Nutanix Certified Professional - Cloud Native v6.10: NCP-CN-6.10 Exam Premium File as PDF & Test Engine

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Nutanix NCP-CN-6.10 Exam Syllabus Topics:

Nutanix Certified Professional - Cloud Native v6.10 Sample Questions:

1. When deploying NKP using the Nutanix provisioning method (CAPX), what are the supported OS platforms?

A) Flatcar, Rocky Linux, and Ubuntu
B) CentOS and Ubuntu
C) CentOS and Rocky Linux
D) Rocky Linux and Ubuntu

2. A company was using a test application called temp-shop developed in the temp-ecommerce NKP Starter cluster. Now, the cluster has just been taking up valuable resources that could be used for other projects, so the development team has decided to remove it. Before proceeding, they verified that they had the cluster configuration file temp-ecommerce.conf. What command should the development team execute to delete the cluster with its nodes and application?

A) nkp delete cluster --application-name=temp-shop --self-managed --kubeconfig=temp- ecommerce.conf
B) nkp delete cluster --cluster-name=temp-ecommerce --self-managed --kubeconfig=temp- ecommerce.conf
C) nkp delete cluster --cluster-name=temp-shop --self-managed --kubeconfig=temp-shop.conf
D) nkp delete cluster --all

3. What is the primary purpose of integrating an identity provider (IdP) into Kommander?

A) To synchronize etcd backups
B) To create default namespaces automatically
C) To authenticate users and assign role-based access
D) To manage pod security policies

4. A current Nutanix cluster is hosting an NKP cluster and a production Kubernetes cluster named production. Infrastructure administrators recently added three nodes with NVidia GPUs for a new AI initiative, and now a Platform Engineer has been asked to add three workers with the GPUs to the production Kubernetes cluster. Which first step should the engineer take to achieve this task?

A) Create a GPU-compatible OS Image with:textCollapseWrapCopynkp create image nutanix --gpu \-
- gpu-name=${GPU_NAME} \--cluster=${NUTANIX_CLUSTER_NAME} \--endpoint=${NUTANIX_PC_ENDPOINT} \--subnet=${NUTANIX_SUBNET} ubuntu-22.04
B) Create a nodepool of workers with GPU:textCollapseWrapCopynkp create nodepool nutanix -c
$CLUSTER_NAME \--vm-image $NAME_OF_GPU_OS_IMAGE_CREATED_BY_NKP_CLI \-o
yaml -- subnets $NUTANIX_SUBNET_NAME \--prism-element-cluster
$NUTANIX_PRISM_ELEMENT_CLUSTER_NAME \$NODEPOOL_NAME
C) Configure Multi-Instance GPU (MIG):textCollapseWrapCopykubectl label nodes ${NODE} nvidia.com/mig.config=all-1g.6gb verwrite
D) Add the GPU Operator to the new workers:textCollapseWrapCopycat <<EOF | kubectl apply -f - kind: Installationapps:nvidia-gpu-operator:enabled: truevalues: |toolkit:nodepool: md-0EOF

5. A development team has decided to implement an efficient logging system and use AWS S3 as storage to manage large volumes of logs in a scalable way.
The team followed these steps:
Set the WORKSPACE_NAMESPACE variable to the namespace copied in the previous step.
Created a config that overrode ConfigMap to update the storage configuration.
Updated the grafana-loki AppDeployment to apply the configuration override.
However the implementation failed.What should the team do to be able to manage log storage in AWS?

A) Configure an IP address corresponding to AWS storage.
B) Create a secret containing the static AWS S3 credentials.
C) Configure a new IAM role specifically for NKP.
D) Create a tenant on AWS.

Solutions: