Linux Foundation KCNA Practice Test 57
Question 560
After a node failure the Deployment stays below desired replicas and the platform team inspects only running application logs. Which observable result BEST confirms the desired Kubernetes or cloud native behavior?
- All intended replicas run the approved digest and upgrades trace back to a reviewed artifact.
- Cluster state can be recovered from a tested snapshot with quorum intact and application volumes handled separately.
- Missing workload replicas are recreated from their controllers and desired counts converge after disruptions.
- The container sees the intended isolated resources while usage limits are reflected in host accounting.
Explanation
Correct Answer
C:Missing workload replicas are recreated from their controllers and desired counts converge after disruptions. This is an observable service outcome, not just evidence that a configuration file was saved. Controllers continuously reconcile desired state; an isolated manually created Pod lacks a Deployment's replica management. Workload context: After a node failure the Deployment stays below desired replicas and the platform team inspects only running application logs.
Incorrect Answers
A:All intended replicas run the approved digest and upgrades trace back to a reviewed artifact. That result validates Immutable container images and digests rather than the requirement here. Verify instead: Missing workload replicas are recreated from their controllers and desired counts converge after disruptions. Workload context: After a node failure the Deployment stays below desired replicas and the platform team inspects only running application logs.
B:Cluster state can be recovered from a tested snapshot with quorum intact and application volumes handled separately. That result validates etcd consistency and cluster state rather than the requirement here. Verify instead: Missing workload replicas are recreated from their controllers and desired counts converge after disruptions. Workload context: After a node failure the Deployment stays below desired replicas and the platform team inspects only running application logs.
D:The container sees the intended isolated resources while usage limits are reflected in host accounting. That result validates Linux namespaces and cgroups rather than the requirement here. Verify instead: Missing workload replicas are recreated from their controllers and desired counts converge after disruptions. Workload context: After a node failure the Deployment stays below desired replicas and the platform team inspects only running application logs.
Question 561
A release renames Pod labels and the frontend's Service has no endpoints despite available healthy Pods. Which observable result BEST confirms the desired Kubernetes or cloud native behavior?
- The application operates within measured memory budgets or receives justified capacity changes without repeated OOM restarts.
- The Service has healthy matching backends and forwards to the application process's actual port.
- Pods on different eligible nodes communicate according to network design and report working network addresses.
- The precise scheduling blocker is removed and the workload binds to an eligible node.
Explanation
Correct Answer
B:The Service has healthy matching backends and forwards to the application process's actual port. This is an observable service outcome, not just evidence that a configuration file was saved. A Service can resolve in DNS yet have zero endpoints or forward to an incorrect port. Workload context: A release renames Pod labels and the frontend's Service has no endpoints despite available healthy Pods.
Incorrect Answers
A:The application operates within measured memory budgets or receives justified capacity changes without repeated OOM restarts. That result validates Container OOMKilled and resource pressure rather than the requirement here. Verify instead: The Service has healthy matching backends and forwards to the application process's actual port. Workload context: A release renames Pod labels and the frontend's Service has no endpoints despite available healthy Pods.
C:Pods on different eligible nodes communicate according to network design and report working network addresses. That result validates CNI Pod networking implementation rather than the requirement here. Verify instead: The Service has healthy matching backends and forwards to the application process's actual port. Workload context: A release renames Pod labels and the frontend's Service has no endpoints despite available healthy Pods.
D:The precise scheduling blocker is removed and the workload binds to an eligible node. That result validates Pending pod FailedScheduling events rather than the requirement here. Verify instead: The Service has healthy matching backends and forwards to the application process's actual port. Workload context: A release renames Pod labels and the frontend's Service has no endpoints despite available healthy Pods.
Question 562
A manifest overrides command with an interactive shell that exits immediately instead of starting the web process. Which Kubernetes or cloud native approach BEST addresses the stated requirement?
- Let kubelet on each node reconcile assigned Pod specifications with the container runtime and report node and Pod status.
- Use a compatible container runtime via the Kubernetes Container Runtime Interface to create and manage containers on nodes.
- Use an authorized ephemeral container for live Pod diagnostics when the original image lacks troubleshooting tools.
- Set container command and args with awareness of how Kubernetes overrides image ENTRYPOINT and CMD defaults.
Explanation
Correct Answer
D:Set container command and args with awareness of how Kubernetes overrides image ENTRYPOINT and CMD defaults. This response implements the controlling Kubernetes or cloud native principle. Kubernetes command maps to the image ENTRYPOINT override and args maps to CMD arguments; a process exit can restart a Pod. Check its effect by: Inspect image metadata, Pod command/args, process exit code and startup logs. Workload context: A manifest overrides command with an interactive shell that exits immediately instead of starting the web process.
Incorrect Answers
A:Let kubelet on each node reconcile assigned Pod specifications with the container runtime and report node and Pod status. This action addresses Kubelet node agent responsibilities instead of the controlling requirement. kubelet manages Pod execution on a node; it does not serve the central Kubernetes API or select new nodes. For this scenario prefer: Set container command and args with awareness of how Kubernetes overrides image ENTRYPOINT and CMD defaults. Workload context: A manifest overrides command with an interactive shell that exits immediately instead of starting the web process.
B:Use a compatible container runtime via the Kubernetes Container Runtime Interface to create and manage containers on nodes. This action addresses Container runtime and CRI instead of the controlling requirement. A runtime executes containers; the CRI is its API integration with kubelet rather than the Kubernetes API server. For this scenario prefer: Set container command and args with awareness of how Kubernetes overrides image ENTRYPOINT and CMD defaults. Workload context: A manifest overrides command with an interactive shell that exits immediately instead of starting the web process.
C:Use an authorized ephemeral container for live Pod diagnostics when the original image lacks troubleshooting tools. This action addresses Ephemeral debugging containers instead of the controlling requirement. Ephemeral containers are intended for debugging and do not behave like ordinary replicated application containers. For this scenario prefer: Set container command and args with awareness of how Kubernetes overrides image ENTRYPOINT and CMD defaults. Workload context: A manifest overrides command with an interactive shell that exits immediately instead of starting the web process.
Question 563
An analyst launches a debug container with host privileges even though inspecting a shared Pod network namespace would suffice. Which evidence should the engineer inspect FIRST to distinguish the likely cause or verify the prerequisite?
- Compare object metadata labels, Service/Deployment selectors and selected object lists.
- Check registry path, pull Secret, tag or digest, IAM grant, TLS trust and registry audit logs.
- Inspect Pod ephemeralContainers entries, RBAC privileges, target process namespace and active diagnostic sessions.
- Check NodeReady condition, kubelet heartbeats, network connectivity, pressure conditions and scheduler events.
Explanation
Correct Answer
C:Inspect Pod ephemeralContainers entries, RBAC privileges, target process namespace and active diagnostic sessions. This is the most discriminating evidence for the described failure or requirement. Ephemeral containers are intended for debugging and do not behave like ordinary replicated application containers. The corresponding implementation is: Use an authorized ephemeral container for live Pod diagnostics when the original image lacks troubleshooting tools. Workload context: An analyst launches a debug container with host privileges even though inspecting a shared Pod network namespace would suffice.
Incorrect Answers
A:Compare object metadata labels, Service/Deployment selectors and selected object lists. These observations are more relevant to Labels selectors and annotations, not this case. The distinguishing check is: Inspect Pod ephemeralContainers entries, RBAC privileges, target process namespace and active diagnostic sessions. Workload context: An analyst launches a debug container with host privileges even though inspecting a shared Pod network namespace would suffice.
B:Check registry path, pull Secret, tag or digest, IAM grant, TLS trust and registry audit logs. These observations are more relevant to OCI registries and image distribution, not this case. The distinguishing check is: Inspect Pod ephemeralContainers entries, RBAC privileges, target process namespace and active diagnostic sessions. Workload context: An analyst launches a debug container with host privileges even though inspecting a shared Pod network namespace would suffice.
D:Check NodeReady condition, kubelet heartbeats, network connectivity, pressure conditions and scheduler events. These observations are more relevant to Node readiness and scheduling exclusion, not this case. The distinguishing check is: Inspect Pod ephemeralContainers entries, RBAC privileges, target process namespace and active diagnostic sessions. Workload context: An analyst launches a debug container with host privileges even though inspecting a shared Pod network namespace would suffice.
Question 564
A PV enters Released after claim deletion and an engineer expects it to bind another PVC without reviewing retained data and claimRef. Which evidence should the engineer inspect FIRST to distinguish the likely cause or verify the prerequisite?
- Inspect Service metadata, selected Pod labels, EndpointSlice readiness, containerPort and actual listening sockets.
- Inspect StorageClass provisioner name, allowed topology, PVC events and CSI controller logs.
- Inspect StatefulSet ordinal Pod names, headless Service, volumeClaimTemplates and update strategy.
- Inspect PV persistentVolumeReclaimPolicy, underlying disk state, claim release and storage provisioner behavior.
Explanation
Correct Answer
D:Inspect PV persistentVolumeReclaimPolicy, underlying disk state, claim release and storage provisioner behavior. This is the most discriminating evidence for the described failure or requirement. Retain leaves storage for deliberate recovery; Delete usually removes underlying dynamically provisioned storage when supported. The corresponding implementation is: Select PV reclaim policies according to retention requirements and verify storage cleanup or recovery steps after PVC deletion. Workload context: A PV enters Released after claim deletion and an engineer expects it to bind another PVC without reviewing retained data and claimRef.
Incorrect Answers
A:Inspect Service metadata, selected Pod labels, EndpointSlice readiness, containerPort and actual listening sockets. These observations are more relevant to Service selector and port mismatch diagnostics, not this case. The distinguishing check is: Inspect PV persistentVolumeReclaimPolicy, underlying disk state, claim release and storage provisioner behavior. Workload context: A PV enters Released after claim deletion and an engineer expects it to bind another PVC without reviewing retained data and claimRef.
B:Inspect StorageClass provisioner name, allowed topology, PVC events and CSI controller logs. These observations are more relevant to StorageClass dynamic provisioning, not this case. The distinguishing check is: Inspect PV persistentVolumeReclaimPolicy, underlying disk state, claim release and storage provisioner behavior. Workload context: A PV enters Released after claim deletion and an engineer expects it to bind another PVC without reviewing retained data and claimRef.
C:Inspect StatefulSet ordinal Pod names, headless Service, volumeClaimTemplates and update strategy. These observations are more relevant to StatefulSet identity and volume templates, not this case. The distinguishing check is: Inspect PV persistentVolumeReclaimPolicy, underlying disk state, claim release and storage provisioner behavior. Workload context: A PV enters Released after claim deletion and an engineer expects it to bind another PVC without reviewing retained data and claimRef.
Question 565
An engineer changes node affinity to fix repeated process crashes even though the Pod already has a healthy node assignment. Which TWO complementary steps supply the appropriate approach AND the evidence required to validate it? Select TWO.
- Review container lastState, exit code, restart count, previous logs and application configuration.
- Use Pod events and scheduler reasons to diagnose Pending workloads before changing application images or reading nonexistent logs.
- Inspect restart history and previous-container logs to diagnose repeatedly exiting containers and fix startup or runtime failures.
- Temporary data is disposable while durable application records remain accessible across Pod recreation.
- Inspect OOMKilled exit reason, memory limit, heap behavior, node pressure and container metrics.
Explanation
Correct Answers
A:Review container lastState, exit code, restart count, previous logs and application configuration. This is the most discriminating evidence for the described failure or requirement. CrashLoopBackOff indicates repeated container exits and restart delays, not a scheduler placement failure. The corresponding implementation is: Inspect restart history and previous-container logs to diagnose repeatedly exiting containers and fix startup or runtime failures. This is the diagnostic evidence part of the paired answer. Workload context: An engineer changes node affinity to fix repeated process crashes even though the Pod already has a healthy node assignment.
C:Inspect restart history and previous-container logs to diagnose repeatedly exiting containers and fix startup or runtime failures. This response implements the controlling Kubernetes or cloud native principle. CrashLoopBackOff indicates repeated container exits and restart delays, not a scheduler placement failure. Check its effect by: Review container lastState, exit code, restart count, previous logs and application configuration. This is the implementation part of the required paired answer. Workload context: An engineer changes node affinity to fix repeated process crashes even though the Pod already has a healthy node assignment.
Incorrect Answers
B:Use Pod events and scheduler reasons to diagnose Pending workloads before changing application images or reading nonexistent logs. This step belongs to Pending pod FailedScheduling events rather than the complementary implementation and evidence pair. The intended approach is: Inspect restart history and previous-container logs to diagnose repeatedly exiting containers and fix startup or runtime failures. Validate with: Review container lastState, exit code, restart count, previous logs and application configuration. Workload context: An engineer changes node affinity to fix repeated process crashes even though the Pod already has a healthy node assignment.
D:Temporary data is disposable while durable application records remain accessible across Pod recreation. This step belongs to Ephemeral emptyDir versus persistent volumes rather than the complementary implementation and evidence pair. The intended approach is: Inspect restart history and previous-container logs to diagnose repeatedly exiting containers and fix startup or runtime failures. Validate with: Review container lastState, exit code, restart count, previous logs and application configuration. Workload context: An engineer changes node affinity to fix repeated process crashes even though the Pod already has a healthy node assignment.
E:Inspect OOMKilled exit reason, memory limit, heap behavior, node pressure and container metrics. This step belongs to Container OOMKilled and resource pressure rather than the complementary implementation and evidence pair. The intended approach is: Inspect restart history and previous-container logs to diagnose repeatedly exiting containers and fix startup or runtime failures. Validate with: Review container lastState, exit code, restart count, previous logs and application configuration. Workload context: An engineer changes node affinity to fix repeated process crashes even though the Pod already has a healthy node assignment.
Question 566
A developer puts an unsupported spec field in a ConfigMap and assumes YAML formatting guarantees correct Kubernetes behavior. Which observable result BEST confirms the desired Kubernetes or cloud native behavior?
- Workloads read needed configuration while unauthorized users cannot retrieve credential material through the API.
- Cluster state can be recovered from a tested snapshot with quorum intact and application volumes handled separately.
- Stateless replicas converge to the declared count and rolling updates progress without manual Pod recreation.
- A supported resource can be applied predictably and unknown fields or removed API versions are identified before rollout.
Explanation
Correct Answer
D:A supported resource can be applied predictably and unknown fields or removed API versions are identified before rollout. This is an observable service outcome, not just evidence that a configuration file was saved. Kubernetes API versions are resource-specific and evolve; a valid YAML file does not guarantee the API accepts its kind or schema. Workload context: A developer puts an unsupported spec field in a ConfigMap and assumes YAML formatting guarantees correct Kubernetes behavior.
Incorrect Answers
A:Workloads read needed configuration while unauthorized users cannot retrieve credential material through the API. That result validates ConfigMap and Secret boundaries rather than the requirement here. Verify instead: A supported resource can be applied predictably and unknown fields or removed API versions are identified before rollout. Workload context: A developer puts an unsupported spec field in a ConfigMap and assumes YAML formatting guarantees correct Kubernetes behavior.
B:Cluster state can be recovered from a tested snapshot with quorum intact and application volumes handled separately. That result validates etcd consistency and cluster state rather than the requirement here. Verify instead: A supported resource can be applied predictably and unknown fields or removed API versions are identified before rollout. Workload context: A developer puts an unsupported spec field in a ConfigMap and assumes YAML formatting guarantees correct Kubernetes behavior.
C:Stateless replicas converge to the declared count and rolling updates progress without manual Pod recreation. That result validates Deployment and ReplicaSet ownership rather than the requirement here. Verify instead: A supported resource can be applied predictably and unknown fields or removed API versions are identified before rollout. Workload context: A developer puts an unsupported spec field in a ConfigMap and assumes YAML formatting guarantees correct Kubernetes behavior.
Question 567
An operator assumes a strict PDB will keep an application online even when every worker suffers a power outage. Which Kubernetes or cloud native approach BEST addresses the stated requirement?
- Set topologySpreadConstraints to balance replicated Pods across zones or nodes with an explicit maxSkew and unsatisfiable action.
- Align volume topology with Pod scheduling, using StorageClass binding behavior appropriate for zonal storage.
- Configure PodDisruptionBudgets for voluntary disruptions while distinguishing eviction safety from normal scheduling decisions.
- Use namespaces to group namespaced resources and policies, and add explicit RBAC and network controls for isolation.
Explanation
Correct Answer
C:Configure PodDisruptionBudgets for voluntary disruptions while distinguishing eviction safety from normal scheduling decisions. This response implements the controlling Kubernetes or cloud native principle. A PodDisruptionBudget governs voluntary eviction; it does not guarantee protection against hardware failure or create new replicas. Check its effect by: Inspect allowedDisruptions, healthy replicas, minAvailable/maxUnavailable and drain eviction results. Workload context: An operator assumes a strict PDB will keep an application online even when every worker suffers a power outage.
Incorrect Answers
A:Set topologySpreadConstraints to balance replicated Pods across zones or nodes with an explicit maxSkew and unsatisfiable action. This action addresses Topology spread constraints instead of the controlling requirement. Spread constraints balance matching Pods across topology domains; missing topology labels and strict maxSkew can prevent placement. For this scenario prefer: Configure PodDisruptionBudgets for voluntary disruptions while distinguishing eviction safety from normal scheduling decisions. Workload context: An operator assumes a strict PDB will keep an application online even when every worker suffers a power outage.
B:Align volume topology with Pod scheduling, using StorageClass binding behavior appropriate for zonal storage. This action addresses PersistentVolume zone binding and placement instead of the controlling requirement. Immediate volume binding can constrain later Pod placement, while WaitForFirstConsumer accounts for scheduling topology. For this scenario prefer: Configure PodDisruptionBudgets for voluntary disruptions while distinguishing eviction safety from normal scheduling decisions. Workload context: An operator assumes a strict PDB will keep an application online even when every worker suffers a power outage.
D:Use namespaces to group namespaced resources and policies, and add explicit RBAC and network controls for isolation. This action addresses Namespace scope and limits instead of the controlling requirement. Namespaces organize resource names but are not automatically strong security boundaries or separate clusters. For this scenario prefer: Configure PodDisruptionBudgets for voluntary disruptions while distinguishing eviction safety from normal scheduling decisions. Workload context: An operator assumes a strict PDB will keep an application online even when every worker suffers a power outage.
Question 568
A team adds a liveness probe to a transient overloaded endpoint and starts a restart storm instead of isolating readiness behavior. Which Kubernetes or cloud native approach BEST addresses the stated requirement?
- Select and operate a Kubernetes-compatible CNI implementation to provide Pod IP connectivity and required network capabilities.
- Use Pod events and scheduler reasons to diagnose Pending workloads before changing application images or reading nonexistent logs.
- Use emptyDir for temporary Pod-scoped data and PVC-backed volumes when data must survive Pod replacement.
- Assign readiness for traffic acceptance, liveness for unhealthy restarts and startup for slow initialization when appropriate.
Explanation
Correct Answer
D:Assign readiness for traffic acceptance, liveness for unhealthy restarts and startup for slow initialization when appropriate. This response implements the controlling Kubernetes or cloud native principle. Readiness failure removes a Pod from ready endpoints; liveness failure may restart a container. Check its effect by: Inspect probe paths, thresholds, failure conditions, Service endpoints and container restart events. Workload context: A team adds a liveness probe to a transient overloaded endpoint and starts a restart storm instead of isolating readiness behavior.
Incorrect Answers
A:Select and operate a Kubernetes-compatible CNI implementation to provide Pod IP connectivity and required network capabilities. This action addresses CNI Pod networking implementation instead of the controlling requirement. The CNI plugin supplies Pod networking; a Kubernetes Service alone cannot correct a broken Pod network implementation. For this scenario prefer: Assign readiness for traffic acceptance, liveness for unhealthy restarts and startup for slow initialization when appropriate. Workload context: A team adds a liveness probe to a transient overloaded endpoint and starts a restart storm instead of isolating readiness behavior.
B:Use Pod events and scheduler reasons to diagnose Pending workloads before changing application images or reading nonexistent logs. This action addresses Pending pod FailedScheduling events instead of the controlling requirement. Pending may mean unschedulable or image preparation; distinguish whether node assignment occurred before choosing next checks. For this scenario prefer: Assign readiness for traffic acceptance, liveness for unhealthy restarts and startup for slow initialization when appropriate. Workload context: A team adds a liveness probe to a transient overloaded endpoint and starts a restart storm instead of isolating readiness behavior.
C:Use emptyDir for temporary Pod-scoped data and PVC-backed volumes when data must survive Pod replacement. This action addresses Ephemeral emptyDir versus persistent volumes instead of the controlling requirement. emptyDir exists for the lifetime of a Pod on a node and is lost when the Pod is removed. For this scenario prefer: Assign readiness for traffic acceptance, liveness for unhealthy restarts and startup for slow initialization when appropriate. Workload context: A team adds a liveness probe to a transient overloaded endpoint and starts a restart storm instead of isolating readiness behavior.
Question 569
Developers believe storing YAML in Git is sufficient GitOps despite having no automated pull reconciliation or drift detection. Which Kubernetes or cloud native approach BEST addresses the stated requirement?
- Trace external HTTP requests through DNS, ingress/Gateway association, TLS configuration, Service and Pod endpoints.
- Compare rollout history and resource generations to identify whether application failures correlate with a new deployment revision.
- Package related Kubernetes resources as a Helm chart and manage per-environment configuration with reviewed values and release history.
- Use a versioned Git repository as declarative desired state and a reconciler to detect and correct drift with approved change controls.
Explanation
Correct Answer
D:Use a versioned Git repository as declarative desired state and a reconciler to detect and correct drift with approved change controls. This response implements the controlling Kubernetes or cloud native principle. GitOps is a pull/reconciliation operating model rather than merely running kubectl from a CI server. Check its effect by: Compare Git revision, application sync status, live resource diff and reconciliation events. Workload context: Developers believe storing YAML in Git is sufficient GitOps despite having no automated pull reconciliation or drift detection.
Incorrect Answers
A:Trace external HTTP requests through DNS, ingress/Gateway association, TLS configuration, Service and Pod endpoints. This action addresses Ingress route and TLS mismatch diagnosis instead of the controlling requirement. A healthy Service does not guarantee correct edge routing; ingress controllers and TLS bindings add separate layers. For this scenario prefer: Use a versioned Git repository as declarative desired state and a reconciler to detect and correct drift with approved change controls. Workload context: Developers believe storing YAML in Git is sufficient GitOps despite having no automated pull reconciliation or drift detection.
B:Compare rollout history and resource generations to identify whether application failures correlate with a new deployment revision. This action addresses Rollout history status and change correlation instead of the controlling requirement. A Deployment being Available does not prove all new replicas are healthy or that a rollout has fully progressed. For this scenario prefer: Use a versioned Git repository as declarative desired state and a reconciler to detect and correct drift with approved change controls. Workload context: Developers believe storing YAML in Git is sufficient GitOps despite having no automated pull reconciliation or drift detection.
C:Package related Kubernetes resources as a Helm chart and manage per-environment configuration with reviewed values and release history. This action addresses Helm charts templates and values instead of the controlling requirement. Helm templates generate manifests; a chart repository alone does not deploy resources or validate runtime behavior. For this scenario prefer: Use a versioned Git repository as declarative desired state and a reconciler to detect and correct drift with approved change controls. Workload context: Developers believe storing YAML in Git is sufficient GitOps despite having no automated pull reconciliation or drift detection.
Question 570
A workload with a custom zone selector is stuck because nodes use a different label key than the manifest. Which TWO complementary steps supply the appropriate approach AND the evidence required to validate it? Select TWO.
- Maintain accurate node labels, allocatable resources and topology information to support workload placement and capacity analysis.
- Inspect Pod scheduling events, available node capacity, taints, selectors and assigned nodeName.
- Set workload requests for placement and limits for bounded runtime use based on measured application needs.
- Review node labels, conditions, capacity versus allocatable, topology zones and node allocatable metrics.
- Replica placement stays within the intended skew or reports clear scheduling limits.
Explanation
Correct Answers
A:Maintain accurate node labels, allocatable resources and topology information to support workload placement and capacity analysis. This response implements the controlling Kubernetes or cloud native principle. Node allocatable excludes reservations from raw capacity; labels must reflect real node capabilities and administration. Check its effect by: Review node labels, conditions, capacity versus allocatable, topology zones and node allocatable metrics. This is the implementation part of the required paired answer. Workload context: A workload with a custom zone selector is stuck because nodes use a different label key than the manifest.
D:Review node labels, conditions, capacity versus allocatable, topology zones and node allocatable metrics. This is the most discriminating evidence for the described failure or requirement. Node allocatable excludes reservations from raw capacity; labels must reflect real node capabilities and administration. The corresponding implementation is: Maintain accurate node labels, allocatable resources and topology information to support workload placement and capacity analysis. This is the diagnostic evidence part of the paired answer. Workload context: A workload with a custom zone selector is stuck because nodes use a different label key than the manifest.
Incorrect Answers
B:Inspect Pod scheduling events, available node capacity, taints, selectors and assigned nodeName. This step belongs to Scheduler responsibility and binding rather than the complementary implementation and evidence pair. The intended approach is: Maintain accurate node labels, allocatable resources and topology information to support workload placement and capacity analysis. Validate with: Review node labels, conditions, capacity versus allocatable, topology zones and node allocatable metrics. Workload context: A workload with a custom zone selector is stuck because nodes use a different label key than the manifest.
C:Set workload requests for placement and limits for bounded runtime use based on measured application needs. This step belongs to CPU requests and memory limits rather than the complementary implementation and evidence pair. The intended approach is: Maintain accurate node labels, allocatable resources and topology information to support workload placement and capacity analysis. Validate with: Review node labels, conditions, capacity versus allocatable, topology zones and node allocatable metrics. Workload context: A workload with a custom zone selector is stuck because nodes use a different label key than the manifest.
E:Replica placement stays within the intended skew or reports clear scheduling limits. This step belongs to Topology spread constraints rather than the complementary implementation and evidence pair. The intended approach is: Maintain accurate node labels, allocatable resources and topology information to support workload placement and capacity analysis. Validate with: Review node labels, conditions, capacity versus allocatable, topology zones and node allocatable metrics. Workload context: A workload with a custom zone selector is stuck because nodes use a different label key than the manifest.