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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.
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NEW QUESTION # 255
What Kubernetes control plane component exposes the programmatic interface used to create, manage and interact with the Kubernetes objects?
Answer: A
NEW QUESTION # 256
What edge and service proxy tool is designed to be integrated with cloud native applications?
Answer: C
Explanation:
Envoy is a high-performance edge and service proxy designed for cloud native applications, often used in service mesh architectures.
NEW QUESTION # 257
A Deployment named web-app is running in the production namespace with 2 replicas. The replica count must be increased to 5. Which kubectl command correctly scales the Deployment?
Answer: A
Explanation:
The kubectl scale command changes the desired replica count of an existing Deployment.
Specifying --replicas=5 updates the Deployment to maintain five Pods in the production namespace.
NEW QUESTION # 258
Which mechanism can be used to automatically adjust the amount of resources for an application?
Answer: B
Explanation:
The verified answer in the PDF is A (HPA), and that aligns with the common Kubernetes meaning of "adjust resources for an application" by scaling replicas. The Horizontal Pod Autoscaler automatically changes the number of Pod replicas for a workload (typically a Deployment) based on observed metrics such as CPU utilization, memory (in some configurations), or custom/external metrics. By increasing replicas under load, the application gains more total CPU/memory capacity available across Pods; by decreasing replicas when load drops, it reduces resource consumption and cost.
It's important to distinguish what each mechanism adjusts:
HPA adjusts replica count (horizontal scaling).
VPA adjusts Pod resource requests/limits (vertical scaling), which is literally "amount of CPU/memory per pod," but it often requires restarts to apply changes depending on mode.
Cluster Autoscaler adjusts the number of nodes in the cluster, not application replicas.
KEDA is event-driven autoscaling that often drives HPA behavior using external event sources (queues, streams), but it's not the primary built-in mechanism referenced in many foundational Kubernetes questions.
Given the wording and the provided answer key, the intended interpretation is: "automatically adjust the resources available to the application" by scaling out/in the number of replicas. That's exactly HPA's role. For example, if CPU utilization exceeds a target (say 60%), HPA computes a higher desired replica count and updates the workload. The Deployment then creates more Pods, distributing load and increasing available compute.
So, within this question set, the verified correct choice is A (Horizontal Pod Autoscaler).
NEW QUESTION # 259
You are running a stateful application on Kubernetes that requires persistent data storage. Which of the following Kubernetes storage classes would be most suitable for this scenario?
Answer: C
Explanation:
Persistent Volumes (PVs) are the most suitable storage class for stateful applications- They guarantee persistent data storage across pod restarts and provide a consistent interface for accessing the data
NEW QUESTION # 260
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