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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?

ARun kubectl get nodes to verify that all worker nodes show a status of ''Ready''.

BRun kubectl get pods to check if all worker pods are running as expected.

CCheck each node manually by logging in via SSH and verifying system status with systemctl.

Question 2

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?

AUse Secure NFS support for data redundancy.

BSet up over-the-air updates to automatically restart failed applications.

CEnable high availability for edge clusters.

DConfigure Fleet Command's multi-instance GPU (MIG) to handle failover.

Question 3

Your Kubernetes cluster is running a mixture of AI training and inference workloads. You want to ensure that inference services have higher priority over training jobs during peak resource usage times.

How would you configure Kubernetes to prioritize inference workloads?

AIncrease the number of replicas for inference services so they always have more resources than training jobs.

BSet up a separate namespace for inference services and limit resource usage in other namespaces.

CUse Horizontal Pod Autoscaling (HPA) based on memory usage to scale up inference services during peak times.

DImplement ResourceQuotas and PriorityClasses to assign higher priority and resource guarantees to inference workloads over training jobs.

Question 4

An organization has multiple containers and wants to view STDIN, STDOUT, and STDERR I/O streams of a specific container.

What command should be used?

Adocker top CONTAINER-NAME

Bdocker stats CONTAINER-NAME

Cdocker logs CONTAINER-NAME

Ddocker inspect CONTAINER-NAME

Question 5

You are tasked with deploying a DOCA service on an NVIDIA BlueField DPU in an air-gapped data center environment. The DPU has the required BlueField OS version (3.9.0 or higher) installed, and you have access to the necessary container image from NVIDIA's NGC catalog. However, you need to ensure that the deployment process is successful without an internet connection.

Which of the following steps should you take to deploy the DOCA service on the DPU?

AInstall Docker on the DPU, pull the container directly from NGC, and run it using 'docker run' with appropriate environment variables.

BPull the container image from NGC using Docker and modify the YAML file before deployment.

CManually download the container image and YAML file beforehand, transfer them to the DPU, and deploy using Kubernetes with standalone Kubelet.

DUse the host system's Docker engine to pull the container image and deploy it on the DPU via SSH.

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