Agent skill
docker-patterns
Docker and Docker Compose patterns for local development, container security, networking, volume strategies, and multi-service orchestration.
Install this agent skill to your Project
npx add-skill https://github.com/x-cmd/skill/tree/main/data/affaanmustafa/docker-patterns
SKILL.md
Docker Patterns
Docker and Docker Compose best practices for containerized development.
When to Activate
- Setting up Docker Compose for local development
- Designing multi-container architectures
- Troubleshooting container networking or volume issues
- Reviewing Dockerfiles for security and size
- Migrating from local dev to containerized workflow
Docker Compose for Local Development
Standard Web App Stack
# docker-compose.yml
services:
app:
build:
context: .
target: dev # Use dev stage of multi-stage Dockerfile
ports:
- "3000:3000"
volumes:
- .:/app # Bind mount for hot reload
- /app/node_modules # Anonymous volume -- preserves container deps
environment:
- DATABASE_URL=postgres://postgres:postgres@db:5432/app_dev
- REDIS_URL=redis://redis:6379/0
- NODE_ENV=development
depends_on:
db:
condition: service_healthy
redis:
condition: service_started
command: npm run dev
db:
image: postgres:16-alpine
ports:
- "5432:5432"
environment:
POSTGRES_USER: postgres
POSTGRES_PASSWORD: postgres
POSTGRES_DB: app_dev
volumes:
- pgdata:/var/lib/postgresql/data
- ./scripts/init-db.sql:/docker-entrypoint-initdb.d/init.sql
healthcheck:
test: ["CMD-SHELL", "pg_isready -U postgres"]
interval: 5s
timeout: 3s
retries: 5
redis:
image: redis:7-alpine
ports:
- "6379:6379"
volumes:
- redisdata:/data
mailpit: # Local email testing
image: axllent/mailpit
ports:
- "8025:8025" # Web UI
- "1025:1025" # SMTP
volumes:
pgdata:
redisdata:
Development vs Production Dockerfile
# Stage: dependencies
FROM node:22-alpine AS deps
WORKDIR /app
COPY package.json package-lock.json ./
RUN npm ci
# Stage: dev (hot reload, debug tools)
FROM node:22-alpine AS dev
WORKDIR /app
COPY --from=deps /app/node_modules ./node_modules
COPY . .
EXPOSE 3000
CMD ["npm", "run", "dev"]
# Stage: build
FROM node:22-alpine AS build
WORKDIR /app
COPY --from=deps /app/node_modules ./node_modules
COPY . .
RUN npm run build && npm prune --production
# Stage: production (minimal image)
FROM node:22-alpine AS production
WORKDIR /app
RUN addgroup -g 1001 -S appgroup && adduser -S appuser -u 1001
USER appuser
COPY --from=build --chown=appuser:appgroup /app/dist ./dist
COPY --from=build --chown=appuser:appgroup /app/node_modules ./node_modules
COPY --from=build --chown=appuser:appgroup /app/package.json ./
ENV NODE_ENV=production
EXPOSE 3000
HEALTHCHECK --interval=30s --timeout=3s CMD wget -qO- http://localhost:3000/health || exit 1
CMD ["node", "dist/server.js"]
Override Files
# docker-compose.override.yml (auto-loaded, dev-only settings)
services:
app:
environment:
- DEBUG=app:*
- LOG_LEVEL=debug
ports:
- "9229:9229" # Node.js debugger
# docker-compose.prod.yml (explicit for production)
services:
app:
build:
target: production
restart: always
deploy:
resources:
limits:
cpus: "1.0"
memory: 512M
# Development (auto-loads override)
docker compose up
# Production
docker compose -f docker-compose.yml -f docker-compose.prod.yml up -d
Networking
Service Discovery
Services in the same Compose network resolve by service name:
# From "app" container:
postgres://postgres:postgres@db:5432/app_dev # "db" resolves to the db container
redis://redis:6379/0 # "redis" resolves to the redis container
Custom Networks
services:
frontend:
networks:
- frontend-net
api:
networks:
- frontend-net
- backend-net
db:
networks:
- backend-net # Only reachable from api, not frontend
networks:
frontend-net:
backend-net:
Exposing Only What's Needed
services:
db:
ports:
- "127.0.0.1:5432:5432" # Only accessible from host, not network
# Omit ports entirely in production -- accessible only within Docker network
Volume Strategies
volumes:
# Named volume: persists across container restarts, managed by Docker
pgdata:
# Bind mount: maps host directory into container (for development)
# - ./src:/app/src
# Anonymous volume: preserves container-generated content from bind mount override
# - /app/node_modules
Common Patterns
services:
app:
volumes:
- .:/app # Source code (bind mount for hot reload)
- /app/node_modules # Protect container's node_modules from host
- /app/.next # Protect build cache
db:
volumes:
- pgdata:/var/lib/postgresql/data # Persistent data
- ./scripts/init.sql:/docker-entrypoint-initdb.d/init.sql # Init scripts
Container Security
Dockerfile Hardening
# 1. Use specific tags (never :latest)
FROM node:22.12-alpine3.20
# 2. Run as non-root
RUN addgroup -g 1001 -S app && adduser -S app -u 1001
USER app
# 3. Drop capabilities (in compose)
# 4. Read-only root filesystem where possible
# 5. No secrets in image layers
Compose Security
services:
app:
security_opt:
- no-new-privileges:true
read_only: true
tmpfs:
- /tmp
- /app/.cache
cap_drop:
- ALL
cap_add:
- NET_BIND_SERVICE # Only if binding to ports < 1024
Secret Management
# GOOD: Use environment variables (injected at runtime)
services:
app:
env_file:
- .env # Never commit .env to git
environment:
- API_KEY # Inherits from host environment
# GOOD: Docker secrets (Swarm mode)
secrets:
db_password:
file: ./secrets/db_password.txt
services:
db:
secrets:
- db_password
# BAD: Hardcoded in image
# ENV API_KEY=sk-proj-xxxxx # NEVER DO THIS
.dockerignore
node_modules
.git
.env
.env.*
dist
coverage
*.log
.next
.cache
docker-compose*.yml
Dockerfile*
README.md
tests/
Debugging
Common Commands
# View logs
docker compose logs -f app # Follow app logs
docker compose logs --tail=50 db # Last 50 lines from db
# Execute commands in running container
docker compose exec app sh # Shell into app
docker compose exec db psql -U postgres # Connect to postgres
# Inspect
docker compose ps # Running services
docker compose top # Processes in each container
docker stats # Resource usage
# Rebuild
docker compose up --build # Rebuild images
docker compose build --no-cache app # Force full rebuild
# Clean up
docker compose down # Stop and remove containers
docker compose down -v # Also remove volumes (DESTRUCTIVE)
docker system prune # Remove unused images/containers
Debugging Network Issues
# Check DNS resolution inside container
docker compose exec app nslookup db
# Check connectivity
docker compose exec app wget -qO- http://api:3000/health
# Inspect network
docker network ls
docker network inspect <project>_default
Anti-Patterns
# BAD: Using docker compose in production without orchestration
# Use Kubernetes, ECS, or Docker Swarm for production multi-container workloads
# BAD: Storing data in containers without volumes
# Containers are ephemeral -- all data lost on restart without volumes
# BAD: Running as root
# Always create and use a non-root user
# BAD: Using :latest tag
# Pin to specific versions for reproducible builds
# BAD: One giant container with all services
# Separate concerns: one process per container
# BAD: Putting secrets in docker-compose.yml
# Use .env files (gitignored) or Docker secrets
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
pufferlib
High-performance reinforcement learning framework optimized for speed and scale. Use when you need fast parallel training, vectorized environments, multi-agent systems, or integration with game environments (Atari, Procgen, NetHack). Achieves 2-10x speedups over standard implementations. For quick prototyping or standard algorithm implementations with extensive documentation, use stable-baselines3 instead.
fluidsim
Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.
metabolomics-workbench-database
Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.
geniml
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.
zinc-database
Access ZINC (230M+ purchasable compounds). Search by ZINC ID/SMILES, similarity searches, 3D-ready structures for docking, analog discovery, for virtual screening and drug discovery.
astropy
Comprehensive Python library for astronomy and astrophysics. This skill should be used when working with astronomical data including celestial coordinates, physical units, FITS files, cosmological calculations, time systems, tables, world coordinate systems (WCS), and astronomical data analysis. Use when tasks involve coordinate transformations, unit conversions, FITS file manipulation, cosmological distance calculations, time scale conversions, or astronomical data processing.
Didn't find tool you were looking for?