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CNCF CKA Practice Test 92

Question 910

At Pinecrest logistics, in a sandbox Kubernetes cluster during a recovery tabletop exercise: Pod dispatch-api in fulfillment cannot schedule on worker-c; events report untolerated taint special=dedicated:NoSchedule. Work only within the stated target and verify before declaring success. Which Kubernetes behavior best explains the required change or diagnosis?

  1. A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources.
  2. HPA CPU utilization is computed from reported metrics relative to requests; missing metrics or requests can prevent scaling decisions.
  3. NetworkPolicy allows only explicitly selected paths once Pod ingress or egress isolation applies, and both directions may matter.
  4. Cluster DNS search domains and dnsPolicy control short-name resolution; resolving a public hostname is not proof of Kubernetes Service resolution.

Explanation

Correct Answer

A:

A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources. This explains the stated condition. The corresponding action is: Run kubectl -n fulfillment describe pod dispatch-api and compare Pod tolerations with kubectl describe node worker-c taints. The direct acceptance evidence is: Verify the exact toleration or deliberate taint removal and confirm that the Pod schedules to an eligible node.

Incorrect Answers

B:

This principle describes a separate cause: HPA CPU utilization is computed from reported metrics relative to requests; missing metrics or requests can prevent scaling decisions. The reported condition is governed by: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources. The two mechanisms should not be conflated.

C:

NetworkPolicy allows only explicitly selected paths once Pod ingress or egress isolation applies, and both directions may matter. That explanation applies to a different technical failure. Here the controlling principle is: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources.

D:

The offered statement is true for this other mechanism: Cluster DNS search domains and dnsPolicy control short-name resolution; resolving a public hostname is not proof of Kubernetes Service resolution. It does not explain the facts described here, which follow from: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources.

Question 911

At Pinecrest logistics, in a sandbox Kubernetes cluster during a recovery tabletop exercise: Pod dispatch-api in fulfillment cannot schedule on worker-c; events report untolerated taint special=dedicated:NoSchedule. Work only within the stated target and verify before declaring success. Which observation best verifies the requested outcome rather than an unrelated state?

  1. Verify HPA reports a numeric utilization and responds to a controlled load change within configured bounds.
  2. Verify the exact toleration or deliberate taint removal and confirm that the Pod schedules to an eligible node.
  3. Verify the node returns to Ready without MemoryPressure and Pod eviction rates stabilize after capacity planning.
  4. Run kubectl -n fulfillment get pod dispatch-api and confirm the image pulls and containers reach Running after the specific failure is corrected.

Explanation

Correct Answer

B:

Verify the exact toleration or deliberate taint removal and confirm that the Pod schedules to an eligible node. This validates the affected object or control path, rather than only showing a command completed. The underlying reason is: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources. The intended action is: Run kubectl -n fulfillment describe pod dispatch-api and compare Pod tolerations with kubectl describe node worker-c taints.

Incorrect Answers

A:

This observation would test a different technical dependency: HPA CPU utilization is computed from reported metrics relative to requests; missing metrics or requests can prevent scaling decisions. The current issue is governed by: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources. Its decisive check is “Verify the exact toleration or deliberate taint removal and confirm that the Pod schedules to an eligible node”.

C:

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: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources. The direct verification is “Verify the exact toleration or deliberate taint removal and confirm that the Pod schedules to an eligible node”.

D:

This observation would test a different technical dependency: ImagePullBackOff indicates failed image retrieval; cluster DNS, credentials, registry availability and image names are distinct potential causes. The current issue is governed by: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources. Its decisive check is “Verify the exact toleration or deliberate taint removal and confirm that the Pod schedules to an eligible node”.

Question 912

At Pinecrest logistics, in a sandbox Kubernetes cluster during a recovery tabletop exercise: Pod dispatch-api in fulfillment cannot schedule on worker-c; events report untolerated taint special=dedicated:NoSchedule. 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. Validate registry credentials and image digests before rollout to constrained clusters.
  3. Maintain an inventory of dedicated-node taints and explicitly reviewed workload tolerations.
  4. Test DNS policy and search domains during application Pod template changes.

Explanation

Correct Answer

C:

Maintain an inventory of dedicated-node taints and explicitly reviewed workload tolerations. This reduces recurrence of the specific operational failure. It reinforces the action: Run kubectl -n fulfillment describe pod dispatch-api and compare Pod tolerations with kubectl describe node worker-c taints. The relevant mechanism is: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources.

Incorrect Answers

A:

The suggested review tracks a different technical risk: Node memory pressure can cause evictions and scheduling instability independent of one container's OOMKilled status. Here the sustained control must address: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources. Choose “Maintain an inventory of dedicated-node taints and explicitly reviewed workload tolerations”.

B:

That safeguard is relevant to: ImagePullBackOff indicates failed image retrieval; cluster DNS, credentials, registry availability and image names are distinct potential causes. The current failure instead follows from: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources. Its prevention measure is “Maintain an inventory of dedicated-node taints and explicitly reviewed workload tolerations”.

D:

The suggested review tracks a different technical risk: Cluster DNS search domains and dnsPolicy control short-name resolution; resolving a public hostname is not proof of Kubernetes Service resolution. Here the sustained control must address: A NoSchedule taint excludes Pods lacking a matching toleration even if the Node has free resources. Choose “Maintain an inventory of dedicated-node taints and explicitly reviewed workload tolerations”.

Question 913

At Northstar finance, in an isolated training cluster during a scheduled maintenance rehearsal: PVC invoice-data in namespace ledger remains Pending and Pod invoice-api cannot mount it; inspect provisioning events and class capability. 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 pvc invoice-data and kubectl get storageclass fast-block before recreating either resource.
  2. Run kubectl -n ledger describe service invoice-svc and kubectl -n ledger get endpointslices -l kubernetes.io/service-name=invoice-svc.
  3. Run kubectl -n ledger describe job daily-archive and get logs of its failed Pods before increasing retry limits.
  4. Run kubectl -n ledger describe hpa invoice-api and check the metrics API, CPU requests and target Pod selection.

Explanation

Correct Answer

A:

Run kubectl -n ledger describe pvc invoice-data and kubectl get storageclass fast-block before recreating either resource. This is the appropriate command-line action or first safe diagnostic. The technical reason is: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. Validate the result with: Run kubectl -n ledger get pvc invoice-data and confirm Bound with capacity and the intended StorageClass after correction. Execute changes only in an authorized disposable lab or after normal production change controls.

Incorrect Answers

B:

This alternative is a response to another technical cause: A Service may exist without usable backends because labels or Pod readiness do not match expected routing. The reported case instead depends on: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. The action that directly addresses it is “Run kubectl -n ledger describe pvc invoice-data and kubectl get storageclass fast-block before recreating either resource”.

C:

The proposed action belongs to the mechanism: A Job retries failed Pod executions up to its backoff limit, but increasing retries does not repair an invalid command or missing dependency. Here the stated fault follows a different mechanism: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. The corrective choice is “Run kubectl -n ledger describe pvc invoice-data and kubectl get storageclass fast-block before recreating either resource”.

D:

The offered action targets: HPA CPU utilization is computed from reported metrics relative to requests; missing metrics or requests can prevent scaling decisions. The case facts point instead to: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. Implement “Run kubectl -n ledger describe pvc invoice-data and kubectl get storageclass fast-block before recreating either resource” to address that specific condition.

Question 914

At Northstar finance, in an isolated training cluster during a scheduled maintenance rehearsal: PVC invoice-data in namespace ledger remains Pending and Pod invoice-api cannot mount it; inspect provisioning events and class capability. Work only within the stated target and verify before declaring success. Which Kubernetes behavior best explains the required change or diagnosis?

  1. ImagePullBackOff indicates failed image retrieval; cluster DNS, credentials, registry availability and image names are distinct potential causes.
  2. A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending.
  3. The container runtime can terminate a container when it exceeds its memory cgroup limit; increasing CPU requests does not repair a memory limit failure.
  4. HPA CPU utilization is computed from reported metrics relative to requests; missing metrics or requests can prevent scaling decisions.

Explanation

Correct Answer

B:

A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. This explains the stated condition. The corresponding action is: Run kubectl -n ledger describe pvc invoice-data and kubectl get storageclass fast-block before recreating either resource. The direct acceptance evidence is: Run kubectl -n ledger get pvc invoice-data and confirm Bound with capacity and the intended StorageClass after correction.

Incorrect Answers

A:

This principle describes a separate cause: ImagePullBackOff indicates failed image retrieval; cluster DNS, credentials, registry availability and image names are distinct potential causes. The reported condition is governed by: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. The two mechanisms should not be conflated.

C:

The offered statement is true for this other mechanism: The container runtime can terminate a container when it exceeds its memory cgroup limit; increasing CPU requests does not repair a memory limit failure. It does not explain the facts described here, which follow from: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending.

D:

This principle describes a separate cause: HPA CPU utilization is computed from reported metrics relative to requests; missing metrics or requests can prevent scaling decisions. The reported condition is governed by: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. The two mechanisms should not be conflated.

Question 915

At Northstar finance, in an isolated training cluster during a scheduled maintenance rehearsal: PVC invoice-data in namespace ledger remains Pending and Pod invoice-api cannot mount it; inspect provisioning events and class capability. 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 endpoint addresses appear for healthy selected Pods and test a request through invoice-svc.
  2. Run kubectl -n ledger get cronjob daily-archive -o yaml and verify suspend is false; observe a scheduled Job in the next eligible window.
  3. Run kubectl -n ledger get pvc invoice-data and confirm Bound with capacity and the intended StorageClass after correction.
  4. Run kubectl -n ledger get pod invoice-api and inspect matching EndpointSlices after correcting the probe or backend.

Explanation

Correct Answer

C:

Run kubectl -n ledger get pvc invoice-data and confirm Bound with capacity and the intended StorageClass after correction. This validates the affected object or control path, rather than only showing a command completed. The underlying reason is: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. The intended action is: Run kubectl -n ledger describe pvc invoice-data and kubectl get storageclass fast-block before recreating either resource.

Incorrect Answers

A:

The alternative verifies a different condition: A Service may exist without usable backends because labels or Pod readiness do not match expected routing. The current case instead depends on: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. Confirm that “Run kubectl -n ledger get pvc invoice-data and confirm Bound with capacity and the intended StorageClass after correction”.

B:

That test belongs to another control with this basis: A suspended CronJob skips creating scheduled Jobs even while its controller and time expression are valid. In the current case, the governing reason is: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. The direct verification is “Run kubectl -n ledger get pvc invoice-data and confirm Bound with capacity and the intended StorageClass after correction”.

D:

The alternative verifies a different condition: A running container is not necessarily Ready; failing readiness can remove a Pod from ready Service endpoints. The current case instead depends on: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. Confirm that “Run kubectl -n ledger get pvc invoice-data and confirm Bound with capacity and the intended StorageClass after correction”.

Question 916

At Northstar finance, in an isolated training cluster during a scheduled maintenance rehearsal: PVC invoice-data in namespace ledger remains Pending and Pod invoice-api cannot mount it; inspect provisioning events and class capability. 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. Set sensible retry limits and preserve failure logs for batch job diagnostics.
  3. Maintain image garbage-collection, log rotation and filesystem capacity alerts.
  4. Monitor CSI provisioning events and test StorageClass compatibility in advance.

Explanation

Correct Answer

D:

Monitor CSI provisioning events and test StorageClass compatibility in advance. This reduces recurrence of the specific operational failure. It reinforces the action: Run kubectl -n ledger describe pvc invoice-data and kubectl get storageclass fast-block before recreating either resource. The relevant mechanism is: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending.

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: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. Its prevention measure is “Monitor CSI provisioning events and test StorageClass compatibility in advance”.

B:

This routine guards against another mechanism: A Job retries failed Pod executions up to its backoff limit, but increasing retries does not repair an invalid command or missing dependency. The recurring exposure in the current case is: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. The matching preventive check is “Monitor CSI provisioning events and test StorageClass compatibility in advance”.

C:

The suggested review tracks a different technical risk: DiskPressure is a node condition triggered by storage thresholds; deleting live runtime data blindly can corrupt workloads. Here the sustained control must address: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. Choose “Monitor CSI provisioning events and test StorageClass compatibility in advance”.

Question 917

At Horizon observability, in a disposable simulated environment during a monitored release window: PVC metrics-data in namespace observability remains Pending and Pod metrics-api cannot mount it; inspect provisioning events and class capability. 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 service metrics-svc and compare Service targetPort with Pod listening port before patching.
  2. Run kubectl -n observability describe pvc metrics-data and kubectl get storageclass balanced-block before recreating either resource.
  3. Run kubectl -n observability describe hpa metrics-api and check the metrics API, CPU requests and target Pod selection.
  4. Run kubectl -n observability describe job hourly-rollup and get logs of its failed Pods before increasing retry limits.

Explanation

Correct Answer

B:

Run kubectl -n observability describe pvc metrics-data and kubectl get storageclass balanced-block before recreating either resource. This is the appropriate command-line action or first safe diagnostic. The technical reason is: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. Validate the result with: Run kubectl -n observability get pvc metrics-data and confirm Bound with capacity and the intended StorageClass after correction. 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: The Service routes to its configured backend target port; working DNS does not establish that the destination process is listening there. The reported case instead depends on: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. The action that directly addresses it is “Run kubectl -n observability describe pvc metrics-data and kubectl get storageclass balanced-block before recreating either resource”.

C:

The offered action targets: HPA CPU utilization is computed from reported metrics relative to requests; missing metrics or requests can prevent scaling decisions. The case facts point instead to: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. Implement “Run kubectl -n observability describe pvc metrics-data and kubectl get storageclass balanced-block before recreating either resource” to address that specific condition.

D:

This alternative is a response to another technical cause: A Job retries failed Pod executions up to its backoff limit, but increasing retries does not repair an invalid command or missing dependency. The reported case instead depends on: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. The action that directly addresses it is “Run kubectl -n observability describe pvc metrics-data and kubectl get storageclass balanced-block before recreating either resource”.

Question 918

At Horizon observability, in a disposable simulated environment during a monitored release window: PVC metrics-data in namespace observability remains Pending and Pod metrics-api cannot mount it; inspect provisioning events and class capability. Work only within the stated target and verify before declaring success. Which Kubernetes behavior best explains the required change or diagnosis?

  1. DiskPressure is a node condition triggered by storage thresholds; deleting live runtime data blindly can corrupt workloads.
  2. Liveness failure triggers restarts, while startup and readiness probes serve different lifecycle purposes.
  3. A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending.
  4. A Job retries failed Pod executions up to its backoff limit, but increasing retries does not repair an invalid command or missing dependency.

Explanation

Correct Answer

C:

A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. This explains the stated condition. The corresponding action is: Run kubectl -n observability describe pvc metrics-data and kubectl get storageclass balanced-block before recreating either resource. The direct acceptance evidence is: Run kubectl -n observability get pvc metrics-data and confirm Bound with capacity and the intended StorageClass after correction.

Incorrect Answers

A:

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: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending.

B:

The offered statement is true for this other mechanism: Liveness failure triggers restarts, while startup and readiness probes serve different lifecycle purposes. It does not explain the facts described here, which follow from: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending.

D:

A Job retries failed Pod executions up to its backoff limit, but increasing retries does not repair an invalid command or missing dependency. That explanation applies to a different technical failure. Here the controlling principle is: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending.

Question 919

At Horizon observability, in a disposable simulated environment during a monitored release window: PVC metrics-data in namespace observability remains Pending and Pod metrics-api cannot mount it; inspect provisioning events and class capability. 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 -n observability get pod metrics-api and inspect matching EndpointSlices after correcting the probe or backend.
  2. Confirm all dependent resources and controllers are cleaned up through supported procedures before the namespace disappears.
  3. Verify node disk pressure clears and relevant Pods become stable after approved cleanup or capacity changes.
  4. Run kubectl -n observability get pvc metrics-data and confirm Bound with capacity and the intended StorageClass after correction.

Explanation

Correct Answer

D:

Run kubectl -n observability get pvc metrics-data and confirm Bound with capacity and the intended StorageClass after correction. This validates the affected object or control path, rather than only showing a command completed. The underlying reason is: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. The intended action is: Run kubectl -n observability describe pvc metrics-data and kubectl get storageclass balanced-block before recreating either resource.

Incorrect Answers

A:

That test belongs to another control with this basis: A running container is not necessarily Ready; failing readiness can remove a Pod from ready Service endpoints. In the current case, the governing reason is: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. The direct verification is “Run kubectl -n observability get pvc metrics-data and confirm Bound with capacity and the intended StorageClass after correction”.

B:

This observation would test a different technical dependency: Finalizers protect cleanup work; forcibly removing them without identifying failing controllers can orphan resources and leak infrastructure. The current issue is governed by: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. Its decisive check is “Run kubectl -n observability get pvc metrics-data and confirm Bound with capacity and the intended StorageClass after correction”.

C:

The alternative verifies a different condition: DiskPressure is a node condition triggered by storage thresholds; deleting live runtime data blindly can corrupt workloads. The current case instead depends on: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. Confirm that “Run kubectl -n observability get pvc metrics-data and confirm Bound with capacity and the intended StorageClass after correction”.

Question 920

At Horizon observability, in a disposable simulated environment during a monitored release window: PVC metrics-data in namespace observability remains Pending and Pod metrics-api cannot mount it; inspect provisioning events and class capability. Work only within the stated target and verify before declaring success. Which operational control most directly prevents this failure or configuration drift?

  1. Monitor CSI provisioning events and test StorageClass compatibility in advance.
  2. Validate DaemonSet coverage whenever node labels, pools or taints change.
  3. Maintain policy test matrices for required app flows, DNS, telemetry and denied peers.
  4. Validate registry credentials and image digests before rollout to constrained clusters.

Explanation

Correct Answer

A:

Monitor CSI provisioning events and test StorageClass compatibility in advance. This reduces recurrence of the specific operational failure. It reinforces the action: Run kubectl -n observability describe pvc metrics-data and kubectl get storageclass balanced-block before recreating either resource. The relevant mechanism is: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending.

Incorrect Answers

B:

The suggested review tracks a different technical risk: DaemonSets schedule according to node selection and toleration rules; unavailable node agents can break networking or logging on selected workers. Here the sustained control must address: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. Choose “Monitor CSI provisioning events and test StorageClass compatibility in advance”.

C:

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: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. Its prevention measure is “Monitor CSI provisioning events and test StorageClass compatibility in advance”.

D:

This routine guards against another mechanism: ImagePullBackOff indicates failed image retrieval; cluster DNS, credentials, registry availability and image names are distinct potential causes. The recurring exposure in the current case is: A PVC binds only to compatible available storage or successful dynamic provisioning; absent provisioners, quotas or delayed binding can leave it Pending. The matching preventive check is “Monitor CSI provisioning events and test StorageClass compatibility in advance”.