Container orchestration
Skill aiskillstore/marketplace/skills/0xdarkmatter/container-orchestration
Docker, Kubernetes, and AWS ECS/Fargate patterns. Triggers on: Dockerfile, docker-compose, kubernetes, k8s, helm, pod, deployment, service, ingress, container, image, ecs, fargate, task definition, ecs service, awsvpc, FARGATE_SPOT, ALB, ecs vs kubernetes.From its SKILL.md
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SKILL.md
5.3 KB, ~1.3k tokens by cl100k_base, as published. Nobody here has run it
Container Orchestration
Facts verified as of 2026-07.
Docker and Kubernetes patterns for containerized applications.
Dockerfile Best Practices
# Use specific version, not :latest
FROM python:3.11-slim AS builder
# Set working directory
WORKDIR /app
# Copy dependency files first (better caching)
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
# Copy application code
COPY src/ ./src/
# Production stage (multi-stage build)
FROM python:3.11-slim
WORKDIR /app
# Create non-root user
RUN useradd --create-home appuser
USER appuser
# Copy from builder
COPY --from=builder /app /app
# Set environment
ENV PYTHONUNBUFFERED=1
# Health check
HEALTHCHECK --interval=30s --timeout=3s \
CMD curl -f http://localhost:8000/health || exit 1
EXPOSE 8000
CMD ["python", "-m", "uvicorn", "src.main:app", "--host", "0.0.0.0"]
Dockerfile Rules
DO:
- Use specific base image versions
- Use multi-stage builds
- Run as non-root user
- Order commands by change frequency
- Use .dockerignore
- Add health checks
DON'T:
- Use :latest tag
- Run as root
- Copy unnecessary files
- Store secrets in image
- Install dev dependencies in production
Docker Compose
# docker-compose.yml
version: "3.9"
services:
app:
build:
context: .
dockerfile: Dockerfile
ports:
- "8000:8000"
environment:
- DATABASE_URL=postgres://user:pass@db:5432/app
depends_on:
db:
condition: service_healthy
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
interval: 30s
timeout: 10s
retries: 3
db:
image: postgres:15-alpine
volumes:
- postgres_data:/var/lib/postgresql/data
environment:
POSTGRES_USER: user
POSTGRES_PASSWORD: pass
POSTGRES_DB: app
healthcheck:
test: ["CMD-SHELL", "pg_isready -U user -d app"]
interval: 10s
timeout: 5s
retries: 5
volumes:
postgres_data:
Kubernetes Basics
Deployment
apiVersion: apps/v1
kind: Deployment
metadata:
name: app
labels:
app: myapp
spec:
replicas: 3
selector:
matchLabels:
app: myapp
template:
metadata:
labels:
app: myapp
spec:
containers:
- name: app
image: myapp:1.0.0
ports:
- containerPort: 8000
resources:
requests:
memory: "128Mi"
cpu: "100m"
limits:
memory: "256Mi"
cpu: "500m"
livenessProbe:
httpGet:
path: /health
port: 8000
initialDelaySeconds: 10
periodSeconds: 30
readinessProbe:
httpGet:
path: /ready
port: 8000
initialDelaySeconds: 5
periodSeconds: 10
env:
- name: DATABASE_URL
valueFrom:
secretKeyRef:
name: app-secrets
key: database-url
Service
apiVersion: v1
kind: Service
metadata:
name: app-service
spec:
selector:
app: myapp
ports:
- port: 80
targetPort: 8000
type: ClusterIP
Ingress
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: app-ingress
annotations:
nginx.ingress.kubernetes.io/rewrite-target: /
spec:
ingressClassName: nginx
rules:
- host: app.example.com
http:
paths:
- path: /
pathType: Prefix
backend:
service:
name: app-service
port:
number: 80
kubectl Quick Reference
| Command | Description |
|---|---|
kubectl get pods | List pods |
kubectl logs <pod> | View logs |
kubectl exec -it <pod> -- sh | Shell into pod |
kubectl apply -f manifest.yaml | Apply config |
kubectl rollout restart deployment/app | Restart deployment |
kubectl rollout status deployment/app | Check rollout |
kubectl describe pod <pod> | Debug pod |
kubectl port-forward svc/app 8080:80 | Local port forward |
Additional Resources
./references/dockerfile-patterns.md- Advanced Dockerfile techniques./references/k8s-manifests.md- Full Kubernetes manifest examples./references/helm-patterns.md- Helm chart structure and values./references/ecs-fargate.md- Amazon ECS on AWS Fargate (task definitions, services, awsvpc networking, IAM roles, secrets, scaling, ALB/NLB, ECS vs Kubernetes)
Scripts
./scripts/build-push.sh- Build and push Docker image
Assets
./assets/Dockerfile.template- Production Dockerfile template./assets/docker-compose.template.yml- Compose starter template
What ships with it: 9 files
158.2 KB alongside SKILL.md, 2 of them executable
assets/
- docker-compose.template.yml4.1 KB
- Dockerfile.template1.9 KB
references/
- dockerfile-patterns.md6.3 KB
- ecs-fargate.md6.7 KB
- helm-patterns.md7.4 KB
- k8s-manifests.md6.9 KB
scripts/
- build-push.shruns5.3 KB
tests/
- run.shruns7.7 KB
- skill-report.json111.9 KB
Gives 0 of the 12 instructions most agent orchestration skills give in ~1.3k tokens
Counted across 848 of the 1,300 authors here whose files we hold, read 2026-09-06
- Dispatch one agent per independent problem domainin 56 of 848, across 42 files
- Run full test suite after integrationin 55 of 848, across 42 files
- Verify fixes do not conflictin 40 of 848, across 32 files
- Review each summary when agents returnin 40 of 848, across 31 files
- Write a handoff document summarising the current conversationin 30 of 848, across 25 files
- Reference existing artifacts by path or URLin 26 of 848, across 24 files
- Give each agent a specific scopein 19 of 848, across 10 files
- Give each agent a clear goalin 19 of 848, across 10 files
- Include a suggested skills section in the documentin 18 of 848, across 16 files
- Tailor the doc to the user argumentsin 18 of 848, across 15 files
- Issue all subagent dispatches in the same responsein 17 of 848, across 11 files
- Use git worktrees for isolationin 17 of 848, across 8 files
Said here and by no other author read
- Use specific base image versions
- Use multi-stage builds
- Run as non-root user
- Order commands by change frequency
- Use .dockerignore
- Add health checks
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.