agentleFS
salmandevsalmandev/everything-gemini/skills/kubernetes-operator/SKILL.md

kubernetes-operator

Skill2 starsChanged 29 days agoApache-2.0View on GitHub

Use this skill when authoring Kubernetes manifests, configuring Helm charts, setting up Horizontal Pod Autoscalers (HPA), or troubleshooting container cluster deployments.

5 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 5 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Always configure resource limits, security contexts, and liveness/readiness probes:

    line 15

“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Kubernetes Cluster & Workload Operations

Overview

This skill guides the agent in writing declarative, production-ready Kubernetes manifests, configuring health probes, resource constraints, ingress controllers, and rolling update strategies.

Procedural Workflow

1. Hardened Deployment Manifest Pattern

Always configure resource limits, security contexts, and liveness/readiness probes:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: api-service
  labels:
    app.kubernetes.io/name: api-service
spec:
  replicas: 3
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
  selector:
    matchLabels:
      app: api-service
  template:
    metadata:
      labels:
        app: api-service
    spec:
      securityContext:
        runAsNonRoot: true
        runAsUser: 10001
      containers:
        - name: app
          image: myregistry.azurecr.io/api-service:v1.0.0
          securityContext:
            readOnlyRootFilesystem: true
            allowPrivilegeEscalation: false
          resources:
            requests:
              cpu: "100m"
              memory: "128Mi"
            limits:
              cpu: "500m"
              memory: "512Mi"
          ports:
            - containerPort: 8080
          readinessProbe:
            httpGet:
              path: /health/ready
              port: 8080
            initialDelaySeconds: 5
            periodSeconds: 10
          livenessProbe:
            httpGet:
              path: /health/live
              port: 8080
            initialDelaySeconds: 15
            periodSeconds: 20

2. Auto-scaling & Ingress

  • HorizontalPodAutoscaler (HPA): Target CPU (e.g. 70%) and Memory utilization before traffic spikes.
  • Ingress with TLS: Annotate with cert-manager (cert-manager.io/cluster-issuer: letsencrypt-prod) for automated SSL lifecycle.

3. Triage & Debugging Commands

  • Inspect crash loops: kubectl logs -l app=api-service --tail=100 -p (previous container logs).
  • Inspect pod events: kubectl describe pod <pod-name>.

Verification Checklist

  • Non-root security context configured (runAsNonRoot: true)
  • Both readiness and liveness probes defined
  • Memory limits defined to prevent cluster OOM killer cascades
  • Rolling update configured with zero downtime (maxUnavailable: 0)

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.