AI Operations

Knowledge Check

The following questions validate your technical proficiency in monitoring, troubleshooting, and optimizing AI infrastructure, specifically focusing on Installation using BCM, K8s initialization, and DOCA services; Administration using tools like Slurm, Kubernetes, and Run:ai, as well as GPU configuration (including MIG); Workload management for inference/training deployment and NGC container use; and Troubleshooting Fabric Manager issues, using DCGM diagnostics, and optimizing Storage bottlenecks. This resource helps MLOps engineers and system architects prepare for the NVIDIA-Certified Professional: AI Operations (NCP-AIO).

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1. Which web interface allows administrators to monitor cluster performance, resource utilization, and node health in real time using widgets and resource trees?
2. Where can features available in the NVIDIA Mission Control toolkit be managed within the Base View interface?
3. When installing a workload manager after the initial BCM setup, which utility provides a Text User Interface (TUI) to guide the administrator through the configuration?
4. To synchronize software images across nodes or update a running node with a dry-run option, which command is used within the device mode of cmsh?
5. Which BCM concept allows an administrator to organize compute nodes into categories to inherit specific software images and roles?
6. Which specific BCM network object is used for booting non-head nodes and for all cluster management communication?
7. Which tool is required to create a specialized software image for BlueField DPUs and provision them to boot over the network?
8. When diagnosing cluster issues, which utility is run on the head node to gather comprehensive diagnostic data for BCM support?
9. How can an administrator configure Kubernetes on NVIDIA hosts using BCM to ensure users have dedicated 'restricted' namespaces?
10. What is the primary function of the 'Mission Control' toolkit mentioned in BCM documentation?
11. To apply firmware updates to a DGX H100 system, where should the '.fwpkg' packages be placed on the head node?
12. In BCM, which command allows an administrator to interactively request that a new node be assigned a specific hostname and category based on its MAC address?
13. When managing job scheduling, which Slurm concept allows administrators to group nodes under a unique name so that features can be assigned to them collectively in 'slurm.conf'?
14. Which DPU operation mode allows the embedded ARM system of the DPU to control the NIC resources and data path of both the host and the DPU?
15. To diagnose a node that fails to start the network during the ramdisk stage, which action should the administrator perform?
16. What is the function of the 'hasclientdaemon' parameter when configuring a Cumulus switch in BCM?
17. Which utility allows a user to submit a Slurm job directly from a Jupyter Notebook cell?
18. How does BCM handle the administration of user accounts to ensure secure access across the cluster?
19. When using BCM to monitor GPU utilization at the cluster level, which data producer is responsible for aggregating these metrics?
20. Which command in cmsh allows an administrator to see the results of a health check query across multiple nodes, grouped by category?
21. What is the purpose of the 'cm-chroot-sw-img' wrapper utility?
22. Which tool is used to generate a Slurm network topology configuration (topology.conf) automatically based on cloud or physical network hierarchy?
23. Which command must be run to make committed DPU settings active on the DPU hardware after they are modified in cmsh?
24. What does the 'drain' command do in the context of workload management in BCM?
25. Which monitoring feature allows BCM to scale a cluster up or down automatically by powering nodes on and off based on job demand?
26. When setting up Kubernetes with BCM, which operator is recommended for managing the lifecycle of Jupyter kernels?
27. What is the purpose of the 'FrozenFile' directive in BCM?
28. In BCM, what is a 'chunk' in the context of PBS job scripts?
29. Which command-line tool is used to manage and update the BCM Ansible collection for NVIDIA Base Command Manager 11?
30. What is the maximum number of GPU instances that an NVIDIA A100 GPU can be partitioned into using Multi-Instance GPU (MIG) technology?
31. Which BCM monitoring tool provides the capability to view historical resource consumption metrics aggregated by user or account?
32. When a node is in the 'INSTALLER_FAILED' state, where can the administrator usually find a log explaining the failure?
33. Which Slurm command allows a user to allocate resources in real-time and spawn a shell to execute parallel tasks?
34. To ensure that a passive head node can take over from the active head in an HA setup, which command is used to initially clone the active head node?
35. What is the primary benefit of using 'Offloaded Monitoring' in clusters with more than 1,000 nodes?
36. In the Jupyter integration, which tool provides an interactive way to create and customize kernels without editing JSON files?
37. Which BCM component is responsible for identifying and placing the software image on a regular node during the boot process?
38. To configure a specific node to use a different BIOS setting via Redfish, which tool should the administrator use?
39. Which command is used to monitor network performance between cluster nodes using a handy Python script provided by BCM?
40. What is the recommended method for an administrator to get support for a cluster that has had its BCM package versions replaced with standard distribution versions?

References

Preparing for the NVIDIA-Certified Professional: AI Operations (NCP-AIO) requires an understanding of cluster management, workload orchestration, and GPU optimization. Below is a curated list of official documentation and resources to help you master the exam domains.

  • Base Command Manager: Study the “Installation Guide” and “Administrator Guide” to understand cluster provisioning and node health.
  • DCGM (Data Center GPU Manager): Study for monitoring cluster health, running diagnostics, and performance profiling.
  • Multi-Instance GPU (MIG): You must know how to configure and manage MIG profiles for various workloads.
  • Fabric Manager: Review troubleshooting procedures for the fabric manager service.
  • Slurm: Focus on job scheduling, resource allocation (GRES), and partition management.
  • NVIDIA GPUDirect RDMA: Understand components used to accelerate data movement across networks.
  • Run:ai: Learn to manage GPU fractions, compute quotas, and project-based resource allocation for multi-tenant teams.
  • Kubernetes and NVIDIA GPUs: Focus on the NVIDIA GPU Operator for automating driver deployment and managing GPU resources in containerized environments.
  • NGC: Understand how to pull optimized containers, models, and Helm charts while using the NGC CLI for registry management.
  • Magnum IO: Study the architecture for GPUDirect Storage (GDS) and how it bypasses the CPU to accelerate data movement.