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deploy-to-kubernetes

pjt222
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Designaidata

About

This Claude Skill deploys applications to Kubernetes clusters using kubectl manifests and Helm charts for production-ready setups. It handles deployments, services, configs, and implements health checks, resource limits, and rolling updates. Use it for deploying to cloud or self-hosted K8s, migrating from Docker Compose, or setting up multi-environment deployments.

Quick Install

Claude Code

Recommended
Primary
npx skills add pjt222/agent-almanac -a claude-code
Plugin CommandAlternative
/plugin add https://github.com/pjt222/agent-almanac
Git CloneAlternative
git clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/deploy-to-kubernetes

Copy and paste this command in Claude Code to install this skill

Documentation

Deploy to Kubernetes

Containerized apps → K8s. Prod-ready: health checks, resource mgmt, auto rollouts.

Use When

  • New apps → K8s (EKS, GKE, AKS, self-hosted)
  • Compose/VMs → orchestration migrate
  • Zero-downtime rolling updates + rollbacks
  • Config + secrets mgmt
  • Multi-env (dev, staging, prod)
  • Reusable Helm charts

In

  • Required: Cluster access (kubectl cluster-info)
  • Required: Images in registry (Docker Hub, ECR, GCR, Harbor)
  • Required: App reqs (ports, env vars, volumes)
  • Optional: TLS certs → HTTPS ingress
  • Optional: Persistent storage (StatefulSets, PVCs)
  • Optional: Helm CLI

Do

See Extended Examples for complete configuration files and templates.

Step 1: Namespace + resource quotas

Orgs apps → namespaces w/ limits + RBAC.

# Create namespace
kubectl create namespace myapp-prod

# Apply resource quota
cat <<EOF | kubectl apply -f -
apiVersion: v1
kind: ResourceQuota
metadata:
  name: compute-quota
  namespace: myapp-prod
spec:
  hard:
    requests.cpu: "10"
    requests.memory: "20Gi"
    limits.cpu: "20"
    limits.memory: "40Gi"
    persistentvolumeclaims: "5"
    services.loadbalancers: "2"
---
apiVersion: v1
kind: LimitRange
metadata:
  name: default-limits
  namespace: myapp-prod
spec:
  limits:
  - default:
      cpu: "500m"
      memory: "512Mi"
    defaultRequest:
      cpu: "100m"
      memory: "128Mi"
    type: Container
EOF

# Create service account
cat <<EOF | kubectl apply -f -
apiVersion: v1
kind: ServiceAccount
metadata:
  name: myapp
  namespace: myapp-prod
---
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
  name: myapp-role
  namespace: myapp-prod
rules:
- apiGroups: [""]
  resources: ["configmaps", "secrets"]
  verbs: ["get", "list", "watch"]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: myapp-rolebinding
  namespace: myapp-prod
subjects:
- kind: ServiceAccount
  name: myapp
  namespace: myapp-prod
roleRef:
  kind: Role
  name: myapp-role
  apiGroup: rbac.authorization.k8s.io
EOF

# Verify namespace setup
kubectl get resourcequota -n myapp-prod
kubectl get limitrange -n myapp-prod
kubectl get sa -n myapp-prod

→ NS created w/ quotas. LimitRange sets defaults. SA least-priv RBAC.

If err: Quota → check nodes (kubectl describe nodes). RBAC → kubectl auth can-i create role --namespace myapp-prod. Rejected resources → kubectl describe.

Step 2: Secrets + ConfigMaps

Externalize config + sensitive data.

# Create ConfigMap from literal values
kubectl create configmap myapp-config \
  --namespace=myapp-prod \
  --from-literal=LOG_LEVEL=info \
  --from-literal=API_TIMEOUT=30s \
  --from-literal=FEATURE_FLAGS='{"newUI":true,"betaAPI":false}'

# Create ConfigMap from file
cat > app.properties <<EOF
database.pool.size=20
cache.ttl=3600
retry.attempts=3
EOF

kubectl create configmap myapp-properties \
  --namespace=myapp-prod \
  --from-file=app.properties

# Create Secret for database credentials
kubectl create secret generic myapp-db-secret \
  --namespace=myapp-prod \
  --from-literal=username=appuser \
  --from-literal=password='sup3rs3cr3t!' \
  --from-literal=connection-string='postgresql://db.example.com:5432/myapp'

# Create TLS secret for ingress
kubectl create secret tls myapp-tls \
  --namespace=myapp-prod \
  --cert=path/to/tls.crt \
  --key=path/to/tls.key

# Verify secrets/configmaps
kubectl get configmap -n myapp-prod
kubectl get secret -n myapp-prod
kubectl describe configmap myapp-config -n myapp-prod

Complex → YAML:

# configmap.yaml
apiVersion: v1
kind: ConfigMap
metadata:
  name: myapp-config
  namespace: myapp-prod
data:
  nginx.conf: |
    server {
      listen 8080;
      location / {
        proxy_pass http://backend:3000;
        proxy_set_header Host $host;
      }
    }
  app-config.json: |
    {
      "logLevel": "info",
      "features": {
        "authentication": true,
        "metrics": true
      }
    }
---
# secret.yaml
apiVersion: v1
kind: Secret
metadata:
  name: myapp-secret
  namespace: myapp-prod
type: Opaque
stringData:  # Automatically base64 encoded
  api-key: "sk-1234567890abcdef"
  jwt-secret: "my-jwt-signing-key"

→ ConfigMaps → non-sensitive. Secrets → creds/keys. Pods read via env/volume. TLS → Ingress.

If err: Encoding → use stringData not data. TLS → openssl x509 -in tls.crt -text -noout. Access → SA RBAC. Decode → kubectl get secret myapp-secret -o jsonpath='{.data.api-key}' | base64 -d.

Step 3: Deployment w/ health + limits

Prod-ready w/ probes + resource mgmt.

# deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp
  namespace: myapp-prod
  labels:
    app: myapp
    version: v1.0.0
spec:
  replicas: 3
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0  # Zero-downtime updates
  selector:
    matchLabels:
      app: myapp
  template:
    metadata:
      labels:
        app: myapp
        version: v1.0.0
      annotations:
        prometheus.io/scrape: "true"
        prometheus.io/port: "8080"
        prometheus.io/path: "/metrics"
    spec:
      serviceAccountName: myapp
      securityContext:
        runAsNonRoot: true
        runAsUser: 1000
        fsGroup: 1000
      containers:
      - name: myapp
        image: myregistry.io/myapp:v1.0.0
        imagePullPolicy: IfNotPresent
        ports:
        - name: http
          containerPort: 8080
          protocol: TCP
        env:
        - name: LOG_LEVEL
          valueFrom:
            configMapKeyRef:
              name: myapp-config
              key: LOG_LEVEL
        - name: DB_USERNAME
          valueFrom:
            secretKeyRef:
              name: myapp-db-secret
              key: username
        - name: DB_PASSWORD
          valueFrom:
            secretKeyRef:
              name: myapp-db-secret
              key: password
        - name: POD_NAME
          valueFrom:
            fieldRef:
              fieldPath: metadata.name
        - name: POD_NAMESPACE
          valueFrom:
            fieldRef:
              fieldPath: metadata.namespace
        resources:
          requests:
            cpu: 250m
            memory: 256Mi
          limits:
            cpu: 500m
            memory: 512Mi
        livenessProbe:
          httpGet:
            path: /healthz
            port: http
          initialDelaySeconds: 30
          periodSeconds: 10
          timeoutSeconds: 5
          failureThreshold: 3
        readinessProbe:
          httpGet:
            path: /ready
            port: http
          initialDelaySeconds: 5
          periodSeconds: 5
          timeoutSeconds: 3
          failureThreshold: 2
        startupProbe:
          httpGet:
            path: /healthz
            port: http
          initialDelaySeconds: 0
          periodSeconds: 10
          timeoutSeconds: 3
          failureThreshold: 30  # 5 minutes for slow startup
        volumeMounts:
        - name: config
          mountPath: /etc/myapp
          readOnly: true
        - name: cache
          mountPath: /var/cache/myapp
      volumes:
      - name: config
        configMap:
          name: myapp-properties
      - name: cache
        emptyDir: {}
      imagePullSecrets:
      - name: registry-credentials

Apply + monitor:

# Apply deployment
kubectl apply -f deployment.yaml

# Watch rollout status
kubectl rollout status deployment/myapp -n myapp-prod

# Check pod status
kubectl get pods -n myapp-prod -l app=myapp

# View pod logs
kubectl logs -n myapp-prod -l app=myapp --tail=50 -f

# Describe deployment for events
kubectl describe deployment myapp -n myapp-prod

# Check resource usage
kubectl top pods -n myapp-prod -l app=myapp

→ 3 replicas rolling. Readiness pre-traffic. Liveness restarts unhealthy. Limits prevent OOM. Logs show startup.

If err: ImagePullBackOff → image + imagePullSecret (kubectl get secret registry-credentials -o yaml). CrashLoopBackOff → kubectl logs pod-name --previous. Probe fail → port-forward + curl. OOMKilled → increase mem or find leaks.

Step 4: Expose via Service + LB

# service.yaml
apiVersion: v1
kind: Service
metadata:
  name: myapp
  namespace: myapp-prod
# ... (see EXAMPLES.md for complete configuration)

Apply + test:

# Apply services
kubectl apply -f service.yaml

# Get service details
kubectl get svc -n myapp-prod

# ... (see EXAMPLES.md for complete configuration)

→ LB → external IP. ClusterIP → stable internal DNS. Endpoints = healthy pod IPs. Curl OK.

If err: LB pending → cloud integration + quotas. No endpoints → kubectl get pods --show-labels matches selector. Refused → targetPort matches container. Debug → kubectl port-forward bypass.

Step 5: HPA

Auto scale on CPU/mem/custom.

# hpa.yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: myapp-hpa
  namespace: myapp-prod
# ... (see EXAMPLES.md for complete configuration)

Install metrics-server:

# Install metrics-server
kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml

# Verify metrics-server
kubectl get deployment metrics-server -n kube-system
kubectl top nodes
# ... (see EXAMPLES.md for complete configuration)

→ HPA monitors. Scale up on threshold, down gradual. Metrics via kubectl top.

If err: "unknown" metrics → metrics-server running + pod requests defined. No scale → kubectl top pods vs target. Flapping → stabilizationWindowSeconds. Slow → reduce periodSeconds.

Step 6: Helm chart

Reusable, multi-env.

# Create Helm chart structure
helm create myapp-chart
cd myapp-chart

# Edit Chart.yaml
cat > Chart.yaml <<EOF
# ... (see EXAMPLES.md for complete configuration)

→ Chart packages all resources. Dry-run renders. Install orders. Upgrades roll. Rollback reverts.

If err: Template → helm template . local render. Dep → helm dependency update. Values → path in values.yaml. Inspect → helm get manifest myapp -n myapp-prod.

Check

  • Pods Running + all ready
  • Readiness pre-endpoints
  • Liveness restarts unhealthy
  • Reqs/limits prevent OOM + overcommit
  • Secrets/ConfigMaps mounted
  • Svcs DNS resolve (cluster.local)
  • LB/Ingress external
  • HPA scales up/down
  • Rolling zero-downtime
  • Logs → kubectl or centralized

Traps

  • No readiness: Traffic before ready. Always readiness probes verify deps.
  • Insufficient startup: Fast liveness kills slow apps. Use startupProbe w/ high failureThreshold.
  • No resource limits: Unlimited CPU/mem → node instability. Always set reqs + limits.
  • Hardcoded config: Env-specific in manifests → no reuse. ConfigMaps, Secrets, Helm values.
  • Default SA: Unnecessary perms. Dedicated SA + minimal RBAC.
  • No rolling strategy: Recreate all → downtime. RollingUpdate + maxUnavailable: 0.
  • Secrets in VCS: Sensitive → Git. Sealed-secrets, external-secrets-operator, or vault.
  • No PDB: Cluster maint drains → break. PodDisruptionBudget → min available.

  • setup-docker-compose — container fundamentals pre-K8s
  • containerize-mcp-server — images for deploy
  • write-helm-chart — advanced Helm
  • manage-kubernetes-secrets — SealedSecrets + external-secrets-operator
  • configure-ingress-networking — NGINX Ingress + cert-manager
  • implement-gitops-workflow — ArgoCD/Flux declarative
  • setup-container-registry — registry integration

GitHub Repository

pjt222/agent-almanac
Path: i18n/caveman-ultra/skills/deploy-to-kubernetes
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