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Nutanix NCP-CN Exam Syllabus Topics:

TopicDetails
Topic 1
  • Conduct NKP Fleet Management: This section tests the abilities of platform administrators and cloud operations engineers in managing multiple clusters as a fleet. It focuses on configuring workspaces to organize clusters, deploying workload clusters within these workspaces, and attaching or detaching clusters as needed. Additionally, candidates must be able to configure projects for workload segmentation and manage platform applications that support the overall NKP environment.
Topic 2
  • Manage Building an NKP Cluster: This section evaluates the skills of Kubernetes administrators and platform engineers in customizing and deploying NKP clusters. Candidates must show proficiency in tailoring cluster configurations to meet specific requirements and deploying Kommander, the management platform, while applying the appropriate licenses to enable cluster features and management capabilities.
Topic 3
  • Prepare the Environment for an NKP Deployment: This section of the exam measures the skills of infrastructure engineers and cloud administrators and covers the initial setup tasks needed for NKP deployment. Candidates must demonstrate the ability to seed a private container registry, create a bootstrap Kubernetes cluster, and determine license tiers suitable for clusters. They also need to prepare a bastion host for secure access, build machine images or prepare nodes for deployment, and gather all necessary information to build a cluster on the target cloud or on-premises provider.
Topic 4
  • Perform Day 2 Operations: This part assesses the expertise of site reliability engineers and cluster operators in ongoing cluster management tasks after deployment. It includes configuring authentication and authorization mechanisms, setting up logging systems, and implementing cluster backup and recovery procedures. Candidates also need to demonstrate skills in monitoring cluster performance and health, configuring autoscaling to handle workload changes, and performing lifecycle management functions such as upgrades and maintenance.

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Nutanix Certified Professional - Cloud Native v6.10 Sample Questions (Q51-Q56):

NEW QUESTION # 51
A development team decided to employ an efficient monitoring system with Grafana-logging, which was successfully implemented as can be seen in the following output:
AppDeployment "kommander-default-workspace/grafana-logging" created in namespace "kommander-default-workspace".
Which command did the team execute to complete this task?

Answer: B


NEW QUESTION # 52

A Platform Engineer is preparing to deploy a new NKP cluster on Nutanix infrastructure into an air-gapped environment. As part of the preparation process, the engineer is supplying a Ubuntu 22.04 instance to be used for NKP cluster nodes that conforms to the corporate OS image hardening standards. However, during the NIB preparation process, the error shown in the exhibit is received.
What is the likely reason the NIB preparation attempt has failed?

Answer: C


NEW QUESTION # 53
A Kubernetes administrator needs to deploy a new Kubernetes cluster into a new workspace. This cluster requires a predictive analytics solution that detects current and future anomalies. Which option does the administrator need to deploy after the cluster is ready?

Answer: B

Explanation:
The NKPA course highlights that NKP Insights is the platform's integrated solution for observability and analytics, providing predictive analytics to detect current and future anomalies in Kubernetes clusters. NKP Insights leverages machine learning to analyze metrics, logs, and events, identifying performance issues and potential failures proactively. After deploying a new cluster, the administrator can enable NKP Insights as a platform application in the workspace to meet the predictive analytics requirement.
The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: "NKP Insights provides predictive analytics and anomaly detection for Kubernetes clusters, enabling administrators to monitor and optimize cluster performance." This is deployed via the NKP UI or CLI by enabling the Insights application in the workspace.
Incorrect Options:
* B. NCM Intelligent Ops: Nutanix Cloud Manager (NCM) Intelligent Ops is for broader infrastructure management, not Kubernetes-specific analytics.
* C. Nutanix Pulse: Pulse is a telemetry service for Nutanix support, not for analytics.
* D. NKP AI Navigator: This is not a recognized NKP component in the NKPA documentation.
:
Nutanix Kubernetes Platform Administration (NKPA) Course, Section on Observability and Insights.
Nutanix Cloud Native (NCP-CN) 6.10 Study Guide, Chapter on Day 2 Operations.
Nutanix Cloud Bible, NutanixKubernetesPlatform Section: https://www.nutanixbible.com


NEW QUESTION # 54

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?

Answer: B

Explanation:
Comprehensive and Detailed Explanation From Exact Extract of Nutanix Kubernetes Platform Administration (NKPA) Course:
The NKPA course outlines the process of adding GPU-enabled worker nodes to an existing NKP-managed Kubernetes cluster, such as the production cluster in this scenario. The first step in this process is to ensure that a GPU-compatible OS image is available for the new worker nodes, as GPU support requires specific drivers and configurations (e.g., NVIDIA drivers) that are not included in standard OS images.
The correct first step is to create a GPU-compatible OS image using the command:
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nkp create image nutanix --gpu \
--gpu-name=${GPU_NAME} \
--cluster=${NUTANIX_CLUSTER_NAME} \
--endpoint=${NUTANIX_PC_ENDPOINT} \
--subnet=${NUTANIX_SUBNET} ubuntu-22.04
(Option D). This command uses the NKP CLI to create a machine image based on Ubuntu 22.04, tailored for Nutanix AHV infrastructure (nutanix) with GPU support enabled (--gpu). The --gpu-name flag specifies the GPU type (e.g., NVIDIA GPU model), and other parameters define the Nutanix cluster, Prism Central endpoint, and subnet for image creation. The resulting image includes the necessary NVIDIA drivers and dependencies, making it suitable for GPU-enabled worker nodes. The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: "Before adding GPU-enabled workers to an NKP cluster on Nutanix, the first step is to create a GPU-compatible OS image using nkp create image nutanix --gpu, ensuring the image includes the required GPU drivers for the target infrastructure." This image is then used in subsequent steps (like Option A) to create a node pool with GPU-enabled workers.
Without this image, the node pool creation in Option A would fail due to the lack of a suitable --vm-image.
Incorrect Options:
* A. Create a nodepool of workers with GPU: This step requires a pre-existing GPU-compatible OS image (specified via --vm-image). Since the question does not indicate that such an image already exists, creating the image (Option D) must happen first.
* B. Add the GPU Operator to the new workers: The NVIDIA GPU Operator can be installed to manage GPU resources, but this step occurs after the GPU-enabled workers are added to the cluster, not as the first step.
* C. Configure Multi-Instance GPU (MIG): MIG configuration is an advanced GPU setup step that occurs after the workers are added and the GPU Operator is installed, not as the first step.
:
Nutanix Kubernetes Platform Administration (NKPA) Course, Section on GPU Support in NKP Clusters.
Nutanix Cloud Native (NCP-CN) 6.10 Study Guide, Chapter on Managing NKP Clusters.
Nutanix Cloud Bible, NutanixKubernetesPlatform Section: https://www.nutanixbible.com NVIDIA GPU Operator Documentation: https://docs.nvidia.com/datacenter/cloud-native/gpu-operator Before adding GPU-enabled worker nodes to the cluster, a GPU-compatible OS image must be created. This ensures that the required drivers and kernel modules are present for GPU workloads. This step is critical as it ensures the OS image is properly prepared for GPU operations before the nodes are integrated into the cluster.
References: Nutanix Kubernetes Platform Administration Guide - GPU Node Preparation and Image Management


NEW QUESTION # 55
A Platform Engineer is deploying a new Kubernetes application in Amazon Web Services (AWS) Elastic Container Service for Kubernetes (EKS) and Azure Kubernetes Service (AKS). The engineer's team has decided to use a custom image instead of the default images provided by AWS or Azure for their clusters. What functionality will the engineer lose in both AWS EKS and Azure AKS by choosing to use a custom image?

Answer: C


NEW QUESTION # 56
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