kubernetes-patterns

# Kubernetes Patterns Deploy and manage production Kubernetes clusters. ## Core Objects ### Workloads | Object | Use Case | Scaling | |--------|----------|---------| | Deployment | Stateless apps | Replicas, HPA | | StatefulSet | Stateful apps (DBs) | Stable network IDs | | DaemonSet | Per-node agents (logging, monitoring) | Node count | | Job/CronJob | Batch tasks, scheduled jobs | Completion | ### Networking - **Service**: Stable endpoint for pods (ClusterIP, NodePort, LoadBalancer) - **Ingress**: HTTP routing, TLS termination, path-based routing - **Network Policies**: Pod-level firewall rules ## Production Best Practices ### Resource Management ```yaml resources: requests: cpu: 100m memory: 128Mi limits: cpu: 500m memory: 256Mi ``` - Always set requests AND limits - Use LimitRange for namespace defaults - Use ResourceQuota for namespace caps ### Pod Anti-Affinity Spread pods across nodes for HA. ### Readiness & Liveness Probes - Readiness: traffic starts flowing - Liveness: pod gets restarted - Startup: for slow-starting containers ## RBAC - Least-privilege service accounts per app - Namespace-scoped roles (not cluster-wide) - Regularly audit permissions - Use groups, not individual users ## Autoscaling - HPA: scale by CPU/memory or custom metrics - VPA: adjust resource requests automatically - Cluster Autoscaler: add/remove nodes - KEDA: event-driven scaling (SQS queue depth, etc.)