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Orchestrating with Kubernetes

@doanchienthangdev/omgkit
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The agent implements Kubernetes container orchestration with deployments, services, Helm charts, and production patterns. Use when deploying containerized applications, configuring autoscaling, managing secrets, or setting up ingress routing.

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SKILL.md

name Orchestrating with Kubernetes
description The agent implements Kubernetes container orchestration with deployments, services, Helm charts, and production patterns. Use when deploying containerized applications, configuring autoscaling, managing secrets, or setting up ingress routing.

Orchestrating with Kubernetes

Quick Start

# deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: api-server
spec:
  replicas: 3
  selector:
    matchLabels:
      app: api-server
  template:
    metadata:
      labels:
        app: api-server
    spec:
      containers:
        - name: api
          image: ghcr.io/org/api:v1.0.0
          ports:
            - containerPort: 3000
          resources:
            requests: { cpu: "100m", memory: "256Mi" }
            limits: { cpu: "500m", memory: "512Mi" }

kubectl apply -f deployment.yaml

Features

Feature Description Guide
Deployments Declarative pod management with rollbacks Define replicas, update strategy, pod template
Services Internal/external load balancing ClusterIP for internal, LoadBalancer for external
ConfigMaps/Secrets Configuration and sensitive data Mount as volumes or environment variables
Ingress HTTP routing with TLS termination Use nginx-ingress or cloud provider ingress
HPA Horizontal Pod Autoscaler Scale based on CPU, memory, or custom metrics
Helm Package manager for K8s applications Template and version deployments

Common Patterns

Production Deployment with Probes

spec:
  containers:
    - name: api
      image: ghcr.io/org/api:v1.0.0
      livenessProbe:
        httpGet: { path: /health/live, port: 3000 }
        initialDelaySeconds: 15
        periodSeconds: 20
      readinessProbe:
        httpGet: { path: /health/ready, port: 3000 }
        initialDelaySeconds: 5
        periodSeconds: 10
      env:
        - name: DATABASE_URL
          valueFrom:
            secretKeyRef: { name: app-secrets, key: database-url }

Horizontal Pod Autoscaler

apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: api-server
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: api-server
  minReplicas: 3
  maxReplicas: 20
  metrics:
    - type: Resource
      resource: { name: cpu, target: { type: Utilization, averageUtilization: 70 } }

Ingress with TLS

apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: api-ingress
  annotations:
    cert-manager.io/cluster-issuer: letsencrypt-prod
spec:
  tls:
    - hosts: [api.example.com]
      secretName: api-tls
  rules:
    - host: api.example.com
      http:
        paths:
          - path: /
            pathType: Prefix
            backend:
              service: { name: api-server, port: { number: 80 } }

Best Practices

Do Avoid
Set resource requests and limits Running containers as root
Implement liveness and readiness probes Using latest tag in production
Use namespaces for environment isolation Hardcoding config in container images
Configure Pod Disruption Budgets Skipping network policies
Use Secrets for sensitive data Exposing unnecessary ports
Implement pod anti-affinity rules Using NodePort in production
Set up HPA for autoscaling Ignoring pod security standards