Nutanix NCP-CN Exam With Confidence Using Practice Dumps

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.

Attaching an existing Amazon EKS cluster to NKP for fleet management involves integrating the cluster into NKP’s management plane, which requires specific preparatory steps. The NKPA course outlines that the first step is tocreate a service account with cluster-admin permissionsin the EKS cluster. This service account is used by NKP to authenticate and manage the cluster, enabling operations like monitoring, scaling, and application deployment.

The Nutanix Cloud Native (NCP-CN) 6.10 Study Guide explains: “To attach an external Kubernetes cluster, such as Amazon EKS, to NKP, a service account with cluster-admin role bindings must be created to allow NKP to interact with the cluster’s API server.” The service account is configured with a token that NKP uses to authenticate requests. The NKPA course provides detailed steps, including creating the service account, assigning the cluster-admin ClusterRole, and generating a token for NKP integration. This step is critical to ensure NKP has the necessary permissions to manage the EKS cluster.

Incorrect Options:

A. Configure a ConfigMap according to EKS configuration: While ConfigMaps may be used for specific configurations, they are not the first step for attaching an EKS cluster. The NKPA course prioritizes service account creation.

C. Configure HAProxy to get connected to EKS clusters: HAProxy is a load balancer, not required for attaching EKS clusters to NKP. EKS uses AWS-native load balancers, and NKP connects via the Kubernetes API.

D. Deploy cert-manager in the EKS clusters: Cert-manager is used for certificate management, not a prerequisite for attaching EKS clusters. The NKPA course does not list it as a required step.

The NKPA course highlights thatNKP Insightsis 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.