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Linux Foundation KCNA Certification is recognized globally as a mark of excellence in cloud-native computing. It is an industry-recognized certification that demonstrates a candidate's expertise in Kubernetes and cloud-native technologies. Kubernetes and Cloud Native Associate certification is ideal for individuals who are seeking to enhance their career prospects in the field of cloud-native computing.

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Linux Foundation KCNA (Kubernetes and Cloud Native Associate) Certification Exam is a highly sought-after certification for individuals who wish to establish their expertise in cloud-native computing technologies. Kubernetes is an open-source platform that manages containerized applications, while cloud-native computing is an approach to building and running applications that takes full advantage of cloud computing models. Kubernetes and Cloud Native Associate certification exam is designed to validate the skills and knowledge of professionals who are seeking a career in cloud-native computing.

Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q154-Q159):

NEW QUESTION # 154
Which control plane component is responsible for scheduling pods?

A. kube api-server
B. kubelet
C. kube scheduler
D. kube-proxy

Answer: C

Explanation:
https://kubernetes.io/docs/concepts/overview/components/

NEW QUESTION # 155
'kubectl delete -n my-ns po,svc --all' will delete pods and services including uninitialized ones in the namespace 'my-ns'

A. TRUE
B. FALSE

Answer: A

Explanation:
https://kubernetes.io/docs/reference/generated/kubectl/kubectl-commands#delete

NEW QUESTION # 156
You're managing a Kubernetes cluster with several deployments using resource requests and limits. Which of the following strategies can help you effectively manage resource utilization and potentially reduce costs?

A. Utilize resource quotas to restrict the total resources that can be consumed by namespaces.
B. Set resource limits lower than requests to encourage efficient resource use.
C. Configure resource reservation to ensure a minimum amount of resources is always available.
D. Use Horizontal Pod Autoscaler (HPA) to adjust the number of pods based on resource utilization and load.
E. Increase resource requests for all deployments to ensure enough resources are always available.

Answer: A,C,D

Explanation:
The most effective strategies for managing resource utilization and cost in Kubernetes involve dynamic scaling and resource allocation. Horizontal Pod Autoscaler (HPA) allows you to adjust the number of pods based on resource utilization, reducing overprovisioning. Resource quotas restrict the total resources that can be consumed by namespaces, preventing resource exhaustion and potential cost spikes. Resource reservation guarantees a minimum amount of resources for critical applications, ensuring they perform well even under high load. Increasing requests without adjusting limits can lead to overprovisioning, while setting limits lower than requests can limit pod performance.

NEW QUESTION # 157
Flux is built using which toolkit?

A. GitOps
B. DevOps
C. CI/CD
D. DevSecOps

Answer: A

Explanation:
https://fluxcd.io/

NEW QUESTION # 158
You're developing a serverless application using AWS Lambda that requires access to environment variables for configuration purposes. How would you securely manage and access these environment variables within your Lambda functions?

A. Store environment variables directly in the Lambda function's code.
B. Use AWS Secrets Manager to store and retrieve sensitive environment variables.
C. Utilize AWS Parameter Store to manage environment variables as parameters.
D. Store environment variables in a separate file and upload it along with the Lambda function's code.
E. Configure environment variables within the AWS Lambda console.

Answer: B,C

Explanation:
The most secure and recommended approaches for managing environment variables in AWS Lambda are to use AWS Secrets Manager (B) and AWS Parameter Store (D). Secrets Manager is specifically designed for storing and retrieving sensitive data like API keys, passwords, and other confidential information. Parameter Store allows you to manage configuration parameters, including environment variables, in a centralized and hierarchical manner. Storing environment variables directly in the code (A) is insecure. Configuring them in the Lambda console (C) is not suitable for managing sensitive data. Storing them in a separate file (E) is less secure and less manageable.

NEW QUESTION # 159
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