# Kubernetes Patterns > Kubernetes deployment patterns, resource management, networking, security, and production best practices. Use when deploying containerized applications to Kubernetes, managing clusters, configuring ingress, or implementing scaling strategies. Use when this capability is needed. - Skill: `tomevault-io/kubernetes-patterns-2` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add tomevault-io/kubernetes-patterns-2` - Raw SKILL.md: https://api.skillmd.com/api/skills/tomevault-io/kubernetes-patterns-2/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: DevOps & Infra - Author: tomevault-io (https://skillmd.com/u/tomevault-io) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/tomevault-io/kubernetes-patterns-2 --- # Kubernetes Patterns Skill ## Overview This skill provides comprehensive Kubernetes deployment patterns for production workloads including resource management, networking configuration, security hardening, auto-scaling, and multi-environment setups. ## Quick Start ### Basic Deployment ```yaml apiVersion: apps/v1 kind: Deployment metadata: name: myapp spec: replicas: 3 selector: matchLabels: app: myapp template: metadata: labels: app: myapp spec: containers: - name: myapp image: myregistry/myapp:latest ports: - containerPort: 8080 resources: requests: memory: "256Mi" cpu: "250m" limits: memory: "512Mi" cpu: "500m" ``` ### Service Exposure ```yaml apiVersion: v1 kind: Service metadata: name: myapp spec: selector: app: myapp ports: - port: 80 targetPort: 8080 type: ClusterIP ``` ### Ingress Configuration ```yaml apiVersion: networking.k8s.io/v1 kind: Ingress metadata: name: myapp annotations: nginx.ingress.kubernetes.io/ssl-redirect: "true" spec: ingressClassName: nginx tls: - hosts: - myapp.example.com secretName: myapp-tls rules: - host: myapp.example.com http: paths: - path: / pathType: Prefix backend: service: name: myapp port: number: 80 ``` ## Core Concepts ### 1. Resource Management - **Requests**: Guaranteed resources for scheduling - **Limits**: Maximum resources allowed - **Quality of Service**: Guaranteed, Burstable, BestEffort ### 2. Pod Lifecycle - **Pending**: Scheduling/initialization - **Running**: All containers running - **Succeeded**: Completed successfully - **Failed**: Terminated with error - **Unknown**: State cannot be determined ### 3. Service Types - **ClusterIP**: Internal cluster access only - **NodePort**: Exposes port on each node - **LoadBalancer**: Cloud provider load balancer - **ExternalName**: Maps to external DNS ## Production Patterns ### Health Checks ```yaml livenessProbe: httpGet: path: /health port: 8080 initialDelaySeconds: 30 periodSeconds: 10 timeoutSeconds: 5 failureThreshold: 3 readinessProbe: httpGet: path: /ready port: 8080 initialDelaySeconds: 5 periodSeconds: 5 ``` ### Graceful Shutdown ```yaml lifecycle: preStop: exec: command: ["/bin/sh", "-c", "sleep 15"] t terminationGracePeriodSeconds: 60 ``` ### Security Context ```yaml securityContext: runAsNonRoot: true runAsUser: 1000 runAsGroup: 1000 fsGroup: 1000 readOnlyRootFilesystem: true allowPrivilegeEscalation: false seccompProfile: type: RuntimeDefault capabilities: drop: - ALL add: - NET_BIND_SERVICE ``` ## Scaling Strategies ### Horizontal Pod Autoscaler ```yaml apiVersion: autoscaling/v2 kind: HorizontalPodAutoscaler metadata: name: myapp spec: scaleTargetRef: apiVersion: apps/v1 kind: Deployment name: myapp minReplicas: 3 maxReplicas: 20 metrics: - type: Resource resource: name: cpu target: type: Utilization averageUtilization: 70 - type: Resource resource: name: memory target: type: Utilization averageUtilization: 80 behavior: scaleUp: stabilizationWindowSeconds: 60 policies: - type: Percent value: 100 periodSeconds: 15 scaleDown: stabilizationWindowSeconds: 300 policies: - type: Percent value: 10 periodSeconds: 60 ``` ### Vertical Pod Autoscaler ```yaml apiVersion: autoscaling.k8s.io/v1 kind: VerticalPodAutoscaler metadata: name: myapp spec: targetRef: apiVersion: apps/v1 kind: Deployment name: myapp updatePolicy: updateMode: "Auto" resourcePolicy: containerPolicies: - containerName: myapp minAllowed: cpu: 50m memory: 100Mi maxAllowed: cpu: 1000m memory: 1Gi controlledResources: ["cpu", "memory"] ``` ## Detailed References See comprehensive guides in references/: - **[Deployment Patterns](references/deployment-patterns.md)** - Deployments, StatefulSets, DaemonSets, Jobs - **[Networking](references/networking.md)** - Services, Ingress, Network Policies, Service Mesh - **[Security](references/security.md)** - RBAC, Pod Security, Network Policies, Secrets - **[Storage](references/storage.md)** - Volumes, Persistent Volumes, ConfigMaps, StatefulSets ## When to Use This Skill Use this skill when: - Deploying containerized applications to Kubernetes - Configuring auto-scaling and resource management - Setting up ingress and load balancing - Implementing security policies and RBAC - Managing secrets and configurations - Troubleshooting pod issues - Planning cluster capacity - Migrating from Docker Compose to Kubernetes ## Related Skills - `@docker-patterns` - Containerization basics - `@ci-cd-pipelines` - CI/CD with Kubernetes - `@security-best-practices` - Container and cluster security - `@observability-monitoring` - Monitoring Kubernetes workloads - `@microservices-patterns` - Service mesh and distributed systems --- > Source: [Jonathan0823/opencode-config](https://github.com/Jonathan0823/opencode-config) — distributed by [TomeVault](https://tomevault.io).