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Get Started Free →Kubernetes operations including manifests, Helm charts, operators, troubleshooting, and resource management
.claude/skills/bilal140202-kubernetes-operations/SKILL.md| Model | Eval pass | Runs |
|---|---|---|
| gemini-3.6-flash | 100% | 2 |
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-05 | ✗→✓ | ▲ Improved | 106% | 0% |
| case-01 | ✗→✓ | ▲ Improved | -6% | 0% |
| case-02 | ✗→✓ | ▲ Improved | 29% | 0% |
| case-03 | ✗→✓ | ▲ Improved | 16% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 49% | 0% |
yamlapiVersion: apps/v1 kind: Deployment metadata: name: api-server labels: app: api-server version: v1 spec: replicas: 3 strategy: type: RollingUpdate rollingUpdate: maxSurge: 1 maxUnavailable: 0 selector: matchLabels: app: api-server template: metadata: labels: app: api-server version: v1 spec: containers: - name: api image: registry.example.com/api:1.2.0 ports: - containerPort: 8080 resources: requests: cpu: 100m memory: 128Mi limits: cpu: 500m memory: 512Mi livenessProbe: httpGet: path: /healthz port: 8080 initialDelaySeconds: 10 periodSeconds: 15 readinessProbe: httpGet: path: /ready port: 8080 initialDelaySeconds: 5 periodSeconds: 5 env: - name: DATABASE_URL valueFrom: secretKeyRef: name: db-credentials key: url topologySpreadConstraints: - maxSkew: 1 topologyKey: kubernetes.io/hostname whenUnsatisfiable: DoNotSchedule labelSelector: matchLabels: app: api-server
Always set resource requests and limits. Use topology spread constraints for high availability.
chart/
Chart.yaml
values.yaml
values-staging.yaml
values-production.yaml
templates/
deployment.yaml
service.yaml
ingress.yaml
hpa.yaml
_helpers.tplyaml# values.yaml replicaCount: 2 image: repository: registry.example.com/api tag: "1.2.0" pullPolicy: IfNotPresent resources: requests: cpu: 100m memory: 128Mi limits: cpu: 500m memory: 512Mi autoscaling: enabled: true minReplicas: 2 maxReplicas: 10 targetCPUUtilization: 70
yamlapiVersion: autoscaling/v2 kind: HorizontalPodAutoscaler metadata: name: api-server spec: scaleTargetRef: apiVersion: apps/v1 kind: Deployment name: api-server minReplicas: 2 maxReplicas: 10 metrics: - type: Resource resource: name: cpu target: type: Utilization averageUtilization: 70 - type: Resource resource: name: memory target: type: Utilization averageUtilization: 80 behavior: scaleDown: stabilizationWindowSeconds: 300
bash# Pod diagnostics kubectl describe pod <pod-name> -n <namespace> kubectl logs <pod-name> -c <container> --previous kubectl exec -it <pod-name> -- /bin/sh # Resource usage kubectl top pods -n <namespace> --sort-by=memory kubectl top nodes # Network debugging kubectl run debug --image=nicolaka/netshoot --rm -it -- bash nslookup <service-name>.<namespace>.svc.cluster.local # Events sorted by time kubectl get events -n <namespace> --sort-by='.lastTimestamp' # Find pods not running kubectl get pods -A --field-selector=status.phase!=Running
securityContext.runAsNonRoot: truelatest tag instead of pinned image versionsPodDisruptionBudget for critical workloadslatest| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-10 | pass→pass | 3,296 | 1,527 | -54% | 1 | 1 | 0% | 485 | 1,333 | +175% | 0 | 0 | — |
case-05 | fail→pass | 4,571 | 4,303 | -6% | 1 | 1 | 0% | 933 | 1,925 | +106% | 0 | 0 | — |
case-01 | fail→pass | 15,286 | 9,266 | -39% | 1 | 1 | 0% | 3,306 | 3,112 | -6% | 0 | 0 | — |
case-02 | fail→pass | 9,596 | 5,658 | -41% | 1 | 1 | 0% | 1,627 | 2,095 | +29% | 0 | 0 | — |
case-03 | fail→pass | 12,138 | 7,465 | -38% | 1 | 1 | 0% | 2,193 | 2,546 | +16% | 0 | 0 | — |
case-04 | fail→pass | 15,528 | 16,769 | +8% | 1 | 1 | 0% | 2,726 | 4,057 | +49% | 0 | 0 | — |
case-06 | fail→pass | 10,746 | 6,439 | -40% | 1 | 1 | 0% | 1,754 | 2,157 | +23% | 0 | 0 | — |
case-07 | fail→pass | 11,112 | 5,676 | -49% | 1 | 1 | 0% | 2,003 | 2,037 | +2% | 0 | 0 | — |
case-08 | pass→pass | 3,421 | 2,684 | -22% | 1 | 1 | 0% | 424 | 1,474 | +248% | 0 | 0 | — |
case-09 | fail→pass | 4,209 | 4,355 | +3% | 1 | 1 | 0% | 658 | 1,871 | +184% | 0 | 0 | — |
case-11 | pass→pass | 10,427 | 2,396 | -77% | 1 | 1 | 0% | 809 | 1,516 | +87% | 0 | 0 | — |
case-12 | pass→pass | 4,524 | 2,744 | -39% | 1 | 1 | 0% | 772 | 1,582 | +105% | 0 | 0 | — |
case-13 | pass→pass | 12,911 | 8,463 | -34% | 1 | 1 | 0% | 2,025 | 2,522 | +25% | 0 | 0 | — |
case-14 | fail→pass | 3,456 | 3,748 | +8% | 1 | 1 | 0% | 576 | 1,721 | +199% | 0 | 0 | — |
case-15 | pass→pass | 10,194 | 6,814 | -33% | 1 | 1 | 0% | 1,476 | 2,219 | +50% | 0 | 0 | — |
case-16 | pass→pass | 6,137 | 2,724 | -56% | 1 | 1 | 0% | 1,063 | 1,543 | +45% | 0 | 0 | — |
case-17 | pass→pass | 6,315 | 5,552 | -12% | 1 | 1 | 0% | 1,053 | 2,005 | +90% | 0 | 0 | — |
case-18 | pass→pass | 14,281 | 12,609 | -12% | 1 | 1 | 0% | 2,325 | 3,112 | +34% | 0 | 0 | — |
case-19 | pass→pass | 6,729 | 2,636 | -61% | 1 | 1 | 0% | 994 | 1,615 | +62% | 0 | 0 | — |
case-20 | pass→fail | 4,716 | 6,553 | +39% | 1 | 1 | 0% | 921 | 2,254 | +145% | 0 | 0 | — |
case-21 | pass→pass | 3,795 | 2,963 | -22% | 1 | 1 | 0% | 756 | 1,733 | +129% | 0 | 0 | — |
case-22 | pass→pass | 3,692 | 4,350 | +18% | 1 | 1 | 0% | 571 | 1,795 | +214% | 0 | 0 | — |
case-23 | pass→pass | 3,646 | 2,622 | -28% | 1 | 1 | 0% | 503 | 1,509 | +200% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +35 percentage points is the difference between those two pass rates over the 23 comparable cases. 1 case got worse with the skill loaded, and it is included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.