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Answers Linux Foundation KCNA Free - KCNA Reliable Braindumps

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The KCNA exam covers a broad range of topics related to Kubernetes and cloud-native technologies, including containerization, pod management, services and networking, storage management, security, and troubleshooting. KCNA exam is designed to test candidates' abilities to deploy Kubernetes clusters, manage containerized applications, and troubleshoot common issues that arise in a cloud-native environment. Successful candidates will receive the KCNA Certification, which demonstrates their proficiency in cloud-native technologies and their ability to work with Kubernetes effectively. Overall, the KCNA exam is an excellent opportunity for IT professionals to enhance their skills and demonstrate their expertise in one of the fastest-growing areas of the technology industry.

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KCNA Reliable Braindumps - Reliable KCNA Test Preparation

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Linux Foundation KCNA (Kubernetes and Cloud Native Associate) Exam is a certification program designed to test the knowledge and skills of individuals who are working with Kubernetes and other cloud-native technologies. Kubernetes has become the de facto standard for container orchestration, and with the increasing adoption of cloud-native technologies, the demand for certified professionals is on the rise.

Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q174-Q179):

NEW QUESTION # 174
You're running a Kubernetes cluster with several applications, and you want to analyze the performance of your applications at the Kubernetes cluster level. What are the key metrics you should monitor to gain insights into cluster-wide performance?

A. Total CPU and memory usage across all nodes in the cluster.
B. Number of pods running in each namespace.
C. Number of failed deployments and pod restarts.
D. Latency and throughput of requests to the Kubernetes API server.
E. Number of active Kubernetes controllers (e.g., Deployment, ReplicaSet).

Answer: A,C,D,E

Explanation:
The correct answers are B, C, D, and E . These metrics are crucial for understanding the overall performance of your Kubernetes cluster. B: Total CPU and memory usage across all nodes in the cluster. This metric helps you assess the overall resource consumption of your cluster. If the CPU or memory utilization consistently reaches high levels, it might indicate resource constraints, performance bottlenecks, or potential capacity planning issues. C: Number of failed deployments and pod restarts. This metric provides insights into the stability and reliability of your applications. Frequent deployment failures or pod restarts might indicate issues with application code, deployment configurations, or underlying infrastructure. D: Latency and throughput of requests to the Kubernetes API server. The Kubernetes API server handles all requests to manage the cluster. Monitoring API server latency and throughput can help identify performance bottlenecks and potential issues with cluster communication. E: Number of active Kubernetes controllers (e.g., Deployment, ReplicaSet). Kubernetes controllers are responsible for managing and maintaining the state of your applications. Tracking the number of active controllers can help you identify potential issues with controller activity, such as resource exhaustion or unexpected controller behavior. Option A is not as crucial for cluster-wide performance analysis. While knowing the number of pods running in each namespace might be useful for resource allocation, it doesn't directly reflect the overall performance of the cluster.

NEW QUESTION # 175
You are running a Kubernetes cluster with multiple nodes. Your application's Pods need to be scheduled across different nodes for high availability. Which Kubernetes concept allows you to control the distribution of Pods across the cluster?

A. Deployment
B. Pod Security Policy
C. Service
D. Ingress
E. Node Affinity

Answer: E

Explanation:
Node Affinity lets you define rules to control where your Pods are scheduled. You can specify hard (required) or soft (preferred) preferences for nodes based on labels or other criteria. This helps to distribute Pods across the cluster for better resource utilization and fault tolerance.

NEW QUESTION # 176
Which of the following is used to request storage in Kubernetes?

A. Container Storage Interface 'CSI'
B. PersistentVolumeClaim 'PVC'
C. PersistentVolume 'PV'
D. StorageClasses

Answer: B

Explanation:
https://kubernetes.io/docs/concepts/storage/persistent-volumes/

NEW QUESTION # 177
Your application is deployed in a Kubernetes cluster and is experiencing performance issues. You need to monitor the health of the cluster and identify potential bottlenecks. Which Kubernetes features would be most helpful for diagnosing and resolving these issues?

A. All of the above
B. Kubernetes Dashboard for visual overview of cluster status
C. kubectl logs and kubectl describe
D. Jaeger for tracing distributed requests
E. Prometheus and Grafana for metrics collection and visualization

Answer: A

Explanation:
All of the mentioned features contribute to effective cluster monitoring and debugging: 'kubectl logs and 'kubectl describe' provide valuable information about specific Pods and their resources. Prometheus and Grafana allow you to collect and analyze metrics from various components of the cluster, helping you identify performance bottlenecks. Kubernetes Dashboard offers a visual overview of the cluster's state and resources. Jaeger is a powerful tool for tracing distributed requests across different microservices within your application, helping you diagnose issues that involve communication between services.

NEW QUESTION # 178
What is a benefits of Kubernetes federation?

A. Creates highly available clusters in different regions
B. Avoids scalability limits on pods and nodes
C. Low latency

Answer: A,B,C

NEW QUESTION # 179
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