kubernetes-orchestration_skill

Overview

This skill is a comprehensive guide to Kubernetes container orchestration covering workloads, networking, storage, security, and production operations. It distills core concepts, object types, and practical YAML patterns for Deployments, StatefulSets, DaemonSets, Jobs, probes, resource requests/limits, and security contexts. The content targets engineers who run containerized apps in development and production.

How this skill works

The skill inspects and explains Kubernetes primitives and control-plane/node components, showing how objects (metadata, spec, status) map to real behavior. It provides concrete YAML examples and recommended patterns for rollout strategies, stateful apps, cluster-level services, ingress, storage claims, probes, autoscaling, logging, and monitoring. It also outlines operational tasks: RBAC, namespaces, troubleshooting, and production readiness.

When to use it

• Designing or refactoring application deployments for Kubernetes
• Migrating stateful services or databases to Kubernetes
• Implementing observability, logging, and monitoring pipelines
• Hardening cluster access, RBAC, and pod security contexts
• Defining autoscaling, resource quotas, and production rollout strategies
• Running batch or scheduled workloads with Jobs and CronJobs

Best practices

• Declare resource requests and limits for predictable scheduling and autoscaling
• Use readiness/liveness/startup probes to manage pod lifecycle and rollouts
• Prefer Deployment rolling updates or blue/green strategies for zero-downtime releases
• Use StatefulSets with PersistentVolumeClaim templates for stateful services
• Isolate teams and workloads with namespaces and resource quotas
• Centralize logging/metrics with DaemonSets and a cluster monitoring stack

Example use cases

• Deploy a stateless web application with Deployment, Service, and Ingress for public traffic
• Run a replicated MySQL cluster with StatefulSet + headless Service and PVC templates
• Install node-level exporters and log collectors as DaemonSets for cluster observability
• Execute parallel batch processing using Job with completions and parallelism settings
• Implement a blue/green rollout for a critical API using two Deployments and switch Service selector
• Enforce least-privilege access by mapping RBAC roles and PodSecurityContexts