KCNA NEW EXAM CAMP, KCNA NEW REAL TEST

KCNA New Exam Camp, KCNA New Real Test

KCNA New Exam Camp, KCNA New Real Test

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Tags: KCNA New Exam Camp, KCNA New Real Test, Latest KCNA Exam Registration, KCNA Valid Test Vce, Exam KCNA Assessment

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Linux Foundation KCNA (Kubernetes and Cloud Native Associate) Certification Exam is a professional certification exam that validates the skills and knowledge of individuals in the field of Kubernetes and cloud native technologies. KCNA exam is designed for individuals who are interested in learning and mastering the fundamentals of Kubernetes and cloud native technologies, and who wish to demonstrate their expertise in these areas to potential employers.

Linux Foundation has released a new certification exam called KCNA (Kubernetes and Cloud Native Associate) Certification Exam. Kubernetes and Cloud Native Associate certification exam is designed to test an individual's knowledge and skills in Kubernetes and cloud-native technologies. It is an entry-level certification that is perfect for those who are looking to start a career in the field of cloud computing.

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Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q102-Q107):

NEW QUESTION # 102
Consider the following Kubernetes YAML file representing a deployment:

What is the primary benefit of using a GitOps approach to manage this deployment compared to traditional methods?

  • A. GitOps provides faster deployment times by eliminating the need for manual interventions.
  • B. GitOps simplifies the process of managing complex Kubernetes deployments by providing a centralized repository for configuration.
  • C. GitOps enables easy rollbacks to previous deployments by leveraging the versioning capabilities of Git.
  • D. GitOps enhances security by preventing unauthorized changes to the Kubernetes cluster.
  • E. GitOps automates the deployment process, eliminating the need for human intervention.

Answer: C

Explanation:
GitOps leverages Git's version control system, providing a history of changes to your cluster's configuration. This enables easy rollbacks to previous deployments by simply reverting to a specific commit in the Git repository, making it easier to recover from errors or unwanted changes.


NEW QUESTION # 103
What is the use of labels in Kubernetes?

  • A. All of the options
  • B. It is used to assign annotation to an object
  • C. It is used to assign a name to an object.
  • D. It is used to assign key-value pair to an object

Answer: D

Explanation:
https://kubernetes.io/docs/concepts/overview/working-with-objects/labels/


NEW QUESTION # 104
Stateful set requires which service for the network identity of pods?

  • A. Load Balancer Service
  • B. Ingress
  • C. Headless Service

Answer: C

Explanation:
https://kubernetes.io/docs/concepts/workloads/controllers/statefulset/


NEW QUESTION # 105
Which of the following best describes the way kubernetes Role-based access control (RBAC) works?

  • A. Kubernetes RBAC states which users can perform which actions against which re-source
  • B. Kubernetes does not do RBAC
  • C. Kubernetes RBAC is responsible for authenticating subjects such as users and groups
  • D. Kubernetes RBAC lists which operations on which resources are denied to users

Answer: A

Explanation:
https://kubernetes.io/docs/reference/access-authn-authz/rbac/


NEW QUESTION # 106
You need to deploy a pod that requires access to a specific GPU device. How can you ensure that
the pod is scheduled on a node with the required GPU?

  • A. Use the 'tolerations' field to tolerate the 'GPU' taint.
  • B. Use the 'podAffinity' field to group pods with GPU requirements together.
  • C. Use the 'nodeSelector' field to target nodes with the 'gpu' label.
  • D. Use the 'affinity' field to prefer nodes with the 'GPU* label.
  • E. Use the 'resources' field to specify the GPU requirements in the container's definition.

Answer: E

Explanation:
You can use both the •nodeselector• and •resources' fields to achieve this: 'nodeselector•: Targets nodes with a label indicating the presence of GPUs (e.g., •gpu: true). •resources': Specify the GPU resource requirements within the container's definition. This provides a more precise way to request specific GPUs and their capabilities. While •tolerations' and 'affinity' can be used for other scheduling needs, they are not directly designed for GPU resource allocation.


NEW QUESTION # 107
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