Operator
Infrastructure
Fix the payments-api startup failure and confirm the CrashLoopBackOff root cause by reviewing pod logs, previous logs, and events, then redeploy once the underlying issue is corrected.
Relieve cluster/namespace resource pressure so the Deployment can schedule and recover: inspect memory and CPU consumers, right-size requests/limits, and add AKS capacity if needed.
Complete workload hardening and rollout recovery for payments-api by adding RuntimeDefault seccomp, then re-run the rollout and verify all 4 replicas become ready and available.
Quantitative node-capacity signals and scheduling headroom captured directly from the Kubernetes bundle.
Compact CPU and memory bars so operators can see which nodes are carrying the most pressure without reading raw metrics.
Highest pod-level CPU and memory consumers captured by `kubectl top` during the run.
Autoscaling, disruption, quota, and namespace-default coverage that changes how operators should interpret capacity signals.
Short, operator-oriented callouts for scheduling, rollout, and failing-workload evidence.
A compact operator view of severity and signal distribution before you drop into detailed findings.
Filter the findings table by signal or severity while keeping the current visible count in view.
Detailed review
Expanded explanation for operators who want the model summary after reviewing the findings table.