Pass the Nutanix Certified Professional (NCP) NCP-CN Questions and answers with ValidTests

The NKPA course explains the role of a bootstrap cluster in NKP deployments, particularly in hybrid architectures involving Nutanix on-prem and Amazon EKS. A bootstrap cluster is a temporary Kubernetes cluster created during the deployment process to initialize Cluster API (CAPI) components, which manage the lifecycle of the target NKP clusters. The primary function of the bootstrap cluster is touse Cluster API for infrastructure-agnostic provisioning(Option D).

CAPI enables NKP to provision clusters across different infrastructures (e.g., Nutanix AHV, AWS EKS) in a consistent, infrastructure-agnostic manner. The bootstrap cluster runs the CAPI controllers (e.g., CAPX for Nutanix, CAPA for AWS) that orchestrate the creation of the target clusters, abstracting the underlying infrastructure details. The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “The bootstrap cluster in NKP uses Cluster API to provide infrastructure-agnostic provisioning, enabling consistent cluster creation across diverse environments like Nutanix AHV and Amazon EKS.” This ensures that the same CAPI-based workflow can deploy clusters on both on-prem Nutanix and cloud-based EKS.

Incorrect Options:

A. Increases security from a single point of entry: A bastion host, not a bootstrap cluster, provides a single point of entry for security. The bootstrap cluster is temporary and focuses on provisioning.

B. Simplifies the networking requirements for Kubernetes: Networking is managed by the target cluster’s CNI (e.g., Calico), not the bootstrap cluster.

C. Saves cost by minimizing resources required for provisioning: The bootstrap cluster is temporary and does not significantly impact costs; its purpose is provisioning, not cost-saving.

NKP uses the Cluster Autoscaler to scale worker node replicas up or down.This ensures that resource availability dynamically matches workload demand by adjusting the number of worker nodes. Pod-level autoscaling (Horizontal-Pod autoscaler) is also supported for pod scaling but is not responsible for node pool expansion or compaction.

Key Reference:

“NKP uses the Cluster Autoscaler to dynamically adjust worker node pool replicas in response to cluster resource demands.”

TheNKPA 6.10 documentationoutlines that in air-gapped environments where default pod network CIDR conflicts exist, the cluster manifest (created via the nkp create cluster command) should be updated to specify an alternate, non-conflicting pod CIDR block range before deployment.

For deployments in air-gapped environments where there is no external Internet connectivity, the --airgapped parameter is required. This instructs the NKP deployment to rely solely on internal resources, using pre-staged images and local container registries, ensuring that no external network dependencies cause deployment failures.

For creating custom images for vSphere (and other supported platforms),Konvoy Image Builder(KIB) is the officially supported tool for NKP. It can create images with custom configurations, package versions, and pre-bundled artifacts.

Key Reference:

“Konvoy Image Builder (KIB) is the Nutanix-recommended tool for building NKP cluster node images for vSphere, AWS, Azure, and other environments.”

The documentation confirms that when a new license is activated to upgrade to a higher tier, users mustlog out and log back infor the license changes to take effect. This ensures that updated entitlements are loaded into the UI and CLI environment.

Exact extract from documentation:

“After applying a new license for a higher-tier product, log out and log back in to see and activate the newly available features.”

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.

When an Amazon EKS cluster is attached to NKP for fleet management, NKP uses GitOps principles, leveragingFlux(a GitOps operator) to synchronize application deployments and configurations from a management Git repository to the attached cluster. The NKPA course explains that detaching a cluster from NKP removes it from the NKP management plane, but the Flux installation on the cluster may continue to reconcile with the Git repository, causing application changes to persist post-detachment.

To resolve this, the engineer must manually disconnect the Flux installation by suspending the Git repository reconciliation. The correct command, as per the NKPA course, is: kubectl -n kommmander-flux patch gitrepo management -p '{"spec":{"suspend":true}}' --type merge. This command suspends Flux’s synchronization with the management Git repository, stopping further application updates. The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “After detaching an external cluster from NKP, the Flux GitOps operator may continue to apply changes unless its GitRepo resource is suspended using kubectl patch in the kommmander-flux namespace.”

Incorrect Options:

A. Forcefully detach EKS cluster: The --force flag is not a standard option for the nkp detach cluster command, and forceful detachment does not address the Flux reconciliation issue.

B. Detached cluster must also be deleted from NKP: The cluster is already detached, and deletion is not necessary to stop GitOps updates. The issue lies with Flux, not NKP’s state.

C. Developers must have some bad configuration: The issue is not with developer configurations but with Flux’s ongoing synchronization, as explained in the NKPA course.

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.”

The exhibit shows a YAML manifest for a NodeGroup resource that has autoscaler-related annotations:

yaml

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cluster.x-k8s.io/cluster-api-autoscaler-node-group-min-size: "3"

cluster.x-k8s.io/cluster-api-autoscaler-node-group-max-size: "15"

According to theNKPA 6.10 documentation, these annotations configure theminimumandmaximumnumber of nodes for the autoscaler in the specified NodeGroup. The autoscaler will ensure the number of nodes never goes below the minimum (3) and never exceeds the maximum (15).

Key Reference:

"The cluster-autoscaler will scale the NodeGroup up to the maximum size and down to the minimum size based on workload requirements."