a process at the time of its crash, providing a snapshot useful for post-mortem debugging. Analyzing core dumps helps identify the cause of segmentation faults or other critical errors by revealing what the process was doing at failure, including stack traces, variable states, and memory content.

Question No : 4

A DGX H100 system in a cluster is showing performance issues when running jobs.
Which command should be run to generate system logs related to the health report?

A.nvsm show logs --save
B.nvsm get logs
C.nvsm dump health
D.nvsm health --dump-log

정답:
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
For troubleshooting and performance optimization on NVIDIA DGX systems such as DGX H100, the NVIDIA System Management (nvsm)tool is used to gather system health and diagnostic data. The command nvsm dump health is the correct command to generate and export detailed system logs related to the health report of the DGX system.
nvsm show logs --save is not a recognized command format.
nvsm get logs retrieves logs but does not specifically dump the health report logs.
nvsm health --dump-log is not a standard documented nvsm command.
Therefore, nvsm dump health is the valid and documented command used to generate system logs focused on health reporting, useful for diagnosing performance issues in DGX H100 systems.
This usage aligns with NVIDIA’s system management tools guidance for DGX platforms as described in NVIDIA AI Operations documentation for troubleshooting and performance optimization.

Question No : 5

An administrator wants to check if the BlueMan service can access the DPU.
How can this be done?

A.Via system logs
B.Via the DOCA Telemetry Service (DTS)
C.Via a lightweight database operating in the DPU server
D.Via Linux dump files

정답:
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The DOCA Telemetry Service (DTS)is used to monitor and verify the status and accessibility of services like BlueMan on NVIDIA DPUs. It provides telemetry data and health monitoring specific to the DPU and its services. System logs or dump files may provide indirect information but DTS is the targeted tool for this check.

Question No : 6

A system administrator wants to run these two commands in Base Command Manager. Main showprofile device status apc01
What command should the system administrator use from the management node system shell?

A.cmsh -c “main showprofile; device status apc01”
B.cmsh -p “main showprofile; device status apc01”
C.system -c “main showprofile; device status apc01”
D.cmsh-system -c “main showprofile; device status apc01”

정답:
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The Base Command Manager command shell (cmsh) accepts the-cflag to execute multiple commands sequentially. Usingcmsh -c “main showprofile; device status apc01”runs themain showprofilefollowed
bydevice status apc01commands in one invocation, allowing scripted or batch execution from the management node shell.

Question No : 7

A system administrator needs to configure and manage multiple installations of NVIDIA hardware ranging from single DGX BasePOD to SuperPOD.
Which software stack should be used?

A.NetQ
B.Fleet Command
C.Magnum IO
D.Base Command Manager

정답:
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
NVIDIA’s Base Command Manager is the software stack designed specifically for configuration, management, and monitoring of NVIDIA DGX systems, from a single DGX BasePOD up to large-scale SuperPOD deployments. It provides centralized management capabilities to orchestrate AI infrastructure, simplifying deployment, hardware monitoring, and lifecycle management across multiple clusters and data centers.
NetQ is focused on network monitoring and diagnostics rather than overall hardware cluster management.
Fleet Command is an enterprise SaaS solution to deploy and manage AI infrastructure in hybrid cloud environments but is not specifically targeted at on-premises DGX BasePOD to SuperPOD scale hardware management.
Magnum IO is NVIDIA’s high-performance data and storage software stack for managing I/O but not hardware or cluster configuration management.
Therefore, Base Command Manager is the correct and dedicated tool for managing multiple installations of NVIDIA DGX hardware spanning from BasePOD to SuperPOD environments.
This is consistent with NVIDIA’s official AI Operations documentation and product descriptions highlighting Base Command Manager as the unified command and control platform for AI infrastructure management.

Question No : 8

An organization only needs basic network monitoring and validation tools.
Which UFM platform should they use?

A.UFM Enterprise
B.UFM Telemetry
C.UFM Cyber-AI
D.UFM Pro

정답:
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The UFM Telemetry platform provides basic network monitoring and validation capabilities, making it suitable for organizations that require foundational insight into their network status without advanced analytics or AI-driven cybersecurity features. Other platforms such as UFM Enterprise or UFM Pro offer broader or more advanced functionalities, while UFM Cyber-AI focuses on AI-driven cybersecurity.

Question No : 9

After completing the installation of a Kubernetes cluster on your NVIDIA DGX systems using BCM, how can you verify that all worker nodes are properly registered and ready?

A.Run kubectl get nodes to verify that all worker nodes show a status of “Ready”.
B.Run kubectl get pods to check if all worker pods are running as expected.
C.Check each node manually by logging in via SSH and verifying system status with systemctl.

정답:
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The standard method to verify that worker nodes are correctly registered and ready in a Kubernetes cluster is to runkubectl get nodes. This command lists all nodes and their statuses. Nodes showing a status of “Ready” indicates they are properly connected and available to schedule workloads. Checking pods or manual SSH is not the direct or reliable way to verify node readiness.

Question No : 10

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?

A.Hardware-level isolation of memory, cache, and compute resources for each instance.
B.Dynamic resource allocation based on workload demand.
C.Shared memory access across all instances.
D.Automatic scaling of instances based on workload size.

정답:
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
NVIDIA's Multi-Instance GPU (MIG) technology provideshardware-level isolationof 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 No : 11

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

A.The control plane consists of the kube-apiserver, etcd, kube-scheduler, and kube-controller-manager, while worker nodes run kubelet and kube-proxy.
B.Worker nodes manage the kube-apiserver and etcd, while the control plane handles all container runtimes.
C.The control plane is responsible for running all application containers, while worker nodes manage network traffic through etcd.
D.The control plane includes the kubelet and kube-proxy, and worker nodes are responsible for running etcd and the scheduler.

정답:
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In Kubernetes architecture, thecontrol planeis composed of several core components including thekube-apiserver, etcd(the cluster’s key-value store),kube-scheduler, andkube-controller-manager. These manage the overall cluster state, scheduling, and orchestration of workloads. Theworker nodesare responsible for running the actual containers and include thekubelet(agent that communicates with the control plane) and kube-proxy (handles network routing for services). Other options incorrectly assign these components or roles.

Question No : 12

An instance of NVIDIA Fabric Manager service is running on an HGX system with KVM. A System Administrator is troubleshooting NVLink partitioning.
By default, what is the GPU polling subsystem set to?

A.Every 1 second
B.Every 30 seconds
C.Every 60 seconds
D.Every 10 seconds

정답:
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
In NVIDIA AI infrastructure, theNVIDIA Fabric Managerservice is responsible for managing GPU fabric features such as NVLink partitioning on HGX systems. This service periodically polls the GPUs to monitor and manage NVLink states. By default, the GPU polling subsystem is set toevery 30 secondsto balance timely updates with system resource usage.
This polling interval allows the Fabric Manager to efficiently detect and respond to changes or issues in the NVLink fabric without excessive overhead or latency. It is a standard default setting unless specifically configured otherwise by system administrators.
This default behavior aligns with NVIDIA’s system management guidelines for HGX platforms and is referenced in NVIDIA AI Operations materials concerning fabric management and troubleshooting of NVLink partitions.

Question No : 13

A system administrator is experiencing issues with Docker containers failing to start due to volume mounting problems. They suspect the issue is related to incorrect file permissions on shared volumes between the host and containers.
How should the administrator troubleshoot this issue?

A.Use the docker logs command to review the logs for error messages related to volume mounting and permissions.
B.Reinstall Docker to reset all configurations and resolve potential volume mounting issues.
C.Disable all shared folders between the host and container to prevent volume mounting errors.
D.Reduce the size of the mounted volumes to avoid permission conflicts during container startup.

정답:
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
The first step to troubleshoot Docker container volume mounting issues is tocheck the container logsusingdocker logsfor detailed error messages, including those related to permissions. This provides direct insight into the cause of the failure. Reinstalling Docker or disabling shared folders are drastic steps and may not address the root cause. Volume size reduction is unrelated to permission conflicts.

Question No : 14

A system administrator is looking to set up virtual machines in an HGX environment with NVIDIA Fabric Manager.
What three (3) tasks will Fabric Manager accomplish? (Choose three.)

A.Configures routing among NVSwitch ports.
B.Installs GPU operator
C.Coordinates with the NVSwitch driver to train NVSwitch to NVSwitch NVLink interconnects.
D.Coordinates with the GPU driver to initialize and train NVSwitch to GPU NVLink interconnects.
E.Installs vGPU driver as part of the Fabric Manager Package.

정답:
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
NVIDIA Fabric Manager is responsible for managing the fabric interconnect in HGX systems, including:
Configuring routing among NVSwitch ports (A)to optimize communication paths.
Coordinating with the NVSwitch driver to train NVSwitch-to-NVSwitch NVLink interconnects (C)for high-speed link setup.
Coordinating with the GPU driver to initialize and train NVSwitch-to-GPU NVLink interconnects (D) ensuring optimal connectivity between GPUs and switches.
Installing the GPU operator and vGPU driver is typically handled separately and not part of Fabric Manager’s core tasks.

Question No : 15

You are an administrator managing a large-scale Kubernetes-based GPU cluster using Run: AI.
To automate repetitive administrative tasks and efficiently manage resources across multiple nodes, which of the following is essential when using the Run:AI Administrator CLI for environments where automation or scripting is required?

A.Use the runai-adm command to directly update Kubernetes nodes without requiring kubectl.
B.Use the CLI to manually allocate specific GPUs to individual jobs for better resource management.
C.Ensure that the Kubernetes configuration file is set up with cluster administrative rights before using the CL
D.Install the CLI on Windows machines to take advantage of its scripting capabilities.

정답:
Explanation:
Comprehensive and Detailed Explanation From Exact Extract:
When automating tasks with the Run:AI Administrator CLI, it is essential to ensure that theKubernetes configuration file (kubeconfig)is correctly set up with cluster administrative rights. This enables the CLI to interact programmatically with the Kubernetes API for managing nodes, resources, and workloads efficiently. Without proper administrative permissions in the kubeconfig, automated operations will fail due to insufficient rights.
Manual GPU allocation is typically handled by scheduling policies rather than CLI manual assignments. The CLI does not replacekubectlcommands entirely, and installation on Windows is not a critical requirement.
The Run:AI Administrator CLI requires a Kubernetes configuration file with cluster-administrative rights in order to perform automation or scripting tasks across the cluster. Without those rights, the CLI cannot manage nodes or resources programmatically.

NVIDIA NCP-AIO 시험