McAfee Secure

CNCF CKA Bundle

Exam Code: CKA

Exam Name Certified Kubernetes Administrator

Certification Provider: CNCF

Corresponding Certification: CKA

CNCF CKA Bundle $44.99
CKA Sample 1 CKA Sample 2 CKA Sample 3 CKA Sample 4 CKA Sample 5 CKA Sample 6 CKA Sample 7 CKA Sample 8 CKA Sample 9 CKA Sample 10

100% CNCF CKA Guaranteed Success With Testking Training Materials

Get Real CKA Exam Questions & Expert Verified Answers as Experienced on the Real Exam!

  • Questions & Answers

    CKA Questions & Answers

    58 Questions & Answers

    The ultimate exam preparation tool, Questions & Answers mirrors the actual CKA exam while allowing you to hone and measure every aspect of your test-taking ability.

  • CKA Video Course

    CKA Training Course

    138 Video Lectures

    CKA Video Course is developed by CNCF Professionals to help you pass the CKA exam.

    Description

    This course will improve your knowledge and skills required to pass Certified Kubernetes Administrator exam.
  • Study Guide

    CKA Study Guide

    268 PDF Pages

    Developed by industry experts, this 268-page guide spells out in painstaking detail all of the information you need to ace CKA exam.

Certified Kubernetes Administrator (CKA) Practice Tests

Satisfaction Guaranteed

Money Back Guarantee

Testking provides hassle-free money back guarantee with our products. That is because we have 100% trust in the abilities of our professional and experience product team, and our record is a proof of that.

99.6% PASS RATE
Total Cost: $194.97
Bundle Price: $149.98

Purchase Individually

  • Questions & Answers

    Questions & Answers

    58 Questions

    $124.99
  • CKA Video Course

    Training Course

    138 Video Lectures

    $39.99
  • Study Guide

    Study Guide

    268 PDF Pages

    $29.99

CNCF CKA Practice Test 113

Question 1120

At Northstar finance, in an isolated training cluster during a scheduled maintenance rehearsal: Node worker-a becomes NotReady and kubelet logs contain container runtime unavailable errors after a host patch. Work only within the stated target and verify before declaring success. Which operational control most directly prevents this failure or configuration drift?

  1. Monitor kubelet health and coordinate OS upgrades with supported runtime versions.
  2. Baseline memory requests and track node allocatable resources and eviction signals.
  3. Test kubelet/CRI version compatibility and runtime services in node patch runbooks.
  4. Maintain image garbage-collection, log rotation and filesystem capacity alerts.

Explanation

Correct Answer

C:

Test kubelet/CRI version compatibility and runtime services in node patch runbooks. This reduces recurrence of the specific operational failure. It reinforces the action: On worker-a, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration. The relevant mechanism is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime.

Incorrect Answers

A:

That safeguard is relevant to: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The current failure instead follows from: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. Its prevention measure is “Test kubelet/CRI version compatibility and runtime services in node patch runbooks”.

B:

This routine guards against another mechanism: Node memory pressure can cause evictions and scheduling instability independent of one container's OOMKilled status. The recurring exposure in the current case is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The matching preventive check is “Test kubelet/CRI version compatibility and runtime services in node patch runbooks”.

D:

That safeguard is relevant to: DiskPressure is a node condition triggered by storage thresholds; deleting live runtime data blindly can corrupt workloads. The current failure instead follows from: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. Its prevention measure is “Test kubelet/CRI version compatibility and runtime services in node patch runbooks”.

Question 1121

At Horizon observability, in a disposable simulated environment during a monitored release window: Node worker-b becomes NotReady and kubelet logs contain container runtime unavailable errors after a host patch. Work only within the stated target and verify before declaring success. Which command or initial safe diagnostic step best addresses the stated lab task?

  1. On worker-b, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration.
  2. On the control-plane host, run sudo crictl ps -a and sudo journalctl -u kubelet -n 100 --no-pager to inspect kube-apiserver container failures.
  3. On worker-c, run sudo systemctl status kubelet and sudo journalctl -u kubelet -n 80 --no-pager along with kubectl describe node worker-c from an admin context.
  4. Run kubectl -n observability describe daemonset metrics-api and compare target node eligibility, taints and Pod events.

Explanation

Correct Answer

A:

On worker-b, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration. This is the appropriate command-line action or first safe diagnostic. The technical reason is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. Validate the result with: Confirm the CRI service is healthy and kubectl get node worker-b returns Ready after supported recovery. Execute changes only in an authorized disposable lab or after normal production change controls.

Incorrect Answers

B:

The proposed action belongs to the mechanism: Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable. Here the stated fault follows a different mechanism: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The corrective choice is “On worker-b, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration”.

C:

The offered action targets: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The case facts point instead to: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. Implement “On worker-b, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration” to address that specific condition.

D:

This alternative is a response to another technical cause: DaemonSets schedule according to node selection and toleration rules; unavailable node agents can break networking or logging on selected workers. The reported case instead depends on: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The action that directly addresses it is “On worker-b, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration”.

Question 1122

At Horizon observability, in a disposable simulated environment during a monitored release window: Node worker-b becomes NotReady and kubelet logs contain container runtime unavailable errors after a host patch. Work only within the stated target and verify before declaring success. Which Kubernetes behavior best explains the required change or diagnosis?

  1. Kubernetes network connectivity requires a functioning CNI implementation on nodes; core API objects alone do not create functional Pod networking.
  2. Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime.
  3. A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources.
  4. Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service.

Explanation

Correct Answer

B:

Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. This explains the stated condition. The corresponding action is: On worker-b, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration. The direct acceptance evidence is: Confirm the CRI service is healthy and kubectl get node worker-b returns Ready after supported recovery.

Incorrect Answers

A:

Kubernetes network connectivity requires a functioning CNI implementation on nodes; core API objects alone do not create functional Pod networking. That explanation applies to a different technical failure. Here the controlling principle is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime.

C:

This principle describes a separate cause: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources. The reported condition is governed by: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The two mechanisms should not be conflated.

D:

Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. That explanation applies to a different technical failure. Here the controlling principle is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime.

Question 1123

At Horizon observability, in a disposable simulated environment during a monitored release window: Node worker-b becomes NotReady and kubelet logs contain container runtime unavailable errors after a host patch. Work only within the stated target and verify before declaring success. Which observation best verifies the requested outcome rather than an unrelated state?

  1. Run kubectl get node worker-b and confirm Ready after restoring the actual failed component.
  2. Verify node disk pressure clears and relevant Pods become stable after approved cleanup or capacity changes.
  3. Confirm the CRI service is healthy and kubectl get node worker-b returns Ready after supported recovery.
  4. Verify the node returns to Ready without MemoryPressure and Pod eviction rates stabilize after capacity planning.

Explanation

Correct Answer

C:

Confirm the CRI service is healthy and kubectl get node worker-b returns Ready after supported recovery. This validates the affected object or control path, rather than only showing a command completed. The underlying reason is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The intended action is: On worker-b, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration.

Incorrect Answers

A:

That test belongs to another control with this basis: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. In the current case, the governing reason is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The direct verification is “Confirm the CRI service is healthy and kubectl get node worker-b returns Ready after supported recovery”.

B:

This observation would test a different technical dependency: DiskPressure is a node condition triggered by storage thresholds; deleting live runtime data blindly can corrupt workloads. The current issue is governed by: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. Its decisive check is “Confirm the CRI service is healthy and kubectl get node worker-b returns Ready after supported recovery”.

D:

That test belongs to another control with this basis: Node memory pressure can cause evictions and scheduling instability independent of one container's OOMKilled status. In the current case, the governing reason is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The direct verification is “Confirm the CRI service is healthy and kubectl get node worker-b returns Ready after supported recovery”.

Question 1124

At Horizon observability, in a disposable simulated environment during a monitored release window: Node worker-b becomes NotReady and kubelet logs contain container runtime unavailable errors after a host patch. Work only within the stated target and verify before declaring success. Which operational control most directly prevents this failure or configuration drift?

  1. Baseline memory requests and track node allocatable resources and eviction signals.
  2. Back up control-plane manifests and validate risky edits before reloading static Pods.
  3. Review sizing and autoscaling headroom against known resource requests.
  4. Test kubelet/CRI version compatibility and runtime services in node patch runbooks.

Explanation

Correct Answer

D:

Test kubelet/CRI version compatibility and runtime services in node patch runbooks. This reduces recurrence of the specific operational failure. It reinforces the action: On worker-b, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration. The relevant mechanism is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime.

Incorrect Answers

A:

This routine guards against another mechanism: Node memory pressure can cause evictions and scheduling instability independent of one container's OOMKilled status. The recurring exposure in the current case is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The matching preventive check is “Test kubelet/CRI version compatibility and runtime services in node patch runbooks”.

B:

The suggested review tracks a different technical risk: Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable. Here the sustained control must address: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. Choose “Test kubelet/CRI version compatibility and runtime services in node patch runbooks”.

C:

That safeguard is relevant to: The scheduler places Pods by requested resources and constraints, not the current shell's observed free CPU alone. The current failure instead follows from: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. Its prevention measure is “Test kubelet/CRI version compatibility and runtime services in node patch runbooks”.

Question 1125

At Pinecrest logistics, in a sandbox Kubernetes cluster during a recovery tabletop exercise: Node worker-c becomes NotReady and kubelet logs contain container runtime unavailable errors after a host patch. Work only within the stated target and verify before declaring success. Which command or initial safe diagnostic step best addresses the stated lab task?

  1. On the control-plane host, run sudo crictl ps -a and sudo journalctl -u kubelet -n 100 --no-pager to inspect kube-apiserver container failures.
  2. On worker-c, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration.
  3. Run kubectl -n fulfillment describe daemonset dispatch-api and compare target node eligibility, taints and Pod events.
  4. On worker-b, run sudo systemctl status kubelet and sudo journalctl -u kubelet -n 80 --no-pager along with kubectl describe node worker-b from an admin context.

Explanation

Correct Answer

B:

On worker-c, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration. This is the appropriate command-line action or first safe diagnostic. The technical reason is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. Validate the result with: Confirm the CRI service is healthy and kubectl get node worker-c returns Ready after supported recovery. Execute changes only in an authorized disposable lab or after normal production change controls.

Incorrect Answers

A:

The proposed action belongs to the mechanism: Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable. Here the stated fault follows a different mechanism: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The corrective choice is “On worker-c, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration”.

C:

This alternative is a response to another technical cause: DaemonSets schedule according to node selection and toleration rules; unavailable node agents can break networking or logging on selected workers. The reported case instead depends on: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The action that directly addresses it is “On worker-c, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration”.

D:

The proposed action belongs to the mechanism: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Here the stated fault follows a different mechanism: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The corrective choice is “On worker-c, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration”.

Question 1126

At Pinecrest logistics, in a sandbox Kubernetes cluster during a recovery tabletop exercise: Node worker-c becomes NotReady and kubelet logs contain container runtime unavailable errors after a host patch. Work only within the stated target and verify before declaring success. Which Kubernetes behavior best explains the required change or diagnosis?

  1. Node memory pressure can cause evictions and scheduling instability independent of one container's OOMKilled status.
  2. CrashLoopBackOff is a restart backoff symptom, not a root cause; the preceding container logs often preserve the terminating process error.
  3. Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime.
  4. Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable.

Explanation

Correct Answer

C:

Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. This explains the stated condition. The corresponding action is: On worker-c, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration. The direct acceptance evidence is: Confirm the CRI service is healthy and kubectl get node worker-c returns Ready after supported recovery.

Incorrect Answers

A:

The offered statement is true for this other mechanism: Node memory pressure can cause evictions and scheduling instability independent of one container's OOMKilled status. It does not explain the facts described here, which follow from: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime.

B:

This principle describes a separate cause: CrashLoopBackOff is a restart backoff symptom, not a root cause; the preceding container logs often preserve the terminating process error. The reported condition is governed by: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The two mechanisms should not be conflated.

D:

The offered statement is true for this other mechanism: Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable. It does not explain the facts described here, which follow from: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime.

Question 1127

At Pinecrest logistics, in a sandbox Kubernetes cluster during a recovery tabletop exercise: Node worker-c becomes NotReady and kubelet logs contain container runtime unavailable errors after a host patch. Work only within the stated target and verify before declaring success. Which observation best verifies the requested outcome rather than an unrelated state?

  1. Confirm the scheduler component is healthy and a new test Pod obtains spec.nodeName after repair.
  2. Run kubectl -n fulfillment get pod dispatch-api -o jsonpath='{.status.containerStatuses[*].lastState.terminated.reason}' and verify healthy replacements after a tested memory correction.
  3. Run kubectl -n fulfillment describe pod dispatch-api and verify corrected Pods become Ready without repeated restarts.
  4. Confirm the CRI service is healthy and kubectl get node worker-c returns Ready after supported recovery.

Explanation

Correct Answer

D:

Confirm the CRI service is healthy and kubectl get node worker-c returns Ready after supported recovery. This validates the affected object or control path, rather than only showing a command completed. The underlying reason is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The intended action is: On worker-c, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration.

Incorrect Answers

A:

This observation would test a different technical dependency: The scheduler assigns unscheduled Pods to nodes; a broken scheduler differs from per-Pod placement constraints. The current issue is governed by: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. Its decisive check is “Confirm the CRI service is healthy and kubectl get node worker-c returns Ready after supported recovery”.

B:

The alternative verifies a different condition: The container runtime can terminate a container when it exceeds its memory cgroup limit; increasing CPU requests does not repair a memory limit failure. The current case instead depends on: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. Confirm that “Confirm the CRI service is healthy and kubectl get node worker-c returns Ready after supported recovery”.

C:

That test belongs to another control with this basis: CrashLoopBackOff is a restart backoff symptom, not a root cause; the preceding container logs often preserve the terminating process error. In the current case, the governing reason is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The direct verification is “Confirm the CRI service is healthy and kubectl get node worker-c returns Ready after supported recovery”.

Question 1128

At Pinecrest logistics, in a sandbox Kubernetes cluster during a recovery tabletop exercise: Node worker-c becomes NotReady and kubelet logs contain container runtime unavailable errors after a host patch. Work only within the stated target and verify before declaring success. Which operational control most directly prevents this failure or configuration drift?

  1. Test kubelet/CRI version compatibility and runtime services in node patch runbooks.
  2. Baseline memory requests and track node allocatable resources and eviction signals.
  3. Monitor kubelet health and coordinate OS upgrades with supported runtime versions.
  4. Back up control-plane manifests and validate risky edits before reloading static Pods.

Explanation

Correct Answer

A:

Test kubelet/CRI version compatibility and runtime services in node patch runbooks. This reduces recurrence of the specific operational failure. It reinforces the action: On worker-c, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration. The relevant mechanism is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime.

Incorrect Answers

B:

That safeguard is relevant to: Node memory pressure can cause evictions and scheduling instability independent of one container's OOMKilled status. The current failure instead follows from: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. Its prevention measure is “Test kubelet/CRI version compatibility and runtime services in node patch runbooks”.

C:

This routine guards against another mechanism: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The recurring exposure in the current case is: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The matching preventive check is “Test kubelet/CRI version compatibility and runtime services in node patch runbooks”.

D:

The suggested review tracks a different technical risk: Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable. Here the sustained control must address: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. Choose “Test kubelet/CRI version compatibility and runtime services in node patch runbooks”.

Question 1129

At Northstar finance, in an isolated training cluster during a scheduled maintenance rehearsal: The kubeadm lab control-plane endpoint stopped responding after a static Pod manifest edit; examine local kubelet and runtime state on the control-plane host. Work only within the stated target and verify before declaring success. Which command or initial safe diagnostic step best addresses the stated lab task?

  1. On worker-a, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration.
  2. On worker-b, run sudo systemctl status kubelet and sudo journalctl -u kubelet -n 80 --no-pager along with kubectl describe node worker-b from an admin context.
  3. On the control-plane host, run sudo crictl ps -a and sudo journalctl -u kubelet -n 100 --no-pager to inspect kube-apiserver container failures.
  4. Run kubectl -n ledger describe pod invoice-api plus kubectl -n ledger logs invoice-api --previous to distinguish startup and runtime faults.

Explanation

Correct Answer

C:

On the control-plane host, run sudo crictl ps -a and sudo journalctl -u kubelet -n 100 --no-pager to inspect kube-apiserver container failures. This is the appropriate command-line action or first safe diagnostic. The technical reason is: Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable. Validate the result with: Confirm local API server container health and successful kubectl get --raw=/readyz after restoring the valid manifest. Execute changes only in an authorized disposable lab or after normal production change controls.

Incorrect Answers

A:

The offered action targets: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The case facts point instead to: Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable. Implement “On the control-plane host, run sudo crictl ps -a and sudo journalctl -u kubelet -n 100 --no-pager to inspect kube-apiserver container failures” to address that specific condition.

B:

This alternative is a response to another technical cause: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The reported case instead depends on: Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable. The action that directly addresses it is “On the control-plane host, run sudo crictl ps -a and sudo journalctl -u kubelet -n 100 --no-pager to inspect kube-apiserver container failures”.

D:

The offered action targets: Liveness failure triggers restarts, while startup and readiness probes serve different lifecycle purposes. The case facts point instead to: Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable. Implement “On the control-plane host, run sudo crictl ps -a and sudo journalctl -u kubelet -n 100 --no-pager to inspect kube-apiserver container failures” to address that specific condition.

Question 1130

At Northstar finance, in an isolated training cluster during a scheduled maintenance rehearsal: The kubeadm lab control-plane endpoint stopped responding after a static Pod manifest edit; examine local kubelet and runtime state on the control-plane host. Work only within the stated target and verify before declaring success. Which Kubernetes behavior best explains the required change or diagnosis?

  1. The scheduler assigns unscheduled Pods to nodes; a broken scheduler differs from per-Pod placement constraints.
  2. The control plane depends on a healthy etcd key-value store, and TLS-authenticated endpoint checks distinguish store failures from API client issues.
  3. Controllers reconcile desired resources with observed state; the API server storing a Deployment does not itself create replica Pods.
  4. Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable.

Explanation

Correct Answer

D:

Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable. This explains the stated condition. The corresponding action is: On the control-plane host, run sudo crictl ps -a and sudo journalctl -u kubelet -n 100 --no-pager to inspect kube-apiserver container failures. The direct acceptance evidence is: Confirm local API server container health and successful kubectl get --raw=/readyz after restoring the valid manifest.

Incorrect Answers

A:

This principle describes a separate cause: The scheduler assigns unscheduled Pods to nodes; a broken scheduler differs from per-Pod placement constraints. The reported condition is governed by: Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable. The two mechanisms should not be conflated.

B:

The control plane depends on a healthy etcd key-value store, and TLS-authenticated endpoint checks distinguish store failures from API client issues. That explanation applies to a different technical failure. Here the controlling principle is: Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable.

C:

The offered statement is true for this other mechanism: Controllers reconcile desired resources with observed state; the API server storing a Deployment does not itself create replica Pods. It does not explain the facts described here, which follow from: Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable.