Free Nutanix NCP-CN Practice Exam with Questions & Answers | Set: 2

TheNKPA 6.10 documentationand Nutanix Best Practices recommend using workspaces to segment cluster deployments and their associated infrastructure providers, as well as to manage access control through RBAC. The typical workflow is:

Create an NKP workspace dedicated to the R&D environment.

Create an infrastructure provider (e.g., vSphere, AHV) scoped to that workspace.

Create an NKP group for the R&D team and assign admin roles to this group within the workspace.

Deploy workload clusters in this workspace, leveraging the scoped infrastructure provider.

This ensures that:

The R&D team has full administrative control over their resources.

Clusters and infrastructure are logically isolated in the R&D workspace.

RBAC policies are applied cleanly within the workspace context.

The NKPA course details NKP’s monitoring stack for collecting and analyzing metrics across attached and managed clusters, which is critical for troubleshooting issues like out-of-memory errors. The engineer needs to collect centralized metrics and set up alerting to identify performance issues. The correct approach is to usePrometheusfor metrics collection andThanos Queryfor alerting (Option C).

Utilize Prometheus to collect and present centralized metrics on NKP attached and managed clusters: Prometheus is NKP’s default metrics collection tool, deployed as a platform application. It scrapes metrics (e.g., CPU, memory usage) from nodes, pods, and services across all clusters in a workspace, centralizing them for analysis. The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “Prometheus is used in NKP to collect and present centralized metrics from attached and managed clusters, enabling detailed performance analysis.” This is ideal for identifying differences in memory usage causing the out-of-memory errors.

Configure Thanos Query to monitor and send out alerts based on the metric thresholds that have been configured within it: Thanos Query, part of NKP’s monitoring stack, aggregates Prometheus metrics across clusters and provides a unified query interface. It also integrates with Alertmanager to send alerts based on configured thresholds (e.g., memory usage > 90%). The NKPA course notes: “Use Thanos Query to monitor metrics across NKP clusters and configure alerts with Alertmanager to notify engineers of performance issues like out-of-memory errors.” This setup helps the engineer proactively address the issue.

Incorrect Options:

A & B. Utilize Fluentd and Fluent Bit: Fluentd and Fluent Bit are logging tools in NKP, used for collecting logs, not metrics. Metrics collection requires Prometheus.

D. Utilize Thanos to collect and present centralized metrics: Thanos does not collect metrics directly; it extends Prometheus by providing long-term storage and query aggregation. Prometheus is the primary collection tool.

In an air-gapped NKP environment with no Internet access, a bastion host is a critical component for secure management. The NKPA course defines the primary purpose of a bastion host asproviding a secure point for creating and operating NKP clusters. The bastion host acts as a jump server, allowing administrators to securely access the isolated environment, manage cluster deployments, and perform operations like cluster creation, scaling, and upgrades without exposing the environment to external threats.

The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “In a dark site NKP deployment, a bastion host serves as a secure entry point for administrators to create, manage, and operate NKP clusters, ensuring isolation from external networks.” The bastion host is configured with SSH keys and tools like the NKP CLI to facilitate secure interactions with the cluster infrastructure.

Incorrect Options:

A. To store and manage sensitive data: The bastion host is not a storage system; its role is access and management, not data storage.

C. To serve as a load balancer: A bastion host does not perform load balancing; that role is handled by Kubernetes components like MetalLB or cloud-native load balancers.

D. To act as a firewall: While a bastion host enhances security, it is not a firewall. Firewalls are separate components in the network architecture.

Continuous Deployment (CD) is the practice of automatically deploying new software releases across environments after a successful build and testing phase. In the context of NKP, enabling CD ensures that software changes are consistently and reliably rolled out to all clusters associated with a project, ensuring operational uniformity and rapid feature adoption.

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.

Comprehensive and Detailed Explanation:

The correct procedure for deleting an NKP cluster involves using the nkp delete cluster command with the appropriate cluster name and namespace. This ensures that not only the Kubernetes resources but also the corresponding NKP resources (e.g., nodepools, Kommander integration) are deleted cleanly and consistently. Simply deleting the VMs does not clean up the associated NKP management objects. This approach is detailed in the NKP documentation for cluster lifecycle management, emphasizing the need to use the provided CLI commands for full removal.

The NKPA course explains that NKP’s monitoring stack includesPrometheusfor metrics collection and storage, andFluent Bitfor log collection and forwarding. To retain system resource utilization data over several months, the company must focus on Prometheus, as it is responsible for storing time-series metrics data, such as CPU, memory, and network utilization, which are critical for long-term trend analysis.

To handle the increased workload from the online retail application, the Platform Engineer should adjust Prometheus byincreasing its container resource limits and memory settingsto ensure it can process and store more metrics, andincreasing its storageto retain data for several months. The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “For long-term metrics retention in NKP, scale the Prometheus deployment by increasing its resource limits (CPU and memory) and expanding its persistent storage to accommodate larger time-series data.” This involves editing the Prometheus deployment’s resource settings (e.g., via kubectl edit deployment) and updating the PersistentVolumeClaim (PVC) to allocate more storage.

Incorrect Options:

A. Adjust the number of replicas for Fluent Bit: Fluent Bit handles logs, not metrics. Increasing replicas does not address long-term metrics storage.

B. Adjust the number of replicas for Prometheus: Increasing replicas improves availability but does not directly address storage or resource needs for metrics retention.

C. Adjust the resource settings for Fluent Bit: Fluent Bit is for log collection, not metrics storage, and is not relevant for this use case.

As outlined in theNKPA 6.10 documentation,Gossis used tovalidatethat an OS image meets the requirements to serve as an NKP node (such as the presence of required packages, kernel modules, and system settings). Goss is not used to modify or harden the image; rather, it validates conformance.

Key reference:

“During the image build process, Goss tests validate that the image meets the required standards for use as a Kubernetes node in NKP deployments.”

According to theNKPA 6.10 documentationunder the “Preparing for FIPS Compliance” section, the first step for enabling FIPS in an NKP environment is to ensure that the underlying operating system (OS) or OS images are correctly configured for FIPS mode. The Nutanix Kubernetes Platform can only leverage FIPS-compliant cryptographic modules if the underlying OS is already configured for FIPS operation.

Specifically, the documentation states:

"Before enabling FIPS in NKP, ensure that the OS or OS images are prepared and configured to operate in FIPS mode, following the vendor’s guidelines. Once the OS is in FIPS mode, the NKP cluster components can be provisioned with FIPS support."

This foundational step is critical to ensure cryptographic consistency and compliance throughout the NKP stack.

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.