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Linux Foundation KCNA (Kubernetes and Cloud Native Associate) Certification Exam is a globally recognized certification exam that validates the skills and knowledge of IT professionals in cloud-native application development and deployment. KCNA exam is designed to assess the candidate's understanding of Kubernetes and other cloud-native technologies, including containerization, microservices, and serverless computing. Kubernetes and Cloud Native Associate certification is an entry-level credential that helps IT professionals advance their careers in the cloud-native industry.

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 (Q109-Q114):

NEW QUESTION # 109
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. StatefulSet
B. PodDisruptionBudget
C. PersistentDisk
D. PersistentVolumeClaim
E. NodePort

Answer: D

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 # 110
You have a Kubernetes Deployment that defines 3 replicas of your application. During a deployment, one of the replicas fails to start. What happens to the deployment?

A. The deployment continues, but with only 2 healthy replicas.
B. Kubernetes automatically restarts the failed replica.
C. The deployment scales down to 2 replicas.
D. The deployment fails and rolls back to the previous version.
E. The deployment remains in a failed state.

Answer: B

Explanation:
Kubernetes' self-healing capabilities ensure high availability. If a pod fails, Kubernetes will automatically restart it, attempting to bring the deployment back to the desired replica count.

NEW QUESTION # 111
You are running a highly sensitive application in Kubernetes. Which of the following security measures is MOST effective in preventing unauthorized access to your application's secrets?

A. Employing a secrets management solution like HashiCorp Vault or AWS Secrets Manager.
B. Deploying your application in a private Kubernetes cluster.
C. Using the '-privileged' flag for your application's container.
D. Disabling Kubernetes RBAC and granting full access to all users.
E. Configuring strong passwords for all Kubernetes users.

Answer: A

Explanation:
Using a secrets management solution like HashiCorp Vault or AWS Secrets Manager is the most effective approach to securely storing and managing secrets in a Kubernetes environment. These solutions offer strong encryption, access control, and audit logging, providing comprehensive protection for your application's sensitive data.

NEW QUESTION # 112
Consider the following Kubernetes resource definition:

What does the "resources" section define in this Deployment manifest?

A. The network bandwidth allocated to the pod
B. The number of CPU cores and memory available on the node
C. The number of replicas that Kubernetes should create for the Deployment
D. The minimum and maximum resource requirements for the container
E. The storage capacity required for the pod

Answer: D

Explanation:
The "resources" section in the Deployment manifest defines the minimum (requests) and maximum (limits) resource requirements for the container This helps Kubernetes schedule pods effectively and prevents resource starvation or excessive resource consumption by individual pods.

NEW QUESTION # 113
You are troubleshooting a performance issue with an application running in a Kubernetes cluster. You have access to Prometheus and Jaeger, but the Jaeger Ul shows that a specific request took an unusually long time to process. Which metric in Prometheus can help you identify the specific component or service within the application that caused the delay?

A. kube_pod_container_status_restart_count
B. kube_pod_status_phase
C. kube_pod_container_resource_requests_cpu_cores
D. http_request_duration_seconds
E. kube_deployment_status_replicas

Answer: D

Explanation:
The correct answer is E . The metric 'http_request_duration_seconds* is typically used to track the time taken for HTTP requests to be processed. In this case, by looking at the 'http_request_duration_seconds' metric for the specific request identified in Jaeger, you can see the duration of each stage of the request processing. This can pinpoint the specific component or service where the delay occurred. The other options are not relevant to identifying the specific component or service causing the delay: A : Shows CPU resource requests for a pod. B : Shows the pod's phase. C : Shows the number of replicas in a deployment. D : Shows the restart count for a pod's containers. These metrics do not provide information about the processing time of individual requests.

NEW QUESTION # 114
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