Nutanix Updated NCP-CN Exam Questions and Answers by emmanuel

Comprehensive and Detailed Explanation:

The NKP Pro licensing tier includes Fleet Management, which enables centralized lifecycle management of multiple Kubernetes clusters. This feature is critical for managing larger environments, providing visibility and control over fleet-wide configurations and updates. Other features, like AI OPS and advanced observability, are typically associated with higher tiers (e.g., Ultimate).

The NKPA course highlights that NKP Insights is the platform’s integrated solution for observability and analytics, providing predictive analytics to detect current and future anomalies in Kubernetes clusters. NKP Insights leverages machine learning to analyze metrics, logs, and events, identifying performance issues and potential failures proactively. After deploying a new cluster, the administrator can enable NKP Insights as a platform application in the workspace to meet the predictive analytics requirement.

The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide states: “NKP Insights provides predictive analytics and anomaly detection for Kubernetes clusters, enabling administrators to monitor and optimize cluster performance.” This is deployed via the NKP UI or CLI by enabling the Insights application in the workspace.

Incorrect Options:

B. NCM Intelligent Ops: Nutanix Cloud Manager (NCM) Intelligent Ops is for broader infrastructure management, not Kubernetes-specific analytics.

C. Nutanix Pulse: Pulse is a telemetry service for Nutanix support, not for analytics.

D. NKP AI Navigator: This is not a recognized NKP component in the NKPA documentation.

According to the NKPA 6.10 documentation, licensing in an NKP cluster is constrained by the total number of vCPUs assigned to all nodes (workers and control planes). In this scenario, the cluster has a maximum of 150 vCPUs available.

The existing output shows 10 worker nodes, each with 8 vCPUs (10×8=80 vCPUs) and 3 control plane nodes, each with 4 vCPUs (3×4=12 vCPUs).

Current vCPU usage: 80 + 12 = 92 vCPUs.

Remaining vCPUs: 150 - 92 = 58 vCPUs.

Option A:

Adding 6 control plane nodes (6×4=24 vCPUs).

This would increase control planes to 9 total (3 existing + 6 new). Control plane nodes would consume 9×4=36 vCPUs.

Worker nodes remain at 80 vCPUs.

Total vCPU usage: 36 + 80 = 116 vCPUs (still under 150 vCPUs).

However, it’s unusual and unnecessary to have 9 control planes in a typical NKP setup. NKPA and NCP-CN best practices indicate typically no more than 3 or 5 control planes for HA. Therefore, this is technically possible but not recommended or standard practice. So not selected.

Option B:

Expanding the existing worker nodepool by 8 nodes (8×8=64 vCPUs).

This would add 64 vCPUs to the current 92 vCPUs:

92 + 64 = 156 vCPUs → exceeds licensing limit.

Correction: The question specifies “expand up to 8 nodes,” so it’s possible to expand by only 7 nodes (7×8=56 vCPUs).

92 + 56 = 148 vCPUs → within licensing limits.

Thus, expanding by up to 7 nodes is valid.

Option C:

Creating a new worker nodepool with 10 nodes (10×8=80 vCPUs).

This would add 80 vCPUs to the existing 92 vCPUs:

92 + 80 = 172 vCPUs → exceeds 150 vCPU licensing limit.

Not valid.

Option D:

Expanding the original worker nodepool by up to 4 nodes (4×8=32 vCPUs) = +32 vCPUs.

Adding a new nodepool of 6 nodes with 4 vCPUs/node (6×4=24 vCPUs) = +24 vCPUs.

Total increase: 32 + 24 = 56 vCPUs.

Total vCPU usage: 92 + 56 = 148 vCPUs → within the 150 vCPU limit.

Thus, valid.

Extract Reference:

NKPA 6.10 – “Cluster Sizing and Licensing”

Nutanix Kubernetes Platform Administration (NKPA) – Licensing Considerations

"The total number of vCPUs for all nodes (control planes and workers) must not exceed the licensed vCPU capacity of the NKP deployment."

This confirms that Options B and D are the two valid approaches to expand the cluster while remaining compliant with licensing constraints.

The NKPA course details that NKP Platform Applications, such as Grafana Logging, Grafana Loki, and Project 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 the Application section under 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.