Linux Foundation KCNA–Prepare With Actual KCNA Exam Questions [2026]

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Linux Foundation KCNA Certification Exam is a valuable credential for IT professionals who want to advance their careers in the cloud-native industry. Kubernetes and Cloud Native Associate certification validates the candidate's understanding of Kubernetes and other cloud-native technologies, and it helps them stay up-to-date with the latest trends and best practices in the industry. Kubernetes and Cloud Native Associate certification is also beneficial for organizations that want to ensure that their IT teams have the necessary skills and knowledge to develop and deploy cloud-native applications.

Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q194-Q199):

NEW QUESTION # 194
Which of the following options includes valid API versions?

Answer: D

Explanation:
Kubernetes API versions follow a consistent naming pattern that indicates stability level and versioning. The valid forms include stable versions like v1, and pre-release versions such as v1alpha1, v1beta1, etc. Option C contains valid-looking Kubernetes version strings-v1alpha1, v2beta3, v2-so C is correct.
In Kubernetes, the "v" prefix is part of the standard for API versions. A stable API uses v1, v2, etc. Pre- release APIs include a stability marker: alpha (earliest, most changeable) and beta (more stable but still may change). The numeric suffix (e.g., alpha1, beta3) indicates iteration within that stability stage.
Option A is invalid because strings like alpha1v1 and beta3v3 do not match Kubernetes conventions (the v comes first, and alpha/beta are qualifiers after the version: v1alpha1). Option B is invalid because alpha1 and beta3 are missing the leading version prefix; Kubernetes API versions are not just "alpha1." Option D includes 2.0, which looks like semantic versioning but is not the Kubernetes API version format. Kubernetes uses v2, not 2.0, for API versions.
Understanding this matters because API versions signal compatibility guarantees. Stable APIs are supported for a defined deprecation window, while alpha/beta APIs may change in incompatible ways and can be removed more easily. When authoring manifests, selecting the correct apiVersion ensures the API server accepts your resource and that controllers interpret fields correctly.
Therefore, among the choices, C is the only option comprised of valid Kubernetes-style API version strings.
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NEW QUESTION # 195
How is application data maintained in containers?

Answer: D

Explanation:
Container filesystems are ephemeral: the writable layer is tied to the container lifecycle and can be lost when containers are recreated. Therefore, maintaining application data correctly means storing it in volumes, making D the correct answer. In Kubernetes, volumes provide durable or shareable storage that is mounted into containers at specific paths. Depending on the volume type, the data can persist across container restarts and even Pod rescheduling.
Kubernetes supports many volume patterns. For transient scratch data you might use emptyDir (ephemeral for the Pod's lifetime). For durable state, you typically use PersistentVolumes consumed by PersistentVolumeClaims (PVCs), backed by storage systems via CSI drivers (cloud disks, SAN/NAS, distributed storage). This decouples the application container image from its state and enables rolling updates, rescheduling, and scaling without losing data.
Options A and B ("folders") are incomplete because folders inside the container filesystem do not guarantee persistence. A folder is only as durable as the underlying storage; without a mounted volume, it lives in the container's writable layer and will disappear when the container is replaced. Option C is incorrect because
"sidecar containers" are not a data durability mechanism; sidecars can help ship logs or sync data, but persistent data should still be stored on volumes (or external services like managed databases).
From an application delivery standpoint, the principle is: containers should be immutable and disposable, and state should be externalized. Volumes (and external managed services) make this possible. In Kubernetes, this is a foundational pattern enabling safe rollouts, self-healing, and portability: the platform can kill and recreate Pods freely because data is maintained independently via volumes.
Therefore, the verified correct choice is D: Store data into volumes.
=========


NEW QUESTION # 196
What is container runtime?

Answer: B

Explanation:
https://www.aquasec.com/cloud-native-academy/container-security/container-runtime/


NEW QUESTION # 197
You are implementing a continuous integration and continuous deployment (CI/CD) pipeline for a cloud native application running in Kubernetes. Which of the following tools can be used for building, testing, and deploying the application to the cluster?

Answer: A,B,C,D,E

Explanation:
All of the listed tools are widely used for CI/CD pipelines and can be integrated with Kubernetes. Each tool has its own strengths and weaknesses depending on your specific needs. Here's a brief overview: Jenkins: Open-source, highly customizable, and supports a wide range of plugins. CircleCl: Cloud-based, user-friendly, and well-suited for smaller teams and projects. Travis Cl: Also cloud-based, popular for open-source projects and known for its simple setup. GitHub Actions: Native to GitHub, allows you to build, test, and deploy directly within your repository. GitLab CI/CD: Integrated with GitLab, provides a complete CI/CD solution with features for building, testing, and deploying applications.


NEW QUESTION # 198
How is application data maintained in containers?

Answer: D

Explanation:
Container filesystems are ephemeral: the writable layer is tied to the container lifecycle and can be lost when containers are recreated. Therefore, maintaining application data correctly means storing it in volumes, making D the correct answer. In Kubernetes, volumes provide durable or shareable storage that is mounted into containers at specific paths. Depending on the volume type, the data can persist across container restarts and even Pod rescheduling.
Kubernetes supports many volume patterns. For transient scratch data you might use emptyDir (ephemeral for the Pod's lifetime). For durable state, you typically use PersistentVolumes consumed by PersistentVolumeClaims (PVCs), backed by storage systems via CSI drivers (cloud disks, SAN/NAS, distributed storage). This decouples the application container image from its state and enables rolling updates, rescheduling, and scaling without losing data.
Options A and B ("folders") are incomplete because folders inside the container filesystem do not guarantee persistence. A folder is only as durable as the underlying storage; without a mounted volume, it lives in the container's writable layer and will disappear when the container is replaced. Option C is incorrect because "sidecar containers" are not a data durability mechanism; sidecars can help ship logs or sync data, but persistent data should still be stored on volumes (or external services like managed databases).
From an application delivery standpoint, the principle is: containers should be immutable and disposable, and state should be externalized. Volumes (and external managed services) make this possible. In Kubernetes, this is a foundational pattern enabling safe rollouts, self-healing, and portability: the platform can kill and recreate Pods freely because data is maintained independently via volumes.
Therefore, the verified correct choice is D: Store data into volumes.


NEW QUESTION # 199
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