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[General] KCNA Exam Dumps Provider, Valid KCNA Test Registration

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【General】 KCNA Exam Dumps Provider, Valid KCNA Test Registration

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Linux Foundation Kubernetes and Cloud Native Associate Sample Questions (Q203-Q208):NEW QUESTION # 203
What sentence is true about CronJobs in Kubernetes?
  • A. The CronJob schedule format is different in Kubernetes and Linux.
  • B. A CronJob creates one container on a repeating schedule.
  • C. A CronJob creates one or multiple Jobs on a repeating schedule.
  • D. CronJobs are useful on Linux but are obsolete in Kubernetes.
Answer: C
Explanation:
The true statement is A: a Kubernetes CronJob creates Jobs on a repeating schedule. CronJob is a controller designed for time-based execution. You define a schedule using standard cron syntax (minute, hour, day-of- month, month, day-of-week), and when the schedule triggers, the CronJob controller creates a Job object.
Then the Job controller creates one or more Pods to run the task to completion.
Option B is incorrect because CronJobs do not "create one container"; they create Jobs, and Jobs create Pods (which may contain one or multiple containers). Option C is wrong because CronJobs are a core Kubernetes workload primitive for recurring tasks and remain widely used for periodic work like backups, batch processing, and cleanup. Option D is wrong because Kubernetes CronJobs intentionally use cron-like scheduling expressions; the format aligns with the cron concept (with Kubernetes-specific controller behavior around missed runs, concurrency, and history).
CronJobs also provide operational controls you don't get from plain Linux cron on a node:
* concurrencyPolicy (Allow/Forbid/Replace) to manage overlapping runs
* startingDeadlineSeconds to control how missed schedules are handled
* history limits for successful/failed Jobs to avoid clutter
* integration with Kubernetes RBAC, Secrets, ConfigMaps, and volumes for consistent runtime configuration
* consistent execution environment via container images, not ad-hoc node scripts Because the CronJob creates Jobs as first-class API objects, you get observability (events/status), predictable retries, and lifecycle management. That's why the accurate statement is A.
=========

NEW QUESTION # 204
What is the name of the lightweight Kubernetes distribution built for IoT and edge computing?
  • A. OpenShift
  • B. k3s
  • C. k1s
  • D. RKE
Answer: B
Explanation:
Edge and IoT environments often have constraints that differ from traditional datacenters: limited CPU/RAM, intermittent connectivity, smaller footprints, and a desire for simpler operations. k3s is a well-known lightweight Kubernetes distribution designed specifically to run in these environments, making B the correct answer.
What makes k3s "lightweight" is that it packages Kubernetes components in a simplified way and reduces operational overhead. It typically uses a single binary distribution and can run with an embedded datastore option for smaller installations (while also supporting external datastores for HA use cases). It streamlines dependencies and is aimed at faster installation and reduced resource consumption, which is ideal for edge nodes, IoT gateways, small servers, labs, and development environments.
By contrast, OpenShift is a Kubernetes distribution focused on enterprise platform capabilities, with additional security defaults, integrated developer tooling, and a larger operational footprint-excellent for many enterprises but not "built for IoT and edge" as the defining characteristic. RKE (Rancher Kubernetes Engine) is a Kubernetes installer/engine used to deploy Kubernetes, but it's not specifically the lightweight edge-focused distribution in the way k3s is. "k1s" is not a standard, widely recognized Kubernetes distribution name in this context.
From a cloud native architecture perspective, edge Kubernetes distributions extend the same declarative and API-driven model to places where you want consistent operations across cloud, datacenter, and edge. You can apply GitOps patterns, standard manifests, and Kubernetes-native controllers across heterogeneous footprints.
k3s provides that familiar Kubernetes experience while optimizing for constrained environments, which is why it has become a common choice for edge/IoT Kubernetes deployments.
=========

NEW QUESTION # 205
Which of the following actions is supported when working with Pods in Kubernetes?
  • A. Managing static Pods directly through the API server.
  • B. Renaming containers in a Pod using kubectl patch.
  • C. Guaranteeing Pods always stay on the same node once scheduled.
  • D. Creating Pods through workload resources like Deployments.
Answer: D
Explanation:
In Kubernetes, Pods are the smallest deployable units and represent one or more containers that share networking and storage. While Pods can be created directly, Kubernetes strongly encourages users to manage Pods indirectly through higher-level workload resources. Among the options provided, creating Pods through workload resources like Deployments is a fully supported and recommended practice.
Workload resources such as Deployments, ReplicaSets, StatefulSets, and Jobs are designed to manage Pods declaratively. A Deployment, for example, defines a desired state-such as the number of replicas and the Pod template-and Kubernetes continuously works to maintain that state. If a Pod crashes, is deleted, or a node fails, the Deployment automatically creates a replacement Pod. This model provides self-healing, scalability, rolling updates, and rollback capabilities, which are not available when managing standalone Pods.
Option A is incorrect because static Pods are not managed through the API server. Static Pods are created and managed directly by the kubelet on a specific node using manifest files placed on disk. Although the API server becomes aware of static Pods, they cannot be created, modified, or deleted through it.
Option B is incorrect because Kubernetes does not guarantee that Pods will always remain on the same node.
If a node becomes unhealthy or a Pod is evicted, the scheduler may place a replacement Pod on a different node. Only certain workload patterns, such as StatefulSets with persistent storage, attempt to preserve identity-not node placement.
Option C is also incorrect because container names within a Pod are immutable. Kubernetes does not allow renaming containers using kubectl patch or any other mechanism after the Pod has been created.
Therefore, the correct and verified answer is option D: creating Pods through workload resources like Deployments, which aligns with Kubernetes design principles and official documentation.

NEW QUESTION # 206
You are running a service in Kubernetes that uses a persistent volume. You need to ensure that the volume is automatically cleaned up when the service is deleted. Which of the following approaches would you use?
  • A. There is no automatic way to clean up a persistent volume when a service is deleted; it needs to be done manually.
  • B. Delete the PersistentVolumeClaim manually when the service is deleted
  • C. Use a DaemonSet to run a cleanup script that removes the volume when the service is deleted
  • D. Set the 'persistentVolumeReclaimPolicy' to 'Delete' in the PersistentVolumeClaim
  • E. Configure a CronJob to periodically check for unused volumes and delete them
Answer: D
Explanation:
Setting the 'persistentVolumeReclaimPolicy' to 'Delete' in the PersistentVolumeClaim ensures that the volume is automatically deleted when the PVC is deleted. This is the most straightforward and recommended approach for cleaning up persistent volumes in Kubernetes.

NEW QUESTION # 207
In Kubernetes, if the API version of feature is v2beta3, it means that:
  • A. The version will remain available for all future releases within a Kubernetes major version.
  • B. The software may contain bugs. Enabling a feature may expose bugs.
  • C. The software is well tested. Enabling a feature is considered safe.
  • D. The API may change in incompatible ways in a later software release without notice.
Answer: D
Explanation:
The correct answer is B. In Kubernetes API versioning, the stability level is encoded in the version string: alpha, beta, and stable (v1). A version like v2beta3 indicates the API is in a beta stage. Beta APIs are more mature than alpha, but they are not fully guaranteed stable in perpetuity the way v1 stable APIs are intended to be. The key implication is that while beta APIs are generally usable, they can still undergo incompatible changes in future releases as the API design evolves.
Option B captures that meaning: a beta API may change in ways that break compatibility. This is why teams should treat beta APIs with some caution in production: verify upgrade plans, monitor deprecation notices, and be prepared to adjust manifests or client code when moving between Kubernetes versions.
Why the other options are incorrect:
A implies permanence across all future releases in a major version, which is not a beta guarantee. Kubernetes has deprecation and graduation processes, but beta does not equal "forever." C overstates safety; beta is typically "tested and enabled by default" for some features, but it's not the same as stable API guarantees.
D is too vague and misaligned. While any software may contain bugs, the defining point of "beta API" is about stability/compatibility guarantees, not merely "bugs." In practice, Kubernetes communicates API lifecycle clearly: alpha is experimental and may be disabled by default; beta is feature-complete-ish but may change; stable v1 is strongly compatibility-focused with formal deprecation policies. So, a v2beta3 API signals: usable, but not fully locked-hence B.

NEW QUESTION # 208
......
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Frames require a bit more file management than regular pages, because they're KCNA comprised of several documents displayed in one browser window, I'm going to sign the update requests using the key generated earlier in this chapter.
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