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Linux Foundation Kubernetes and Cloud Native Associate (KCNA) Certification Exam is a highly regarded certification that demonstrates an individual's understanding of Kubernetes and cloud-native technologies. The KCNA certification exam is designed to test a candidate's knowledge of Kubernetes architecture, deployment, and maintenance, as well as the fundamental concepts of cloud-native computing. Kubernetes and Cloud Native Associate certification is valuable for individuals who want to validate their skills in Kubernetes and cloud-native technologies, such as cloud engineers, DevOps engineers, software developers, and system administrators.

Linux Foundation has been providing certification exams to individuals who want to demonstrate their expertise in open source technologies. One of their newest offerings is the KCNA (Kubernetes and Cloud Native Associate) Certification Exam. KCNA exam is designed for individuals who want to prove their knowledge and skills in cloud native computing and Kubernetes.

Linux Foundation KCNA Certification Exam is a vendor-neutral certification program, which means that it is not tied to any specific cloud platform or technology vendor. This makes it an excellent choice for IT professionals who want to demonstrate their expertise in Kubernetes and cloud native technologies without being limited by proprietary technologies or vendor lock-in.

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Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q170-Q175):

NEW QUESTION # 170
You are running a large-scale, microservice-based application in Kubernetes, and you are using HorizontalPodAutoscalers (HPAs) for automatic scaling. Which of the following statements about resource utilization monitoring in this scenario is true?

A. It is essential to monitor resource utilization at both the Pod and namespace levels to get a comprehensive view of resource usage and optimize scaling
B. Resource utilization monitoring is not critical in Kubernetes as the system automatically manages resource allocation and scaling.
C. Monitoring resource utilization at the node level is sufficient for scaling individual microservices.
D. Monitoring resource utilization is only necessary during peak load periods, not during normal operations.
E. Monitoring resource utilization at the Pod level provides sufficient insights for overall application health and scaling decisions-

Answer: A

Explanation:
Monitoring resource utilization at both the Pod and namespace levels provides a comprehensive understanding of resource usage. Monitoring Pods allows you to identify resource-intensive services and fine-tune their scaling behavior. Monitoring namespaces helps you understand the overall resource consumption and optimize scaling across the entire application. This is crucial in large-scale microservice deployments where resources can be easily exhausted if not carefully monitored

NEW QUESTION # 171
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 'podAffinity' field to group pods with GPU requirements together.
B. Use the 'resources' field to specify the GPU requirements in the container's definition.
C. Use the 'affinity' field to prefer nodes with the 'GPU* label.
D. Use the 'nodeSelector' field to target nodes with the 'gpu' label.
E. Use the 'tolerations' field to tolerate the 'GPU' taint.

Answer: B

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 # 172
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. Ingress
B. Deployment
C. Pod Security Policy
D. Node Affinity
E. Service

Answer: D

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 # 173
What Kubernetes resource would allow you to run one Pod on some of your Nodes?

A. ClusterSet
B. Deployment
C. DaemonSet
D. ReplicaSet

Answer: C

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

NEW QUESTION # 174
What is the purpose of the 'kube-proxy' component in Kubernetes and how does it contribute to the networking model?

A. kube-proxy acts as a network load balancer for Kubernetes services, distributing traffic among pods.
B. kube-proxy is responsible for managing network connectivity between pods and external services.
C. kube-proxy provides network security features by enforcing network policies and firewall rules.
D. kube-proxy enables communication between pods within the same namespace, ensuring they can access each others services.
E. kube-proxy implements the Kubernetes DNS service, resolving hostnames to IP addresses for pods within the cluster.

Answer: A

Explanation:
kube-proxy is a critical component in Kubernetes' networking model. Its primary role is to act as a network load balancer for Kubernetes services. It listens on the node's IP address and forwards traffic to the corresponding pods based on service rules. This allows for load balancing, service discovery and efficient communication between pods and external clients. Options A, C, D, and E are incorrect. While kube-proxy contributes to external connectivity its core responsibility is internal load balancing. Communication within a namespace relies on the pod network, not kube-proxy. DNS resolution is handled by CoreDNS in Kubernetes, not kube-proxy. Security features like NetworkPolicies are implemented separately.

NEW QUESTION # 175
......

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