Nutanix NCP-CN Actual Questions

The NKPA course emphasizes that NKP’s fleet management capabilities allow administrators to manage multiple Kubernetes clusters, including lightweight clusters on edge devices, by attaching them to an NKP workspace. With the NKP Ultimate license tier, the administrator has access to advanced fleet management features, including GitOps-based application deployment across attached clusters.

The most efficient way to lifecycle manage application deployments across the 30 edge devices is tocreate a new workspace and attach the 30 edge devices to this workspace using the Attach Cluster functionality(Option D). Once attached, NKP can use GitOps (via Flux) to push applications to all clusters in the workspace simultaneously, ensuring consistent deployment and lifecycle management. The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “For managing edge devices with lightweight Kubernetes, attach the clusters to an NKP workspace using the Attach Cluster feature, enabling centralized application deployment and lifecycle management via GitOps.” The administrator can use the kubeconfig files to attach each cluster via the NKP UI or CLI (e.g., nkp attach cluster).

Incorrect Options:

A. Create a GitHub configuration for each device: This is manual and inefficient compared to NKP’s centralized GitOps management.

B. Create a script to automate deployment: Scripting is error-prone and lacks NKP’s built-in fleet management capabilities.

C. Delete lightweight Kubernetes and deploy new clusters: This is unnecessary, as NKP can manage existing clusters, including lightweight ones.

The NKPA course details that NKP Platform Applications, such asGrafana Logging,Grafana Loki, andProject Logging, are deployed to Kubernetes clusters to provide monitoring and logging capabilities. To ensure these components are automatically deployed to new workload clusters in a workspace, the administrator must enable them in theApplication sectionunder the workspace configuration in the NKP UI.

The course explains that the Application section allows administrators to select and configure platform applications that should be applied to all clusters within a workspace. By enabling Grafana Logging, Grafana Loki (for log aggregation), and Project Logging (for project-specific log management), these components are automatically deployed as part of the cluster provisioning process. The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “To deploy platform applications like Grafana Loki and logging components to new clusters, configure them in the Application section of the workspace settings in the NKP UI.”

Incorrect Options:

A. Enable them in the Insights section under workspace: The Insights section is for analytics and monitoring dashboards, not for deploying logging components.

B. Enable them in the Projects section under workspace: Projects are sub-divisions within workspaces for resource allocation, not for configuring platform applications.

C. Enable them in the Clusters section under workspace: The Clusters section is for managing cluster settings, not for enabling platform applications.

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 tocreate a GPU-compatible OS imageusing the command:

text

CollapseWrap

Copy

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.

The exhibit shows the NKP UI with a list of clusters, including "arca," "demo," and "production," each with a three-dot menu on the right side. The NKPA course explains that to delete a cluster directly from the NKP UI, the engineer should use theDeleteoption available in the cluster’s three-dot menu. This action initiates the deletion process, removing the cluster from NKP management and freeing up any associated licenses (e.g., CPU core-based licenses, as per NKP licensing).

The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “To delete a cluster in NKP via the UI, navigate to the cluster list, click the three-dot menu for the target cluster (e.g., demo), and select ‘Delete’ to remove the cluster and its resources.” The UI in the exhibit aligns with this process, showing the three-dot menu next to the "demo" cluster, which includes the Delete option. This is the most straightforward method to delete the demo cluster and reallocate resources to the arca cluster.

Incorrect Options:

A. Download kubeconfig and use kubectl delete cluster: kubectl delete cluster is not a valid command for deleting NKP clusters. NKP uses the nkp CLI or UI for cluster deletion.

C. Select Detach and ask the cluster owner to delete: Detach is for external clusters (e.g., EKS), not NKP-managed clusters like "demo," which is on Nutanix infrastructure. Detaching does not delete the cluster.

D. SSH to kommander cluster and execute kubectl delete cluster: Kommander is a management component, but kubectl delete cluster is not a valid command for NKP cluster deletion.