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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 KCNA (Kubernetes and Cloud Native Associate) Certification Exam is a professional certification program designed for individuals who want to validate their skills and knowledge in Kubernetes and cloud native technologies. KCNA exam is developed and maintained by the Linux Foundation, a nonprofit organization that supports the growth of open-source software and promotes standardization and collaboration among software developers.

Linux Foundation KCNA Exam is a certification program that validates an individual’s knowledge of Kubernetes and cloud-native technologies. KCNA exam is designed to be challenging and is suitable for IT professionals who are interested in working with these technologies. Kubernetes and Cloud Native Associate certification is recognized by leading companies in the tech industry and can help individuals advance their career and increase their earning potential. Candidates are encouraged to prepare thoroughly before attempting the exam to ensure success.

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Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q73-Q78):

NEW QUESTION # 73
What does the 'kops' acronym means?

A. Kubernetes Operation Policy Specification
B. Kubernetes Operations
C. Kubernetes Operators
D. Kubernetes Open Platform Specification

Answer: B

Explanation:
https://github.com/kubernetes/kops

NEW QUESTION # 74
You have configured Prometheus to scrape metrics from a Kubernetes cluster, but you notice that some pods are not being scraped. You suspect that the Prometheus server might be experiencing resource constraints. How can you troubleshoot this issue?

A. Verify the Prometheus server's configuration and ensure that the scraping interval and target labels are correct.
B. Check the Prometheus logs for any errors related to scraping or resource limitations.
C. All of the above
D. Use the Prometheus •status/targets• endpoint to see which targets are currently being scraped and any errors encountered.
E. Examine the Prometheus server's CPU and memory usage to identify any resource bottlenecks.

Answer: A,B,C,D,E

Explanation:
All of the mentioned options are valuable for troubleshooting scraping issues caused by resource constraints. Checking logs, monitoring server resource usage, reviewing configuration, and using the 'status/targetS endpoint provide comprehensive insights into the problem. By investigating these aspects, you can pinpoint the root cause and take appropriate actions to resolve the issue.

NEW QUESTION # 75
What kind of limitation cgroups allows?

A. Prioritization
B. Server cpu and memory
C. Control
D. None of the options
E. Resource limiting
F. Accounting

Answer: A,C,E,F

NEW QUESTION # 76
You have a Kubernetes cluster running on Google Kubernetes Engine (GKE). Your application requires persistent storage for its dat
a. Which GKE feature would you use to provision persistent volumes for your pods?

A. PodDisruptionBudget
B. PersistentVolumeClaim
C. NodePort
D. StatefulSet
E. PersistentDisk

Answer: B

Explanation:
PersistentVolumeClaim (PVC) is the primary mechanism for requesting persistent storage in Kubernetes. It allows pods to request a specific amount of storage with desired access modes (Read-Only, ReadWriteOnce, ReadWriteMany). GKE integrates with PVCs to provision persistent volumes from underlying storage solutions like Google Cloud Persistent Disks.

NEW QUESTION # 77
Explain the difference between a Deployment and a StatefulSet in Kubernetes.

A. Deployments handle rolling updates, while StatefulSets only support manual updates.
B. Deployments are used for deploying and managing stateless applications, while StatefulSets are used for deploying and managing stateful applications.
C. Deployments are used for managing the lifecycle of a single Pod, while StatefulSets manage multiple Pods.
D. Deployments are used for stateless applications, while StatefulSets are used for stateful applications that require persistent storage and unique identities.
E. Deployments are responsible for scheduling Pods, while StatefulSets manage the lifecycle of Services.

Answer: B,D

Explanation:
Deployments are used for deploying and managing stateless applications, while StatefulSets are used for deploying and managing stateful applications. Deployments are ideal for applications where the state of each Pod is not important, while StatefulSets are designed for applications that require persistent storage, unique network identities, and ordered scaling.

NEW QUESTION # 78
......

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Valid KCNA Test Book, Valid KCNA Torrent

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Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q73-Q78):

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