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SKILL verified MIT Self-run

Kubernetes Expert

skill-miaoge-ge-coding-agent-skills-kubernetes-expert · by Miaoge-Ge

Expert Kubernetes: workloads, services, config, probes, resources, and troubleshooting. Trigger keywords: Kubernetes, k8s, Deployment, StatefulSet, Service, Pod, ConfigMap, Secret, Ingress, liveness, readiness, probe, requests, limits, HPA, kubectl, Helm, CrashLoopBackOff, ImagePullBackOff, OOMKilled. Use for writing manifests, configuring workloads, or debugging cluster issues.

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Install

$ agentstack add skill-miaoge-ge-coding-agent-skills-kubernetes-expert

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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3mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
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About

Kubernetes Expert

> Declarative, resilient, right-sized. Set resource requests/limits and correct probes, keep config out of images, and when debugging read the events first — they almost always name the cause.

When to Use

  • Writing/reviewing manifests (Deployments, StatefulSets, Services, Ingress, Config/Secrets).
  • Probes, resource requests/limits, autoscaling (HPA), rollouts.
  • Debugging CrashLoopBackOff, ImagePullBackOff, OOMKilled, Pending, or networking.
  • Templating with Helm/Kustomize.

When NOT to Use

  • Building the container image → docker-expert.
  • App-level bugs inside the container → relevant language skill.
  • CI/CD pipeline wiring → github-master.

Core Principles

1. Pick the right workload

  • Deployment for stateless apps, StatefulSet for stable identity/storage, DaemonSet for per-node, Job/CronJob for batch. Don't run databases as a plain Deployment.

2. Resources & scheduling

  • Always set requests and limits. Requests drive scheduling and guarantees; limits cap usage. Missing requests → noisy-neighbor evictions and unschedulable surprises.
  • Memory limit too low → OOMKilled. CPU limit throttles (doesn't kill). Size from real usage; set requests == limits for guaranteed/latency-sensitive pods.

3. Health & rollouts

  • Readiness gates traffic (don't route until ready); liveness restarts a hung process; startup probe protects slow boots. A too-aggressive liveness probe causes restart loops — tune initialDelay/failureThreshold.
  • RollingUpdate with sensible maxSurge/maxUnavailable; add PodDisruptionBudget for availability during drains. Pin image tags/digests, never :latest.

4. Config, secrets, security

  • Config in ConfigMap, secrets in Secret (+ a real secrets manager / sealed-secrets for prod). Never bake them into images. Roll pods on config change (checksum annotation).
  • Drop root, set securityContext (runAsNonRoot, read-only root FS), apply NetworkPolicy (default deny), and least-privilege RBAC.

5. Troubleshoot methodically

  • kubectl get podsdescribe pod (read Events) → logs (+ --previous for crashed) → get events --sort-by=.lastTimestamp. CrashLoop → check logs+probes; ImagePull → check tag/registry/secret; Pending → check resources/taints; OOMKilled → raise memory or fix the leak.

Common Mistakes

  • No resource requests/limits → eviction, OOM, throttling, scheduling failures.
  • Liveness probe doing heavy/slow checks → restart loops; use a cheap readiness check for traffic.
  • :latest images → unpredictable rollouts, no rollback.
  • Secrets in ConfigMaps or images → exposure.
  • Editing live objects with kubectl edit instead of updating manifests → config drift; stay declarative/GitOps.
  • One giant pod / multiple concerns per container → scale and fail independently instead.

Examples

Deployment with probes, resources, and security context

apiVersion: apps/v1
kind: Deployment
metadata: { name: web }
spec:
  replicas: 3
  selector: { matchLabels: { app: web } }
  template:
    metadata: { labels: { app: web } }
    spec:
      securityContext: { runAsNonRoot: true }
      containers:
        - name: web
          image: registry.example.com/web@sha256:…   # pinned by digest
          ports: [ { containerPort: 3000 } ]
          resources:
            requests: { cpu: "100m", memory: "128Mi" }
            limits:   { cpu: "500m", memory: "256Mi" }
          readinessProbe: { httpGet: { path: /health, port: 3000 }, initialDelaySeconds: 5 }
          livenessProbe:  { httpGet: { path: /health, port: 3000 }, periodSeconds: 10, failureThreshold: 6 }
          securityContext: { allowPrivilegeEscalation: false, readOnlyRootFilesystem: true }

See Also

  • docker-expert — the images these workloads run.
  • security-expert — RBAC, NetworkPolicy, and secret handling.
  • performance-expert — right-sizing resources and HPA tuning.
  • github-master — CD pipelines that apply manifests.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.