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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: Select PV reclaim policies according to retention requirements and verify storage cleanup or recovery steps after PVC deletion. Workload context: A production dataset's PV uses Delete and its administrator removes the claim assuming the raw disk must be retained.

Use PVCs to request persistent storage and PVs to represent volumes whose lifecycle is separate from ephemeral Pods. This action addresses PersistentVolume and claim bindings instead of the controlling requirement. A PVC is a storage request and a PV is a cluster storage resource; neither should be confused with an emptyDir volume. For this scenario prefer: Select PV reclaim policies according to retention requirements and verify storage cleanup or recovery steps after PVC deletion. Workload context: A production dataset's PV uses Delete and its administrator removes the claim assuming the raw disk must be retained.

Use a Service type LoadBalancer with a supported cloud or in-cluster load-balancer controller to provide an approved external endpoint. This action addresses LoadBalancer Service provisioning instead of the controlling requirement. A LoadBalancer Service depends on an implementation or provider controller; creating it does not guarantee an external address. For this scenario prefer: Select PV reclaim policies according to retention requirements and verify storage cleanup or recovery steps after PVC deletion. Workload context: A production dataset's PV uses Delete and its administrator removes the claim assuming the raw disk must be retained.

Feasible Pods are scheduled after resource or policy conflicts are resolved without overcommitting critical nodes. That result validates Pending Pods and resource-fit checks rather than the requirement here. Verify instead: Scheduling constraints match verified node attributes without exhausting reserved system resources. Workload context: A workload with a custom zone selector is stuck because nodes use a different label key than the manifest.

Pods schedule based on requests and stay within resource policy without avoidable throttling or memory termination. That result validates CPU requests and memory limits rather than the requirement here. Verify instead: Scheduling constraints match verified node attributes without exhausting reserved system resources. Workload context: A workload with a custom zone selector is stuck because nodes use a different label key than the manifest.

Workloads relocate where permitted and the maintained node returns to service without unexpected data loss. That result validates Node cordon drain maintenance rather than the requirement here. Verify instead: Scheduling constraints match verified node attributes without exhausting reserved system resources. Workload context: A workload with a custom zone selector is stuck because nodes use a different label key than the manifest.

Plan component upgrades using the currently supported version-skew policy and validated addon compatibility rather than upgrading arbitrarily. This step belongs to Kubernetes upgrades and version skew rather than the complementary implementation and evidence pair. The intended approach is: Use a DaemonSet to run a supported node agent across eligible nodes, respecting taints and selectors. Validate with: Inspect DaemonSet desired/current/ready counts, node eligibility, tolerations and per-node Pod placement. Workload context: A new Kubernetes node receives workloads but has no metrics agent because the DaemonSet's node selector excludes it.

Eligible Pending Pods trigger appropriate capacity increases and then receive scheduler bindings. This step belongs to Scheduler versus autoscaler responsibility rather than the complementary implementation and evidence pair. The intended approach is: Use a DaemonSet to run a supported node agent across eligible nodes, respecting taints and selectors. Validate with: Inspect DaemonSet desired/current/ready counts, node eligibility, tolerations and per-node Pod placement. Workload context: A new Kubernetes node receives workloads but has no metrics agent because the DaemonSet's node selector excludes it.

Inspect SBOM package inventory, CVE applicability, signature validation and approved exception decisions. This step belongs to Image scanning and software bills of materials rather than the complementary implementation and evidence pair. The intended approach is: Use a DaemonSet to run a supported node agent across eligible nodes, respecting taints and selectors. Validate with: Inspect DaemonSet desired/current/ready counts, node eligibility, tolerations and per-node Pod placement. Workload context: A new Kubernetes node receives workloads but has no metrics agent because the DaemonSet's node selector excludes it.

Use CoreDNS or the configured cluster DNS service to resolve Service and Pod naming in their correct namespaces. This action addresses Cluster DNS and service discovery instead of the controlling requirement. Kubernetes DNS uses namespace-aware search paths; a fully qualified Service name avoids ambiguity across namespaces. For this scenario prefer: Trace requests through Service DNS, selector, EndpointSlice and targetPort before attributing all timeouts to network latency. Workload context: An API listens on port 9000 but its Service targetPort remains 8080 from a previous release.

Diagnose memory limit terminations using lastState and observed working-set growth rather than assuming every restart is application logic. This action addresses Container OOMKilled and resource pressure instead of the controlling requirement. Container memory exceeding its cgroup limit can trigger OOMKilled even when node aggregate memory seems available. For this scenario prefer: Trace requests through Service DNS, selector, EndpointSlice and targetPort before attributing all timeouts to network latency. Workload context: An API listens on port 9000 but its Service targetPort remains 8080 from a previous release.

Inspect restart history and previous-container logs to diagnose repeatedly exiting containers and fix startup or runtime failures. This action addresses CrashLoopBackOff and previous logs instead of the controlling requirement. CrashLoopBackOff indicates repeated container exits and restart delays, not a scheduler placement failure. For this scenario prefer: Trace requests through Service DNS, selector, EndpointSlice and targetPort before attributing all timeouts to network latency. Workload context: An API listens on port 9000 but its Service targetPort remains 8080 from a previous release.

Inspect Pod label selectors, namespaces, topologyKey and actual placement of matching peer Pods. These observations are more relevant to Pod affinity anti-affinity, not this case. The distinguishing check is: Compare host kernel sharing, namespace isolation, hypervisor boundaries and workload trust requirements. Workload context: A multi-tenant hosting provider runs untrusted code and assumes a container namespace is equivalent to a separate hypervisor VM.

Check server and kubelet versions, deprecated APIs, CNI/CSI compatibility, maintenance order and rollback limits. These observations are more relevant to Kubernetes upgrades and version skew, not this case. The distinguishing check is: Compare host kernel sharing, namespace isolation, hypervisor boundaries and workload trust requirements. Workload context: A multi-tenant hosting provider runs untrusted code and assumes a container namespace is equivalent to a separate hypervisor VM.

Inspect Pod ephemeralContainers entries, RBAC privileges, target process namespace and active diagnostic sessions. These observations are more relevant to Ephemeral debugging containers, not this case. The distinguishing check is: Compare host kernel sharing, namespace isolation, hypervisor boundaries and workload trust requirements. Workload context: A multi-tenant hosting provider runs untrusted code and assumes a container namespace is equivalent to a separate hypervisor VM.

The helper supports the main app and its lifecycle is correctly coordinated during start and shutdown. That result validates Sidecar containers and shared Pod lifecycle rather than the requirement here. Verify instead: Eligible nodes retrieve authorized images while unrelated namespaces and identities cannot pull private artifacts. Workload context: A private image pull returns Unauthorized because the namespace has no correctly scoped imagePullSecret.

Critical workloads gain capacity when eligible without uncontrolled eviction of unrelated protected services. That result validates PriorityClass and preemption rather than the requirement here. Verify instead: Eligible nodes retrieve authorized images while unrelated namespaces and identities cannot pull private artifacts. Workload context: A private image pull returns Unauthorized because the namespace has no correctly scoped imagePullSecret.

An operator investigates a running Pod without modifying its immutable application image or replacing production workload containers. That result validates Ephemeral debugging containers rather than the requirement here. Verify instead: Eligible nodes retrieve authorized images while unrelated namespaces and identities cannot pull private artifacts. Workload context: A private image pull returns Unauthorized because the namespace has no correctly scoped imagePullSecret.

Check resource namespace, role bindings, quotas and effective network enforcement across namespaces. These observations are more relevant to Namespace scope and limits, not this case. The distinguishing check is: Inspect image metadata, Pod command/args, process exit code and startup logs. Workload context: A service enters CrashLoopBackOff because an override points at a binary absent from the container image.

Compare host kernel sharing, namespace isolation, hypervisor boundaries and workload trust requirements. These observations are more relevant to Container versus virtual machine isolation, not this case. The distinguishing check is: Inspect image metadata, Pod command/args, process exit code and startup logs. Workload context: A service enters CrashLoopBackOff because an override points at a binary absent from the container image.

Inspect process namespace, container cgroup limits, OOM events and host resource metrics. These observations are more relevant to Linux namespaces and cgroups, not this case. The distinguishing check is: Inspect image metadata, Pod command/args, process exit code and startup logs. Workload context: A service enters CrashLoopBackOff because an override points at a binary absent from the container image.

External clients reach only the intended healthy Service backends and the allocated endpoint matches network policy. That result validates LoadBalancer Service provisioning rather than the requirement here. Verify instead: Clients resolve the intended in-cluster Service name and external DNS forwarding operates as designed. Workload context: All Pods can communicate by IP but names intermittently fail after CoreDNS replicas become unready.

Temporary data is disposable while durable application records remain accessible across Pod recreation. That result validates Ephemeral emptyDir versus persistent volumes rather than the requirement here. Verify instead: Clients resolve the intended in-cluster Service name and external DNS forwarding operates as designed. Workload context: All Pods can communicate by IP but names intermittently fail after CoreDNS replicas become unready.

Applications mount volumes with the requested access pattern without unsupported simultaneous access assumptions. That result validates ReadWriteOnce and ReadWriteMany semantics rather than the requirement here. Verify instead: Clients resolve the intended in-cluster Service name and external DNS forwarding operates as designed. Workload context: All Pods can communicate by IP but names intermittently fail after CoreDNS replicas become unready.

Pending eligible Pods receive appropriate node bindings when capacity and constraints allow scheduling. This step belongs to Scheduler responsibility and binding rather than the complementary implementation and evidence pair. The intended approach is: Set workload requests for placement and limits for bounded runtime use based on measured application needs. Validate with: Inspect Pod requests/limits, node allocatable capacity, usage history, throttling and OOMKilled events. Workload context: An app exceeds its memory limit and restarts with OOMKilled while its CPU request remains satisfied.

Check API endpoint connectivity, request audit records, resource authorization and response status. This step belongs to Kubernetes API server and API requests rather than the complementary implementation and evidence pair. The intended approach is: Set workload requests for placement and limits for bounded runtime use based on measured application needs. Validate with: Inspect Pod requests/limits, node allocatable capacity, usage history, throttling and OOMKilled events. Workload context: An app exceeds its memory limit and restarts with OOMKilled while its CPU request remains satisfied.

Assign a Role to namespaced permissions and a ClusterRole where appropriate for cluster-scoped or reusable rules, binding least privilege. This step belongs to Role and ClusterRole authorization rather than the complementary implementation and evidence pair. The intended approach is: Set workload requests for placement and limits for bounded runtime use based on measured application needs. Validate with: Inspect Pod requests/limits, node allocatable capacity, usage history, throttling and OOMKilled events. Workload context: An app exceeds its memory limit and restarts with OOMKilled while its CPU request remains satisfied.

Check Service selectors and EndpointSlices to distinguish backend discovery from kube-proxy or data-plane forwarding faults. This action addresses Service endpoint routing and kube-proxy instead of the controlling requirement. Service routing depends on endpoints and the cluster's Service dataplane; some clusters replace kube-proxy with an alternate implementation. For this scenario prefer: Apply supported Kubernetes NetworkPolicies to restrict traffic using Pod/namespace selectors and explicit ingress/egress rules. Workload context: A security engineer assumes a policy that selects server Pods also blocks outgoing traffic, although only ingress policyTypes are configured.

Require approved registry artifacts and verifiable signatures or digests before admitting production workloads. This action addresses Image provenance and admission policies instead of the controlling requirement. An image scanner alone does not prove publisher identity; signed provenance and admission enforcement address different guarantees. For this scenario prefer: Apply supported Kubernetes NetworkPolicies to restrict traffic using Pod/namespace selectors and explicit ingress/egress rules. Workload context: A security engineer assumes a policy that selects server Pods also blocks outgoing traffic, although only ingress policyTypes are configured.

Use CoreDNS or the configured cluster DNS service to resolve Service and Pod naming in their correct namespaces. This action addresses Cluster DNS and service discovery instead of the controlling requirement. Kubernetes DNS uses namespace-aware search paths; a fully qualified Service name avoids ambiguity across namespaces. For this scenario prefer: Apply supported Kubernetes NetworkPolicies to restrict traffic using Pod/namespace selectors and explicit ingress/egress rules. Workload context: A security engineer assumes a policy that selects server Pods also blocks outgoing traffic, although only ingress policyTypes are configured.

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.

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.

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.