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Exam Code: CKA

Exam Name Certified Kubernetes Administrator

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CNCF CKA Practice Test 109

Question 1080

At Pinecrest logistics, in a sandbox Kubernetes cluster during a recovery tabletop exercise: Pods on new worker worker-c cannot communicate while the CNI node agent DaemonSet in kube-system lacks a Ready Pod there. Work only within the stated target and verify before declaring success. Which operational control most directly prevents this failure or configuration drift?

  1. Gate worker acceptance on CNI readiness and a cross-node connectivity check.
  2. Maintain policy test matrices for required app flows, DNS, telemetry and denied peers.
  3. Monitor kubelet health and coordinate OS upgrades with supported runtime versions.
  4. Maintain an inventory of dedicated-node taints and explicitly reviewed workload tolerations.

Explanation

Correct Answer

A:

Gate worker acceptance on CNI readiness and a cross-node connectivity check. This reduces recurrence of the specific operational failure. It reinforces the action: Run kubectl -n kube-system get daemonsets and kubectl -n kube-system get pods -o wide to identify CNI plugin coverage on worker-c. The relevant mechanism is: Kubernetes network connectivity requires a functioning CNI implementation on nodes; core API objects alone do not create functional Pod networking.

Incorrect Answers

B:

That safeguard is relevant to: NetworkPolicy allows only explicitly selected paths once Pod ingress or egress isolation applies, and both directions may matter. The current failure instead follows from: Kubernetes network connectivity requires a functioning CNI implementation on nodes; core API objects alone do not create functional Pod networking. Its prevention measure is “Gate worker acceptance on CNI readiness and a cross-node connectivity check”.

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: Kubernetes network connectivity requires a functioning CNI implementation on nodes; core API objects alone do not create functional Pod networking. The matching preventive check is “Gate worker acceptance on CNI readiness and a cross-node connectivity check”.

D:

The suggested review tracks a different technical risk: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources. Here the sustained control must address: Kubernetes network connectivity requires a functioning CNI implementation on nodes; core API objects alone do not create functional Pod networking. Choose “Gate worker acceptance on CNI readiness and a cross-node connectivity check”.

Question 1081

At Northstar finance, in an isolated training cluster during a scheduled maintenance rehearsal: Node worker-a changes to NotReady after an operating system update; determine whether kubelet is running before deleting Pods. 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. Run kubectl -n ledger describe pod invoice-api and inspect readiness failure events and probe configuration.
  2. Run kubectl -n fulfillment describe pod dispatch-api and compare Pod tolerations with kubectl describe node worker-c taints.
  3. On worker-a, run sudo systemctl status kubelet and sudo journalctl -u kubelet -n 80 --no-pager along with kubectl describe node worker-a from an admin context.
  4. Run kubectl -n ledger describe daemonset invoice-api and compare target node eligibility, taints and Pod events.

Explanation

Correct Answer

C:

On worker-a, run sudo systemctl status kubelet and sudo journalctl -u kubelet -n 80 --no-pager along with kubectl describe node worker-a from an admin context. This is the appropriate command-line action or first safe diagnostic. The technical reason is: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Validate the result with: Run kubectl get node worker-a and confirm Ready after restoring the actual failed component. Execute changes only in an authorized disposable lab or after normal production change controls.

Incorrect Answers

A:

The offered action targets: A running container is not necessarily Ready; failing readiness can remove a Pod from ready Service endpoints. The case facts point instead to: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Implement “On worker-a, run sudo systemctl status kubelet and sudo journalctl -u kubelet -n 80 --no-pager along with kubectl describe node worker-a from an admin context” to address that specific condition.

B:

This alternative is a response to another technical cause: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources. The reported case instead depends on: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The action that directly addresses it is “On worker-a, run sudo systemctl status kubelet and sudo journalctl -u kubelet -n 80 --no-pager along with kubectl describe node worker-a from an admin context”.

D:

The offered action targets: DaemonSets schedule according to node selection and toleration rules; unavailable node agents can break networking or logging on selected workers. The case facts point instead to: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Implement “On worker-a, run sudo systemctl status kubelet and sudo journalctl -u kubelet -n 80 --no-pager along with kubectl describe node worker-a from an admin context” to address that specific condition.

Question 1082

At Northstar finance, in an isolated training cluster during a scheduled maintenance rehearsal: Node worker-a changes to NotReady after an operating system update; determine whether kubelet is running before deleting Pods. Work only within the stated target and verify before declaring success. Which Kubernetes behavior best explains the required change or diagnosis?

  1. A hard nodeSelector must match a Node's actual labels; tolerations or Service routing cannot bypass the unmatched selector.
  2. Kubernetes network connectivity requires a functioning CNI implementation on nodes; core API objects alone do not create functional Pod networking.
  3. Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime.
  4. Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service.

Explanation

Correct Answer

D:

Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. This explains the stated condition. The corresponding action is: On worker-a, run sudo systemctl status kubelet and sudo journalctl -u kubelet -n 80 --no-pager along with kubectl describe node worker-a from an admin context. The direct acceptance evidence is: Run kubectl get node worker-a and confirm Ready after restoring the actual failed component.

Incorrect Answers

A:

This principle describes a separate cause: A hard nodeSelector must match a Node's actual labels; tolerations or Service routing cannot bypass the unmatched selector. The reported condition is governed by: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The two mechanisms should not be conflated.

B:

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: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service.

C:

The offered statement is true for this other mechanism: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. It does not explain the facts described here, which follow from: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service.

Question 1083

At Northstar finance, in an isolated training cluster during a scheduled maintenance rehearsal: Node worker-a changes to NotReady after an operating system update; determine whether kubelet is running before deleting Pods. 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-a and confirm Ready after restoring the actual failed component.
  2. Verify the node returns to Ready without MemoryPressure and Pod eviction rates stabilize after capacity planning.
  3. Run kubectl -n ledger get pod invoice-api and inspect matching EndpointSlices after correcting the probe or backend.
  4. Confirm the scheduler events clear and the Pod is assigned after capacity or request adjustments.

Explanation

Correct Answer

A:

Run kubectl get node worker-a and confirm Ready after restoring the actual failed component. This validates the affected object or control path, rather than only showing a command completed. The underlying reason is: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The intended action is: On worker-a, run sudo systemctl status kubelet and sudo journalctl -u kubelet -n 80 --no-pager along with kubectl describe node worker-a from an admin context.

Incorrect Answers

B:

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: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The direct verification is “Run kubectl get node worker-a and confirm Ready after restoring the actual failed component”.

C:

This observation would test a different technical dependency: A running container is not necessarily Ready; failing readiness can remove a Pod from ready Service endpoints. The current issue is governed by: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Its decisive check is “Run kubectl get node worker-a and confirm Ready after restoring the actual failed component”.

D:

The alternative verifies a different condition: The scheduler places Pods by requested resources and constraints, not the current shell's observed free CPU alone. The current case instead depends on: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Confirm that “Run kubectl get node worker-a and confirm Ready after restoring the actual failed component”.

Question 1084

At Northstar finance, in an isolated training cluster during a scheduled maintenance rehearsal: Node worker-a changes to NotReady after an operating system update; determine whether kubelet is running before deleting Pods. Work only within the stated target and verify before declaring success. Which operational control most directly prevents this failure or configuration drift?

  1. Govern scheduler labels and include eligible-node checks before promoting hard node selectors.
  2. Monitor kubelet health and coordinate OS upgrades with supported runtime versions.
  3. Back up control-plane manifests and validate risky edits before reloading static Pods.
  4. Test kubelet/CRI version compatibility and runtime services in node patch runbooks.

Explanation

Correct Answer

B:

Monitor kubelet health and coordinate OS upgrades with supported runtime versions. This reduces recurrence of the specific operational failure. It reinforces the action: On worker-a, run sudo systemctl status kubelet and sudo journalctl -u kubelet -n 80 --no-pager along with kubectl describe node worker-a from an admin context. The relevant mechanism is: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service.

Incorrect Answers

A:

That safeguard is relevant to: A hard nodeSelector must match a Node's actual labels; tolerations or Service routing cannot bypass the unmatched selector. The current failure instead follows from: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Its prevention measure is “Monitor kubelet health and coordinate OS upgrades with supported runtime versions”.

C:

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: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Choose “Monitor kubelet health and coordinate OS upgrades with supported runtime versions”.

D:

That safeguard is relevant to: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The current failure instead follows from: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Its prevention measure is “Monitor kubelet health and coordinate OS upgrades with supported runtime versions”.

Question 1085

At Horizon observability, in a disposable simulated environment during a monitored release window: Node worker-b changes to NotReady after an operating system update; determine whether kubelet is running before deleting Pods. 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. Run kubectl -n observability describe pod metrics-api and compare Pod tolerations with kubectl describe node worker-b taints.
  2. Run kubectl get nodes -l workload=restricted and compare with kubectl -n observability describe pod metrics-api before changing node labels.
  3. Run kubectl describe node worker-b and on the host inspect df -h and kubelet eviction messages.
  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

D:

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. This is the appropriate command-line action or first safe diagnostic. The technical reason is: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Validate the result with: Run kubectl get node worker-b and confirm Ready after restoring the actual failed component. Execute changes only in an authorized disposable lab or after normal production change controls.

Incorrect Answers

A:

This alternative is a response to another technical cause: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources. The reported case instead depends on: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The action that directly addresses it is “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”.

B:

The proposed action belongs to the mechanism: A hard nodeSelector must match a Node's actual labels; tolerations or Service routing cannot bypass the unmatched selector. Here the stated fault follows a different mechanism: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The corrective choice is “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”.

C:

The offered action targets: DiskPressure is a node condition triggered by storage thresholds; deleting live runtime data blindly can corrupt workloads. The case facts point instead to: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Implement “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” to address that specific condition.

Question 1086

At Horizon observability, in a disposable simulated environment during a monitored release window: Node worker-b changes to NotReady after an operating system update; determine whether kubelet is running before deleting Pods. Work only within the stated target and verify before declaring success. Which Kubernetes behavior best explains the required change or diagnosis?

  1. Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service.
  2. Kubeadm control-plane components are commonly static Pods managed by kubelet; kubectl cannot diagnose them if the API server itself is unavailable.
  3. Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime.
  4. DiskPressure is a node condition triggered by storage thresholds; deleting live runtime data blindly can corrupt workloads.

Explanation

Correct Answer

A:

Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. This explains the stated condition. The corresponding action is: 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. The direct acceptance evidence is: Run kubectl get node worker-b and confirm Ready after restoring the actual failed component.

Incorrect Answers

B:

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: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service.

C:

This principle describes a separate cause: Kubelet relies on a CRI-compatible runtime for container creation; restarting application Pods cannot repair an unavailable runtime. The reported condition is governed by: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The two mechanisms should not be conflated.

D:

DiskPressure is a node condition triggered by storage thresholds; deleting live runtime data blindly can corrupt workloads. That explanation applies to a different technical failure. Here the controlling principle is: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service.

Question 1087

At Horizon observability, in a disposable simulated environment during a monitored release window: Node worker-b changes to NotReady after an operating system update; determine whether kubelet is running before deleting Pods. 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 CRI service is healthy and kubectl get node worker-a returns Ready after supported recovery.
  2. Run kubectl get node worker-b and confirm Ready after restoring the actual failed component.
  3. Confirm the expected CNI Pod is Ready on worker-b and test Pod-to-Pod connectivity from that node.
  4. Verify node disk pressure clears and relevant Pods become stable after approved cleanup or capacity changes.

Explanation

Correct Answer

B:

Run kubectl get node worker-b and confirm Ready after restoring the actual failed component. This validates the affected object or control path, rather than only showing a command completed. The underlying reason is: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The intended action is: 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.

Incorrect Answers

A:

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

C:

The alternative verifies a different condition: Kubernetes network connectivity requires a functioning CNI implementation on nodes; core API objects alone do not create functional Pod networking. The current case instead depends on: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Confirm that “Run kubectl get node worker-b and confirm Ready after restoring the actual failed component”.

D:

That test belongs to another control with this basis: DiskPressure is a node condition triggered by storage thresholds; deleting live runtime data blindly can corrupt workloads. In the current case, the governing reason is: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The direct verification is “Run kubectl get node worker-b and confirm Ready after restoring the actual failed component”.

Question 1088

At Horizon observability, in a disposable simulated environment during a monitored release window: Node worker-b changes to NotReady after an operating system update; determine whether kubelet is running before deleting Pods. 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. Maintain an inventory of dedicated-node taints and explicitly reviewed workload tolerations.
  3. Monitor kubelet health and coordinate OS upgrades with supported runtime versions.
  4. Maintain image garbage-collection, log rotation and filesystem capacity alerts.

Explanation

Correct Answer

C:

Monitor kubelet health and coordinate OS upgrades with supported runtime versions. This reduces recurrence of the specific operational failure. It reinforces the action: 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. The relevant mechanism is: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service.

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: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The matching preventive check is “Monitor kubelet health and coordinate OS upgrades with supported runtime versions”.

B:

The suggested review tracks a different technical risk: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources. Here the sustained control must address: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Choose “Monitor kubelet health and coordinate OS upgrades with supported runtime versions”.

D:

This routine guards against another mechanism: DiskPressure is a node condition triggered by storage thresholds; deleting live runtime data blindly can corrupt workloads. The recurring exposure in the current case is: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The matching preventive check is “Monitor kubelet health and coordinate OS upgrades with supported runtime versions”.

Question 1089

At Pinecrest logistics, in a sandbox Kubernetes cluster during a recovery tabletop exercise: Node worker-c changes to NotReady after an operating system update; determine whether kubelet is running before deleting Pods. 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-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.
  2. On worker-a, run sudo systemctl status containerd and sudo journalctl -u containerd -n 80 --no-pager before modifying runtime configuration.
  3. Run kubectl describe node worker-c and on the host inspect df -h and kubelet eviction messages.
  4. Run kubectl describe node worker-c and kubectl top node worker-c where metrics are available before altering Pod requests.

Explanation

Correct Answer

A:

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. This is the appropriate command-line action or first safe diagnostic. The technical reason is: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Validate the result with: Run kubectl get node worker-c and confirm Ready after restoring the actual failed component. Execute changes only in an authorized disposable lab or after normal production change controls.

Incorrect Answers

B:

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: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. Implement “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” to address that specific condition.

C:

This alternative is a response to another technical cause: DiskPressure is a node condition triggered by storage thresholds; deleting live runtime data blindly can corrupt workloads. The reported case instead depends on: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The action that directly addresses it is “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”.

D:

The proposed action belongs to the mechanism: Node memory pressure can cause evictions and scheduling instability independent of one container's OOMKilled status. Here the stated fault follows a different mechanism: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. The corrective choice is “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”.

Question 1090

At Pinecrest logistics, in a sandbox Kubernetes cluster during a recovery tabletop exercise: Node worker-c changes to NotReady after an operating system update; determine whether kubelet is running before deleting Pods. 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. Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service.
  3. Kubernetes network connectivity requires a functioning CNI implementation on nodes; core API objects alone do not create functional Pod networking.
  4. DaemonSets schedule according to node selection and toleration rules; unavailable node agents can break networking or logging on selected workers.

Explanation

Correct Answer

B:

Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service. This explains the stated condition. The corresponding action is: 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. The direct acceptance evidence is: Run kubectl get node worker-c and confirm Ready after restoring the actual failed component.

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: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service.

C:

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: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service.

D:

The offered statement is true for this other mechanism: DaemonSets schedule according to node selection and toleration rules; unavailable node agents can break networking or logging on selected workers. It does not explain the facts described here, which follow from: Node readiness depends on the kubelet and node conditions; application restarts cannot fix a stopped kubelet service.