kubernetes-patterns

name	kubernetes-patterns
description	Kubernetes workload patterns, resource management, RBAC, probes, autoscaling, ConfigMap/Secret handling, and kubectl debugging for production-grade deployments. Use when writing or reviewing Kubernetes manifests, or debugging probes, RBAC, autoscaling, or resource limits.
metadata	{"origin":"ECC"}

Kubernetes Patterns

Production-grade Kubernetes patterns for deploying, managing, and debugging workloads reliably.

When to Activate

• Writing Kubernetes manifests (Deployments, Services, Ingress, Jobs)
• Configuring resource requests/limits, liveness/readiness probes
• Setting up RBAC, namespaces, or ServiceAccounts
• Managing configuration and secrets in K8s
• Debugging CrashLoopBackOff, OOMKilled, pending pods, or image pull errors
• Configuring HPA (Horizontal Pod Autoscaler) or PodDisruptionBudgets
• Reviewing K8s YAML for security or correctness

When to Use

Same as When to Activate above. This alias satisfies repo skill-format conventions. Use this skill any time you are writing, reviewing, or debugging Kubernetes YAML and workloads.

How It Works

This skill provides copy-pasteable, production-grade YAML patterns and kubectl debugging commands organized by task:

1. Deployment template — A fully configured production Deployment with security context, rolling update strategy, all three probe types, resource limits, and environment injection from ConfigMap/Secret.
2. Probes — Decision table for startup vs liveness vs readiness, with correct failureThreshold × periodSeconds math.
3. Services & Ingress — ClusterIP, LoadBalancer, and TLS Ingress patterns with cert-manager annotations.
4. ConfigMaps & Secrets — envFrom, file-mount, and external secrets guidance.
5. Resource management — Requests vs limits rules of thumb by workload type (web API, JVM, worker, sidecar).
6. RBAC — Least-privilege ServiceAccount → Role → RoleBinding chain.
7. HPA & PDB — Autoscaling and node-drain safety configurations.
8. Jobs & CronJobs — One-off and scheduled workload patterns with correct restartPolicy.
9. kubectl cheatsheet — Logs, exec, rollback, port-forward, dry-run, and common error diagnosis commands.
10. Anti-patterns & checklist — What NOT to do, and a security/reliability/observability checklist.

Examples

See the sections below for complete, runnable examples. Quick references:

Task	Jump to
Full production Deployment YAML	Core Workload Patterns
Probe configuration	Probes
RBAC least-privilege setup	RBAC
Debug a CrashLoopBackOff	kubectl Debugging Cheatsheet
Autoscaling	HPA

---

Core Workload Patterns

Deployment — Production Template

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-app
  namespace: my-namespace
  labels:
    app: my-app
    version: "1.0.0"
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-app
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1          # Allow 1 extra pod during update
      maxUnavailable: 0    # Never reduce below desired count
  template:
    metadata:
      labels:
        app: my-app
        version: "1.0.0"
    spec:
      # Security context at pod level
      securityContext:
        runAsNonRoot: true
        runAsUser: 1001
        fsGroup: 1001

      # Graceful shutdown
      terminationGracePeriodSeconds: 30

      containers:
        - name: my-app
          image: ghcr.io/org/my-app:1.0.0   # Never use :latest
          imagePullPolicy: IfNotPresent

          ports:
            - containerPort: 8080
              protocol: TCP

          # Resource requests AND limits are both required
          resources:
            requests:
              cpu: "100m"
              memory: "128Mi"
            limits:
              cpu: "500m"
              memory: "256Mi"

          # Container security context
          securityContext:
            allowPrivilegeEscalation: false
            readOnlyRootFilesystem: true
            capabilities:
              drop:
                - ALL

          # Probes (see Probes section below)
          startupProbe:
            httpGet:
              path: /health
              port: 8080
            failureThreshold: 30
            periodSeconds: 5
          livenessProbe:
            httpGet:
              path: /health
              port: 8080
            initialDelaySeconds: 0
            periodSeconds: 30
            failureThreshold: 3
          readinessProbe:
            httpGet:
              path: /ready
              port: 8080
            initialDelaySeconds: 5
            periodSeconds: 10
            failureThreshold: 2

          # Environment from ConfigMap and Secret
          envFrom:
            - configMapRef:
                name: my-app-config
          env:
            - name: DB_PASSWORD
              valueFrom:
                secretKeyRef:
                  name: my-app-secrets
                  key: db-password

          # Writable tmp directory when readOnlyRootFilesystem: true
          volumeMounts:
            - name: tmp
              mountPath: /tmp

      volumes:
        - name: tmp
          emptyDir: {}

---

Probes — Liveness, Readiness, Startup

Understanding when to use each probe is critical:

Probe	Failure Action	Use For
startupProbe	Kills container if slow to start	Slow-starting apps (JVM, Python)
livenessProbe	Restarts container	Deadlock / hung process detection
readinessProbe	Removes from Service endpoints	Temporary unavailability (DB reconnect)

# Correct pattern: startupProbe covers slow startup,
# then liveness/readiness take over
startupProbe:
  httpGet:
    path: /health
    port: 8080
  failureThreshold: 30  # 30 * 5s = 150s max startup time
  periodSeconds: 5

livenessProbe:
  httpGet:
    path: /health
    port: 8080
  periodSeconds: 30
  failureThreshold: 3   # 3 * 30s = 90s before restart

readinessProbe:
  httpGet:
    path: /ready         # Separate endpoint: checks DB, cache, etc.
    port: 8080
  periodSeconds: 10
  failureThreshold: 2

# WRONG: initialDelaySeconds without startupProbe
# If the app takes 60s to start, set a startupProbe instead
livenessProbe:
  httpGet:
    path: /health
    port: 8080
  initialDelaySeconds: 60   # BAD: Arbitrary wait, race condition

---

Services and Ingress

Service Types

# ClusterIP (default) — internal-only
apiVersion: v1
kind: Service
metadata:
  name: my-app
  namespace: my-namespace
spec:
  selector:
    app: my-app
  ports:
    - port: 80
      targetPort: 8080
      protocol: TCP
  type: ClusterIP

# LoadBalancer — external traffic (cloud providers)
spec:
  type: LoadBalancer
  ports:
    - port: 443
      targetPort: 8080

Ingress with TLS

apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: my-app
  namespace: my-namespace
  annotations:
    nginx.ingress.kubernetes.io/ssl-redirect: "true"
    cert-manager.io/cluster-issuer: "letsencrypt-prod"
spec:
  ingressClassName: nginx
  tls:
    - hosts:
        - myapp.example.com
      secretName: my-app-tls
  rules:
    - host: myapp.example.com
      http:
        paths:
          - path: /
            pathType: Prefix
            backend:
              service:
                name: my-app
                port:
                  number: 80

---

ConfigMaps and Secrets

ConfigMap — Non-sensitive configuration

apiVersion: v1
kind: ConfigMap
metadata:
  name: my-app-config
  namespace: my-namespace
data:
  LOG_LEVEL: "info"
  APP_ENV: "production"
  MAX_CONNECTIONS: "100"
  # Mount as a file for complex config
  app.yaml: |
    server:
      port: 8080
      timeout: 30s

# Mount ConfigMap as a file
volumes:
  - name: config
    configMap:
      name: my-app-config
      items:
        - key: app.yaml
          path: app.yaml
volumeMounts:
  - name: config
    mountPath: /etc/app
    readOnly: true

Secrets — Sensitive data

# Create secret from literal (CLI, then store in Vault/SOPS)
kubectl create secret generic my-app-secrets \
  --from-literal=db-password='s3cr3t' \
  --namespace=my-namespace \
  --dry-run=client -o yaml | kubectl apply -f -

apiVersion: v1
kind: Secret
metadata:
  name: my-app-secrets
  namespace: my-namespace
type: Opaque
# Values are base64-encoded (NOT encrypted — use Sealed Secrets or ESO for real encryption)
data:
  db-password: czNjcjN0  # base64 of 's3cr3t'

Important: Raw Kubernetes Secrets are only base64-encoded, not encrypted at rest unless your cluster has encryption configured. Use Sealed Secrets or External Secrets Operator for production.

---

Resource Requests and Limits

resources:
  requests:       # Scheduler uses this to place the pod
    cpu: "100m"   # 100 millicores = 0.1 CPU
    memory: "128Mi"
  limits:         # Container is killed/throttled above this
    cpu: "500m"
    memory: "256Mi"

Rules of thumb:

Workload Type	CPU Request	Memory Request	Notes
Web API	100–250m	128–256Mi	Set limits 2-4x requests
Worker/consumer	250–500m	256–512Mi	Memory limit = request for predictability
JVM app	500m–1	512Mi–2Gi	Allow headroom above -Xmx for JVM overhead
Sidecar	10–50m	32–64Mi	Keep minimal

# WRONG: No requests or limits — unpredictable scheduling, OOM evictions
containers:
  - name: app
    image: myapp:latest
    # Missing resources: {} — this is dangerous in production

# WRONG: Limits without requests — requests default to limits, over-reserves capacity
resources:
  limits:
    cpu: "2"
    memory: "1Gi"
  # requests missing — will default to limits values

---

RBAC — Roles and ServiceAccounts

Principle of Least Privilege

Two patterns depending on whether the app calls the Kubernetes API:

Pattern A — App does NOT need the Kubernetes API (most apps)

Disable token automounting on the ServiceAccount. The Role/RoleBinding are not needed.

# ServiceAccount with token disabled — safest default
apiVersion: v1
kind: ServiceAccount
metadata:
  name: my-app-sa
  namespace: my-namespace
automountServiceAccountToken: false   # No K8s API token injected into pods

# Reference in Deployment — no token, no API access
spec:
  template:
    spec:
      serviceAccountName: my-app-sa
      automountServiceAccountToken: false   # Belt-and-suspenders: also set at pod level

Pattern B — App DOES need the Kubernetes API (operators, controllers, config watchers)

Enable the token and grant only the permissions actually required.

# 1. ServiceAccount — enable token for this SA
apiVersion: v1
kind: ServiceAccount
metadata:
  name: my-app-sa
  namespace: my-namespace
automountServiceAccountToken: true    # Token required: app calls K8s API

# 2. Role — grant only what the app needs (namespace-scoped)
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
  name: my-app-role
  namespace: my-namespace
rules:
  - apiGroups: [""]
    resources: ["configmaps"]
    verbs: ["get", "list", "watch"]    # Read-only, specific resource
  - apiGroups: [""]
    resources: ["secrets"]
    resourceNames: ["my-app-secrets"]  # Restrict to specific secret by name
    verbs: ["get"]

# 3. Bind Role to ServiceAccount
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: my-app-rolebinding
  namespace: my-namespace
subjects:
  - kind: ServiceAccount
    name: my-app-sa
    namespace: my-namespace
roleRef:
  kind: Role
  apiGroup: rbac.authorization.k8s.io
  name: my-app-role

# 4. Reference SA in Deployment
spec:
  template:
    spec:
      serviceAccountName: my-app-sa
      # automountServiceAccountToken defaults to true from SA — token is injected

---

Horizontal Pod Autoscaler (HPA)

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: my-app-hpa
  namespace: my-namespace
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: my-app
  minReplicas: 2      # Always at least 2 for HA
  maxReplicas: 10
  metrics:
    - type: Resource
      resource:
        name: cpu
        target:
          type: Utilization
          averageUtilization: 70    # Scale up when avg CPU > 70%
    - type: Resource
      resource:
        name: memory
        target:
          type: Utilization
          averageUtilization: 80

HPA requires resources.requests to be set on all containers — it calculates utilization as current / request.

---

PodDisruptionBudget (PDB)

Prevent too many pods going down during node drains or rolling updates:

apiVersion: policy/v1
kind: PodDisruptionBudget
metadata:
  name: my-app-pdb
  namespace: my-namespace
spec:
  minAvailable: 2           # OR use maxUnavailable: 1
  selector:
    matchLabels:
      app: my-app

---

Namespaces and Multi-Tenancy

# Create namespace with resource quotas
kubectl create namespace my-namespace

# Apply ResourceQuota to limit namespace consumption
kubectl apply -f - <<EOF
apiVersion: v1
kind: ResourceQuota
metadata:
  name: my-namespace-quota
  namespace: my-namespace
spec:
  hard:
    requests.cpu: "4"
    requests.memory: 4Gi
    limits.cpu: "8"
    limits.memory: 8Gi
    pods: "20"
EOF

---

Jobs and CronJobs

# One-off Job (DB migration, data processing)
apiVersion: batch/v1
kind: Job
metadata:
  name: db-migrate
  namespace: my-namespace
spec:
  backoffLimit: 3          # Retry up to 3 times on failure
  ttlSecondsAfterFinished: 3600   # Auto-delete after 1h
  template:
    spec:
      restartPolicy: OnFailure    # Never for Jobs (not Always)
      containers:
        - name: migrate
          image: ghcr.io/org/my-app:1.0.0
          command: ["python", "manage.py", "migrate"]
          resources:
            requests:
              cpu: "100m"
              memory: "256Mi"

# CronJob
apiVersion: batch/v1
kind: CronJob
metadata:
  name: cleanup-job
  namespace: my-namespace
spec:
  schedule: "0 2 * * *"         # 2am daily
  concurrencyPolicy: Forbid      # Don't run if previous still running
  successfulJobsHistoryLimit: 3
  failedJobsHistoryLimit: 1
  jobTemplate:
    spec:
      template:
        spec:
          restartPolicy: OnFailure
          containers:
            - name: cleanup
              image: ghcr.io/org/cleanup:1.0.0
              resources: