Free NCP-AIO Exam Braindumps
NCP - AI Operations Questions 11–15 (page: 4)

Updated On: 10-Feb-2026

What must be done before installing new versions of DOCA drivers on a BlueField DPU?

  1. Uninstall any previous versions of DOCA drivers.
  2. Re-flash the firmware every time.
  3. Disable network interfaces during installation.
  4. Reboot the host system.

Answer(s): A

Explanation:

Comprehensive and Detailed Explanation From Exact Extract:

Before installing new versions of DOCA drivers on NVIDIA BlueField DPUs, it is required to uninstall any previous versions of DOCA drivers to prevent conflicts and ensure a clean upgrade. This ensures that the new installation is not affected by leftover files or configurations from earlier versions. Re- flashing firmware or disabling network interfaces is not always required before every driver installation. Rebooting the host system might be recommended after installation but is not a prerequisite before installing drivers.



A Slurm user needs to display real-time information about the running processes and resource usage of a Slurm job.

Which command should be used?

  1. smap -j <jobid>
  2. scontrol show job <jobid>
  3. sstat -j <job(.step)>
  4. sinfo -j <jobid>

Answer(s): C

Explanation:

Comprehensive and Detailed Explanation From Exact Extract:

The Slurm command sstat is designed to provide real-time statistics about running jobs, including process-level details and resource usage such as CPU, memory, and GPU utilization. Using sstat -j <jobid> or sstat -j <jobid.step> allows monitoring of active job resource consumption.

smap is not a standard Slurm command.

scontrol show job gives job configuration and status but not real-time resource usage.

sinfo displays node and partition information, not job-specific resource stats.

Therefore, sstat is the correct command for real-time job process and resource monitoring.



Which two (2) ways does the pre-configured GPU Operator in NVIDIA Enterprise Catalog differ from the GPU Operator in the public NGC catalog? (Choose two.)

  1. It is configured to use a prebuilt vGPU driver image.
  2. It supports Mixed Strategies for Kubernetes deployments.
  3. It automatically installs the NVIDIA Datacenter driver.
  4. It is configured to use the NVIDIA License System (NLS).
  5. It additionally installs Network Operator.

Answer(s): A,D

Explanation:

Comprehensive and Detailed Explanation From Exact Extract:

The pre-configured GPU Operator in the NVIDIA Enterprise Catalog differs from the public NGC catalog GPU Operator primarily by its configuration to use a prebuilt vGPU driver image and being configured to use the NVIDIA License System (NLS). These adaptations allow better support for enterprise environments where vGPU functionality and license management are critical.

Other options such as automatic installation of the Datacenter driver or additional installation of Network Operator are not specific differences highlighted between the two operators.



You are managing multiple edge AI deployments using NVIDIA Fleet Command. You need to ensure that each AI application running on the same GPU is isolated from others to prevent interference.

Which feature of Fleet Command should you use to achieve this?

  1. Remote Console
  2. Secure NFS support
  3. Multi-Instance GPU (MIG) support
  4. Over-the-air updates

Answer(s): C

Explanation:

Comprehensive and Detailed Explanation From Exact Extract:

NVIDIA Fleet Command is a cloud-native software platform designed to deploy, manage, and orchestrate AI applications at the edge.
When managing multiple AI applications on the same GPU, Multi-Instance GPU (MIG) support is critical. MIG allows a single GPU to be partitioned into multiple independent instances, each with dedicated resources (compute, memory, bandwidth), enabling workload isolation and preventing interference between applications.

Remote Console allows remote access for management but does not provide GPU resource isolation.

Secure NFS support is for secure network file system sharing, unrelated to GPU resource partitioning.

Over-the-air updates are for updating software remotely, not for GPU resource management.

Therefore, to ensure application isolation on the same GPU in Fleet Command environments, enabling MIG support (option C) is the recommended and standard practice.

This capability is emphasized in NVIDIA's AI Operations and Fleet Command documentation for managing edge AI deployments efficiently and securely.



You are deploying AI applications at the edge and want to ensure they continue running even if one of the servers at an edge location fails.

How can you configure NVIDIA Fleet Command to achieve this?

  1. Use Secure NFS support for data redundancy.
  2. Set up over-the-air updates to automatically restart failed applications.
  3. Enable high availability for edge clusters.
  4. Configure Fleet Command's multi-instance GPU (MIG) to handle failover.

Answer(s): C

Explanation:

Comprehensive and Detailed Explanation From Exact Extract:

To ensure continued operation of AI applications at the edge despite server failures, NVIDIA Fleet Command allows administrators to enable high availability (HA) for edge clusters. This HA configuration ensures redundancy and failover capabilities, so applications remain operational when an edge server goes down.

Over-the-air updates handle software patching but do not inherently provide failover. MIG manages GPU resource partitioning, not failover. Secure NFS supports storage redundancy but is not the primary solution for application failover.



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