Free Practice Questions for Nutanix NCP-CN Exam

The exhibit shows an NKP UI message stating “No insights identified,” indicating that NKP Insights, the platform’s predictive analytics and observability feature, is not active. The NKPA course explains that NKP Insights is a platform application that provides anomaly detection and alerting for Kubernetes clusters but requires deployment and configuration to generate insights.

The correct approach (Option C) involves two steps:

Create a persistent volume claim (PVC) and assign it to nkp-insights: NKP Insights requires persistent storage to save logs, metrics, and historical data for analysis. The course specifies that a PVC must be created to provide this storage, ensuring the application can retain data for generating insights.

Install nkp-insights with nkp create appdeployment nkp-insights --app nkp-insights-1.2.2 --workspace kommander-workspace: This command deploys the NKP Insights application across all clusters in the specified workspace (kommander-workspace). The --app flag specifies the application version, and the deployment ensures that insights are generated for all clusters in the workspace.

The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “To enable NKP Insights, create a PersistentVolumeClaim for storage and deploy the application using nkp create appdeployment nkp-insights --app --workspace to begin generating insights across clusters.” This aligns with the need to control alerts across all company clusters, as NKP Insights provides centralized observability.

Incorrect Options:

A. Acquire the NKP Insights Add-on license: NKP Insights is a platform application included in higher-tier licenses (e.g., NKP Ultimate), not a separate add-on. The course does not indicate a separate license requirement.

B. Install nkp-insights in every cluster with kubectl apply: This method is manual and inefficient. NKP’s appdeployment command automates deployment across all clusters in a workspace.

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:

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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.

According to theNKPA 6.10 documentationand Nutanix licensing details, NKP Starter is bundled with theNCI Starterentitlement. This basic licensing tier includes essential capabilities for deploying and managing Kubernetes clusters within a Nutanix environment.

Key reference:

“NKP Starter is included with NCI Starter, providing foundational Kubernetes cluster lifecycle management features for small-scale or starter deployments.”

The NKPA course explains that upgrading an NKP license to the Ultimate tier unlocks advanced features such as fleet management, air-gapped deployments, and additional platform services (e.g., monitoring, logging, backup/restore). These services are deployed on the Management cluster and require sufficient resources to operate effectively. A key prerequisite is tosize the Control Plane nodes appropriately to support the installation of default platform services(Option C).

The Control Plane nodes in the NKP Management cluster run critical components like the API server, controller manager, and Kommander, as well as platform services such as Prometheus, Grafana Loki, and Velero. The Ultimate license increases resource demands due to the expanded functionality, and undersized Control Plane nodes can lead to performance issues or failed deployments. The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “Before upgrading to an NKP Ultimate license, ensure the Control Plane nodes of the Management cluster are sized appropriately (e.g., sufficient CPU, memory, and storage) to support the additional default platform services enabled by the license.” For example, Control Plane nodes might need to be scaled to at least 4 vCPUs and 16 GB RAM, depending on the workload.

Incorrect Options:

A. Size the Sidecar containers appropriately: Sidecar containers are typically used for specific workloads (e.g., logging agents), not for platform services deployment, and are not a licensing prerequisite.

B. Size the ETCD nodes appropriately: While etcd is part of the Control Plane, the course refers to the Control Plane nodes as a whole, not etcd specifically, as the sizing requirement.

D. Size the Worker nodes appropriately: Worker nodes run user workloads, not the platform services, which are deployed on the Control Plane in the Management cluster.

The NKPA course explains that deleting a workspace in NKP, especially after all associated clusters have been removed, is a straightforward process through the NKP UI. The correct method is to navigate to theGlobalview in the top menu bar, selectWorkspacesfrom the menu, locate the target workspace, click thethree-dot buttonnext to it, and selectDelete. This action removes the workspace and its associated configurations from NKP, ensuring a clean environment after the project is finished.

The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “To delete an empty workspace in NKP, go to the Global view in the UI, select Workspaces, click the three-dot menu for the workspace, and choose Delete.” The course confirms that a workspace must be empty (no clusters or resources) before it can be deleted, which aligns with the scenario where the three clusters have already been removed.

Incorrect Options:

A & B. Run kubectl delete workspace: Both options are syntactically similar, but kubectl delete workspace is not a valid command in NKP. Workspaces are managed through the NKP UI or CLI (nkp), not directly via kubectl.

D. Ask a workspace user to delete the workspace: Workspace users typically lack permissions to delete workspaces; this action is reserved for administrators via the Global view.

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 Nutanix Kubernetes Platform (NKP) leverages Cluster API (CAPI) to manage the lifecycle of Kubernetes clusters. When preparing machine images for NKP deployment, the Nutanix Image Builder (NIB) or Kubernetes Image Builder (KIB) process is used to create custom machine images that are compatible with NKP’s infrastructure requirements. According to the NKPA course, the primary purpose of this process is to createCAPI-compliant imagesthat can be used as the base for NKP cluster nodes.

The NKPA course explains that NKP uses CAPI to provision and manage Kubernetes clusters, and CAPI requires machine images that meet specific criteria, such as including the necessary Kubernetes components, container runtimes, and operating system configurations. The NIB/KIB process ensures that the images are pre-configured with these components, making them suitable for use as NKP worker and control plane nodes. The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “The Nutanix Image Builder (NIB) or Kubernetes Image Builder (KIB) is used to create CAPI-compliant machine images that include the required OS, Kubernetes binaries, and dependencies for NKP cluster nodes.”

These images are typically based on supported operating systems like Rocky Linux or Ubuntu, as provided by Nutanix, and are customized to include the container runtime (e.g., containerd), kubeadm, and other dependencies required for CAPI-based cluster provisioning. The resulting images are stored in a location accessible to the NKP deployment process, such as a local registry or Nutanix Prism Central.

Incorrect Options:

A. Hardening an OS image with client-supplied hardening scripts: While hardening the OS is a good practice, it is not the primary purpose of the NIB/KIB process. The NKPA course notes that hardening can be applied as part of image customization, but the core goal is to ensure CAPI compliance, not just hardening.

B. Creating a custom user account for NKP admins to ensure access to NKP nodes: The NIB/KIB process does not focus on creating user accounts. User access is managed through Kubernetes RBAC or external identity providers, as covered in the NKPA course’s authentication section.

C. Tagging the image to be used specifically for NKP: Tagging may occur as part of image management, but it is not the primary purpose. The NKPA course emphasizes CAPI compliance over tagging.

The error states:

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Could not find or access '/home/.../nkp-image-builder-.../playbooks/.../artifacts/1.29.6_ubuntu_22.04_x86_64.tar.gz'

This indicates that theOS package bundle(artifacts/1.29.6_ubuntu_22.04_x86_64.tar.gz) has not been created or is missing. Creating the OS package bundle is a prerequisite step in the NIB workflow.

Key Reference:

Nutanix Kubernetes Platform Administration (NKPA) 6.10 – “Creating OS Package Bundles for NIB”

NCP-CN 6.10 Study Guide – “NIB Preparation Prerequisites”

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According to theNKPA 6.10 documentation, theFIPS Compliant Build featureis exclusively available forEnterprise tierlicensing. This ensures compliance with NIST security standards and provides hardened cryptographic capabilities throughout the Kubernetes cluster stack.

Exact extract from documentation:

“The FIPS-compliant build feature is included in the NKP Enterprise tier, enabling deployments in environments that require strict security compliance.”