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 the OS 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 the NKPA 6.10 documentation , Rook Ceph is the recommended out-of-the-box storage solution integrated with NKP for persistent data storage, backups, and object storage within the Kubernetes environment.

Key Reference:

“Rook Ceph is integrated with NKP for providing persistent storage and backup support within the cluster.”

The NKPA course explains that by default, NKP creates new AWS infrastructure (VPC, subnets, ELBs) when deploying a cluster on AWS. However, NKP supports deploying clusters on existing AWS infrastructure by providing custom configurations. The recommended method using the NKP CLI is to create an overrides file specifying the pre-existing VPC, subnets, and ELB, and then pass this file to the nkp create cluster aws command using the --overrides parameter.

The overrides file (e.g., aws-infra-overrides.yaml) contains details like vpcID, subnetIDs, and loadBalancerIDs, which NKP uses to deploy the cluster on the specified infrastructure instead of creating new resources. For example:

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aws:

vpcID: vpc-12345678

subnetIDs:

- subnet-12345678

- subnet-87654321

loadBalancerIDs:

- elb-12345678

The engineer then runs: nkp create cluster aws --overrides aws-infra-overrides.yaml.

The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “To deploy an NKP cluster on existing AWS infrastructure, create an overrides file with the pre-existing VPC, subnets, and ELB details, and use the --overrides parameter with the nkp create cluster aws command to apply the custom configuration.” This method ensures the AWS team’s requirement is met while leveraging NKP’s CLI for deployment.

Incorrect Options :

A. nkp adopt infrastructure aws : There is no nkp adopt infrastructure command in NKP for this purpose.

C. Use the NKP UI : While the UI allows specifying infrastructure details, the question focuses on the CLI-based deployment, and the UI method is less relevant here.

D. Include parameters directly in nkp create cluster aws : The nkp create cluster aws command does not support direct parameters for VPC, subnets, and ELB; it requires an overrides file.

NKP Platform Applications (e.g., Rook Ceph, Prometheus, Fluent Bit) are pre-integrated tools that can be deployed to Kubernetes clusters within a workspace to provide services like storage, monitoring, and logging. The NKPA course specifies that to deploy a platform application to all clusters in a workspace from the command line, the engineer uses the nkp create appdeployment command. This command creates an application deployment resource that targets the specified workspace and clusters.

The required parameters include the application ID (to identify the platform application), the version (to specify the desired version of the application), and the NKP workspace (to define the scope of clusters). For example: nkp create appdeployment --app-id prometheus --version 2.30.0 --workspace fin-vd. The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “Use the nkp create appdeployment command to deploy platform applications, specifying the application ID, version, and target workspace to apply the deployment across all clusters in that workspace.”

Incorrect Options :

B. nkp deploy platform-app : This is not a valid NKP command. The correct command is nkp create appdeployment.

C. nkp deploy app : This is not a recognized command in the NKPA documentation.

D. kubectl create appdeployment : kubectl interacts with Kubernetes resources, not NKP-specific platform applications.

According to the NKPA 6.10 documentation , the Pre-provisioned infrastructure provider (CAPPP) requires the user to provide an inventory file of the servers that will become the cluster nodes. This inventory file contains connection information (IP addresses, credentials, etc.) for each pre-provisioned node, enabling the Cluster API to connect and configure these servers directly during cluster creation.

For deploying NKP clusters in AWS, setting the AWS_REGION environment variable is a key prerequisite to ensure that the AWS CLI and underlying deployment scripts know which region to target. This is essential for provisioning instances using the specified AMI.

Exact extract:

“Set the AWS_REGION environment variable to the appropriate region prior to deploying clusters to ensure proper interaction with the AWS API.”

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.”

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 to create 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 addresses resource contention in Kubernetes clusters, where one application (e.g., ApplicationB) consumes excessive resources, impacting others (e.g., ApplicationA). To mitigate this, the course recommends implementing Quotas and Limit Ranges .

Resource Quotas restrict the total amount of CPU, memory, and other resources a namespace can consume, ensuring fair resource allocation across teams.

Limit Ranges set minimum and maximum resource limits for individual pods and containers within a namespace, preventing any single application from monopolizing resources.

The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “To prevent resource contention in NKP clusters, apply Resource Quotas to limit namespace resource usage and Limit Ranges to enforce pod and container resource boundaries.” For example, the administrator can create a ResourceQuota to cap ApplicationB’s namespace resource usage and a LimitRange to restrict its pod resource requests/limits, ensuring ApplicationA has sufficient resources.

Incorrect Options :

B. Setting up Network Policies : Network Policies control network traffic, not resource usage.

C. Configuring RBAC : RBAC manages access permissions, not resource allocation.

D. Implementing Continuous Deployment (CD) : CD automates deployments but does not address resource contention.

NKP uses Cluster API (CAPI) to provision and manage Kubernetes clusters across supported infrastructures, including Nutanix AHV, vSphere, AWS, and GCP. CAPI components, such as controllers and providers, are deployed to manage the lifecycle of clusters on these platforms. However, when NKP attaches to a managed Kubernetes service like Azure Kubernetes Service (AKS), CAPI components are not deployed because AKS is managed by Azure, and NKP only integrates with the cluster for fleet management, not provisioning.

The NKPA course explains: “For managed Kubernetes services like AKS, NKP attaches the cluster to its management plane without deploying CAPI components, as the underlying infrastructure is managed by the cloud provider.” The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide reinforces this: “CAPI is used for NKP-managed clusters on Nutanix, vSphere, AWS, and GCP, but not for attached managed services like AKS.”

Incorrect Options :

A. vSphere : NKP deploys CAPI components (e.g., CAPV provider) to manage vSphere-based clusters.

B. GCP : NKP deploys CAPI components (e.g., CAPG provider) for GCP-based clusters.

C. Nutanix : NKP deploys CAPI components (e.g., CAPA provider for AHV) for Nutanix AHV clusters.