docker
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Skill 文档
Docker Containerization Skill
Summary
Docker provides containerization for packaging applications with their dependencies into isolated, portable units. Containers ensure consistency across development, testing, and production environments, eliminating “works on my machine” problems.
When to Use
- Local Development: Consistent dev environments across team members
- CI/CD Pipelines: Reproducible build and test environments
- Microservices: Isolated services with independent scaling
- Production Deployment: Portable applications across cloud providers
- Database/Service Testing: Ephemeral databases for integration tests
- Legacy Application Isolation: Run incompatible dependencies side-by-side
Quick Start
1. Create Dockerfile
FROM node:18-alpine
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY . .
EXPOSE 3000
CMD ["node", "server.js"]
2. Build Image
docker build -t myapp:1.0 .
3. Run Container
docker run -p 3000:3000 myapp:1.0
Core Concepts
Images vs Containers
- Image: Read-only template with application code, runtime, and dependencies
- Container: Running instance of an image with writable layer
- Registry: Storage for images (Docker Hub, GitHub Container Registry)
Layers and Caching
Each Dockerfile instruction creates a layer. Docker caches unchanged layers for faster builds.
# GOOD: Dependencies change less frequently than code
FROM python:3.11-slim
COPY requirements.txt .
RUN pip install -r requirements.txt # Cached unless requirements.txt changes
COPY . . # Rebuild only when code changes
# BAD: Invalidates cache on every code change
FROM python:3.11-slim
COPY . . # Changes frequently
RUN pip install -r requirements.txt # Reinstalls on every build
Volumes
Persistent data storage that survives container restarts.
# Named volume (managed by Docker)
docker run -v mydata:/app/data myapp
# Bind mount (host directory)
docker run -v $(pwd)/data:/app/data myapp
# Anonymous volume (temporary)
docker run -v /app/data myapp
Networks
Containers communicate through Docker networks.
# Create network
docker network create mynetwork
# Run containers on network
docker run --network mynetwork --name db postgres
docker run --network mynetwork --name app myapp
# App can connect to db using hostname "db"
Dockerfile Basics
Essential Instructions
# Base image
FROM node:18-alpine
# Metadata
LABEL maintainer="dev@example.com"
LABEL version="1.0"
# Set working directory
WORKDIR /app
# Copy files
COPY package*.json ./
COPY src/ ./src/
# Run commands (creates layer)
RUN npm ci --only=production
# Set environment variables
ENV NODE_ENV=production
ENV PORT=3000
# Expose ports (documentation only)
EXPOSE 3000
# Default command
CMD ["node", "src/server.js"]
# Alternative: ENTRYPOINT (not overridden by docker run args)
ENTRYPOINT ["node"]
CMD ["src/server.js"] # Default args for ENTRYPOINT
Instruction Order for Cache Efficiency
# 1. Base image (rarely changes)
FROM python:3.11-slim
# 2. System dependencies (rarely change)
RUN apt-get update && apt-get install -y \
gcc \
&& rm -rf /var/lib/apt/lists/*
# 3. Application dependencies (change occasionally)
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
# 4. Application code (changes frequently)
COPY . .
# 5. Runtime configuration
ENV PYTHONUNBUFFERED=1
EXPOSE 8000
CMD ["python", "manage.py", "runserver", "0.0.0.0:8000"]
.dockerignore
Exclude files from build context (faster builds, smaller images).
# .dockerignore
node_modules/
npm-debug.log
.git/
.gitignore
*.md
.env
.vscode/
__pycache__/
*.pyc
.pytest_cache/
coverage/
dist/
build/
Multi-Stage Builds
Optimize image size by separating build and runtime stages.
Node.js TypeScript Example
# Build stage
FROM node:18-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build
# Production stage
FROM node:18-alpine
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY /app/dist ./dist
EXPOSE 3000
CMD ["node", "dist/server.js"]
Benefits:
- Build dependencies (TypeScript, webpack) excluded from final image
- Final image: ~50MB vs ~500MB with build tools
- Faster deployments and reduced attack surface
Python Example
# Build stage
FROM python:3.11 AS builder
WORKDIR /app
COPY requirements.txt .
RUN pip install --user --no-cache-dir -r requirements.txt
# Runtime stage
FROM python:3.11-slim
WORKDIR /app
COPY /root/.local /root/.local
COPY . .
ENV PATH=/root/.local/bin:$PATH
CMD ["python", "app.py"]
Go Example (Smallest Images)
# Build stage
FROM golang:1.21-alpine AS builder
WORKDIR /app
COPY go.* ./
RUN go mod download
COPY . .
RUN CGO_ENABLED=0 GOOS=linux go build -o server
# Runtime stage (scratch = empty base image)
FROM scratch
COPY /app/server /server
EXPOSE 8080
ENTRYPOINT ["/server"]
Result: ~10MB final image containing only the compiled binary.
Docker Compose
Define multi-container applications in YAML.
Basic Structure
version: '3.8'
services:
app:
build: .
ports:
- "3000:3000"
environment:
- DATABASE_URL=postgres://db:5432/myapp
depends_on:
- db
volumes:
- ./src:/app/src # Hot reload in development
db:
image: postgres:15-alpine
environment:
POSTGRES_PASSWORD: secret
POSTGRES_DB: myapp
volumes:
- db_data:/var/lib/postgresql/data
ports:
- "5432:5432"
volumes:
db_data:
Commands
# Start all services
docker-compose up
# Start in background
docker-compose up -d
# Rebuild images
docker-compose up --build
# Stop services
docker-compose down
# Stop and remove volumes
docker-compose down -v
# View logs
docker-compose logs -f app
# Run one-off command
docker-compose run app npm test
Full Stack Example
version: '3.8'
services:
# Frontend
web:
build:
context: ./frontend
dockerfile: Dockerfile.dev
ports:
- "3000:3000"
volumes:
- ./frontend/src:/app/src
environment:
- REACT_APP_API_URL=http://localhost:8000
# Backend API
api:
build: ./backend
ports:
- "8000:8000"
environment:
- DATABASE_URL=postgresql://postgres:secret@db:5432/myapp
- REDIS_URL=redis://redis:6379
depends_on:
db:
condition: service_healthy
redis:
condition: service_started
volumes:
- ./backend:/app
command: uvicorn main:app --host 0.0.0.0 --reload
# Database
db:
image: postgres:15-alpine
environment:
POSTGRES_PASSWORD: secret
POSTGRES_DB: myapp
volumes:
- db_data:/var/lib/postgresql/data
- ./init.sql:/docker-entrypoint-initdb.d/init.sql
healthcheck:
test: ["CMD-SHELL", "pg_isready -U postgres"]
interval: 10s
timeout: 5s
retries: 5
# Cache
redis:
image: redis:7-alpine
ports:
- "6379:6379"
volumes:
- redis_data:/data
# Worker (background jobs)
worker:
build: ./backend
command: celery -A tasks worker --loglevel=info
environment:
- REDIS_URL=redis://redis:6379
depends_on:
- redis
- db
volumes:
db_data:
redis_data:
networks:
default:
name: myapp_network
Development Workflows
Hot Reload with Volumes
Node.js
services:
app:
build: .
volumes:
- ./src:/app/src # Sync source code
- /app/node_modules # Prevent overwriting container's node_modules
command: npm run dev
# Dockerfile.dev
FROM node:18-alpine
WORKDIR /app
COPY package*.json ./
RUN npm install # Include dev dependencies
COPY . .
EXPOSE 3000
CMD ["npm", "run", "dev"]
Python (Django/FastAPI)
services:
web:
build: .
volumes:
- .:/app
command: python manage.py runserver 0.0.0.0:8000
# or for FastAPI:
# command: uvicorn main:app --host 0.0.0.0 --reload
VS Code Dev Containers
.devcontainer/devcontainer.json:
{
"name": "Python Dev Container",
"dockerComposeFile": "../docker-compose.yml",
"service": "app",
"workspaceFolder": "/app",
"customizations": {
"vscode": {
"extensions": [
"ms-python.python",
"ms-python.vscode-pylance"
],
"settings": {
"python.defaultInterpreterPath": "/usr/local/bin/python"
}
}
},
"postCreateCommand": "pip install -r requirements-dev.txt",
"remoteUser": "vscode"
}
Local Database Containers
# PostgreSQL
docker run -d \
--name dev-postgres \
-e POSTGRES_PASSWORD=localdev \
-e POSTGRES_DB=myapp_dev \
-p 5432:5432 \
-v pgdata:/var/lib/postgresql/data \
postgres:15-alpine
# MySQL
docker run -d \
--name dev-mysql \
-e MYSQL_ROOT_PASSWORD=localdev \
-e MYSQL_DATABASE=myapp_dev \
-p 3306:3306 \
-v mysqldata:/var/lib/mysql \
mysql:8
# MongoDB
docker run -d \
--name dev-mongo \
-p 27017:27017 \
-v mongodata:/data/db \
mongo:7
# Redis
docker run -d \
--name dev-redis \
-p 6379:6379 \
redis:7-alpine
Production Patterns
Health Checks
FROM node:18-alpine
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY . .
# Health check endpoint
HEALTHCHECK \
CMD node healthcheck.js
EXPOSE 3000
CMD ["node", "server.js"]
// healthcheck.js
const http = require('http');
const options = {
host: 'localhost',
port: 3000,
path: '/health',
timeout: 2000
};
const request = http.request(options, (res) => {
if (res.statusCode === 200) {
process.exit(0);
} else {
process.exit(1);
}
});
request.on('error', () => process.exit(1));
request.end();
Security Best Practices
FROM python:3.11-slim
# 1. Use non-root user
RUN groupadd -r appuser && useradd -r -g appuser appuser
# 2. Install dependencies as root
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
# 3. Copy application files
COPY . .
# 4. Switch to non-root user
USER appuser
# 5. Drop unnecessary privileges
EXPOSE 8000
CMD ["gunicorn", "--bind", "0.0.0.0:8000", "app:app"]
Additional Security Measures:
- Use minimal base images (alpine, distroless)
- Scan images for vulnerabilities:
docker scan myapp:latest - Don’t include secrets in images (use environment variables or secret managers)
- Keep base images updated
- Use read-only root filesystem when possible
Secrets Management
# Docker Swarm secrets (production)
echo "db_password_here" | docker secret create db_password -
version: '3.8'
services:
app:
image: myapp
secrets:
- db_password
environment:
- DB_PASSWORD_FILE=/run/secrets/db_password
secrets:
db_password:
external: true
Alternative: Environment Files
# docker-compose.yml
services:
app:
env_file:
- .env.production # Never commit this file
# .env.production (gitignored)
DATABASE_URL=postgresql://user:pass@db:5432/prod
SECRET_KEY=your-secret-key
Resource Limits
services:
app:
image: myapp
deploy:
resources:
limits:
cpus: '1.0'
memory: 512M
reservations:
cpus: '0.5'
memory: 256M
restart_policy:
condition: on-failure
delay: 5s
max_attempts: 3
# Command-line resource limits
docker run -d \
--memory="512m" \
--cpus="1.0" \
--restart=unless-stopped \
myapp
Framework-Specific Examples
Python: Django
FROM python:3.11-slim
ENV PYTHONUNBUFFERED=1
ENV PYTHONDONTWRITEBYTECODE=1
WORKDIR /app
# Install system dependencies
RUN apt-get update && apt-get install -y \
postgresql-client \
&& rm -rf /var/lib/apt/lists/*
# Install Python dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
# Copy application
COPY . .
# Collect static files
RUN python manage.py collectstatic --noinput
# Create non-root user
RUN useradd -m -u 1000 django && chown -R django:django /app
USER django
EXPOSE 8000
CMD ["gunicorn", "--bind", "0.0.0.0:8000", "--workers", "4", "myproject.wsgi:application"]
docker-compose.yml:
version: '3.8'
services:
web:
build: .
command: python manage.py runserver 0.0.0.0:8000
volumes:
- .:/app
ports:
- "8000:8000"
environment:
- DEBUG=1
- DATABASE_URL=postgres://postgres:postgres@db:5432/django_dev
depends_on:
- db
db:
image: postgres:15-alpine
environment:
POSTGRES_PASSWORD: postgres
POSTGRES_DB: django_dev
volumes:
- postgres_data:/var/lib/postgresql/data
volumes:
postgres_data:
Python: FastAPI
FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
EXPOSE 8000
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000", "--workers", "4"]
Node.js: Next.js
# Multi-stage build for Next.js
FROM node:18-alpine AS deps
WORKDIR /app
COPY package*.json ./
RUN npm ci
FROM node:18-alpine AS builder
WORKDIR /app
COPY /app/node_modules ./node_modules
COPY . .
RUN npm run build
FROM node:18-alpine AS runner
WORKDIR /app
ENV NODE_ENV=production
RUN addgroup -g 1001 -S nodejs
RUN adduser -S nextjs -u 1001
COPY /app/public ./public
COPY /app/.next/standalone ./
COPY /app/.next/static ./.next/static
USER nextjs
EXPOSE 3000
CMD ["node", "server.js"]
next.config.js (required for standalone output):
module.exports = {
output: 'standalone',
}
Node.js: Express
FROM node:18-alpine
WORKDIR /app
# Install dependencies
COPY package*.json ./
RUN npm ci --only=production
# Copy application
COPY . .
# Create non-root user
RUN addgroup -S appgroup && adduser -S appuser -G appgroup
USER appuser
EXPOSE 3000
CMD ["node", "server.js"]
TypeScript Build
# Build stage
FROM node:18-alpine AS builder
WORKDIR /app
COPY package*.json tsconfig.json ./
RUN npm ci
COPY src/ ./src/
RUN npm run build
# Production stage
FROM node:18-alpine
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY /app/dist ./dist
EXPOSE 3000
CMD ["node", "dist/index.js"]
Container Orchestration Basics
Docker Swarm (Built-in)
# Initialize swarm
docker swarm init
# Deploy stack
docker stack deploy -c docker-compose.yml myapp
# Scale service
docker service scale myapp_web=5
# Update service (zero-downtime)
docker service update --image myapp:2.0 myapp_web
# Remove stack
docker stack rm myapp
Kubernetes Comparison
| Feature | Docker Compose | Docker Swarm | Kubernetes |
|---|---|---|---|
| Complexity | Low | Medium | High |
| Use Case | Local dev | Small clusters | Production at scale |
| Setup | Single file | Built-in | Separate installation |
| Scaling | Manual | Automatic | Automatic + Advanced |
| HA | No | Yes | Yes |
| Ecosystem | Limited | Docker | Massive |
When to use each:
- Docker Compose: Local development, simple deployments
- Docker Swarm: Small production clusters, simpler than K8s
- Kubernetes: Large-scale production, multi-cloud, advanced orchestration
CI/CD Integration
GitHub Actions
# .github/workflows/docker.yml
name: Build and Push Docker Image
on:
push:
branches: [main]
pull_request:
branches: [main]
env:
REGISTRY: ghcr.io
IMAGE_NAME: ${{ github.repository }}
jobs:
build:
runs-on: ubuntu-latest
permissions:
contents: read
packages: write
steps:
- uses: actions/checkout@v3
- name: Log in to Container Registry
uses: docker/login-action@v2
with:
registry: ${{ env.REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Extract metadata
id: meta
uses: docker/metadata-action@v4
with:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
tags: |
type=ref,event=branch
type=semver,pattern={{version}}
type=sha
- name: Build and push
uses: docker/build-push-action@v4
with:
context: .
push: true
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
cache-from: type=gha
cache-to: type=gha,mode=max
- name: Run tests
run: |
docker run --rm ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.sha }} npm test
GitLab CI
# .gitlab-ci.yml
stages:
- build
- test
- deploy
variables:
DOCKER_DRIVER: overlay2
IMAGE_TAG: $CI_REGISTRY_IMAGE:$CI_COMMIT_SHORT_SHA
build:
stage: build
image: docker:latest
services:
- docker:dind
script:
- docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY
- docker build -t $IMAGE_TAG .
- docker push $IMAGE_TAG
test:
stage: test
script:
- docker run --rm $IMAGE_TAG npm test
deploy:
stage: deploy
script:
- docker pull $IMAGE_TAG
- docker tag $IMAGE_TAG $CI_REGISTRY_IMAGE:latest
- docker push $CI_REGISTRY_IMAGE:latest
only:
- main
Debugging Containers
Viewing Logs
# Stream logs
docker logs -f container_name
# Last 100 lines
docker logs --tail 100 container_name
# Logs since timestamp
docker logs --since 2024-01-01T10:00:00 container_name
# With timestamps
docker logs -t container_name
# Docker Compose logs
docker-compose logs -f service_name
Execute Commands in Running Container
# Interactive shell
docker exec -it container_name /bin/sh
# or
docker exec -it container_name /bin/bash
# Run single command
docker exec container_name ls -la /app
# Run as different user
docker exec -u root container_name apt-get update
Inspect Container
# Full container details
docker inspect container_name
# Specific field (IP address)
docker inspect -f '{{.NetworkSettings.IPAddress}}' container_name
# Environment variables
docker inspect -f '{{.Config.Env}}' container_name
# Mounted volumes
docker inspect -f '{{.Mounts}}' container_name
Resource Usage
# Real-time stats
docker stats
# Single container
docker stats container_name
# No streaming (single snapshot)
docker stats --no-stream
Network Debugging
# List networks
docker network ls
# Inspect network
docker network inspect bridge
# Test connectivity between containers
docker exec container1 ping container2
# Check DNS resolution
docker exec container_name nslookup other_container
Debugging Build Issues
# Build with no cache
docker build --no-cache -t myapp .
# Show build progress
docker build --progress=plain -t myapp .
# Build specific stage
docker build --target builder -t myapp-builder .
# Inspect intermediate layers
docker history myapp:latest
Local Docker Patterns (mcp-browser, mcp-memory)
mcp-browser dev compose
docker-compose.ymlrunsmcp-serverwith a port range8875-8895and optionalchromeprofile.- Code mounts are read-only (
./src:/app/src:ro) with persistent logs and temp volumes. - Environment defaults:
MCP_DEBUG=true,MCP_LOG_LEVEL=DEBUG,MCP_HOST=0.0.0.0,MCP_PORT=8875. - Optional profiles:
chrome(browser) andtools(dev tools container).
mcp-browser Dockerfile.dev
ARG PYTHON_VERSION=3.11, installwatchdog+ Playwright Chromium.- Install package in editable mode and run
python -m src.dev_runner. - Non-root user and healthcheck on
/health.
mcp-memory production Dockerfile
- Multi-stage build with venv in
/opt/venvandpython:3.11-slim. - Runtime installs
curlfor healthcheck, setsPYTHONPATH=/app. - Uses non-root user and
CMD ["python", "run_api_server.py"]with/healthcheck.
Troubleshooting
Common Issues
“Port already in use”
# Find process using port
lsof -i :3000
# or
netstat -tulpn | grep 3000
# Kill process
kill -9 <PID>
# Or use different host port
docker run -p 3001:3000 myapp
“Cannot connect to Docker daemon”
# Check Docker is running
docker info
# Restart Docker Desktop (Mac/Windows)
# or
sudo systemctl restart docker # Linux
# Check permissions (Linux)
sudo usermod -aG docker $USER
# Log out and back in
“No space left on device”
# Remove unused containers, images, volumes
docker system prune -a --volumes
# Remove only dangling images
docker image prune
# Remove stopped containers
docker container prune
# Remove unused volumes
docker volume prune
# Check disk usage
docker system df
“Build context too large”
# Create .dockerignore
cat > .dockerignore << EOF
node_modules/
.git/
*.log
dist/
coverage/
EOF
# Build with specific context
docker build -f Dockerfile -t myapp ./src
Container Exits Immediately
# Check logs
docker logs container_name
# Run with interactive shell to debug
docker run -it myapp /bin/sh
# Override entrypoint
docker run -it --entrypoint /bin/sh myapp
# Check exit code
docker inspect -f '{{.State.ExitCode}}' container_name
Permission Denied in Container
# Run as root to debug
docker exec -u root -it container_name /bin/sh
# Fix ownership
docker exec -u root container_name chown -R appuser:appuser /app
# Or rebuild with correct permissions in Dockerfile
Performance Issues
Slow Builds
# Use BuildKit (faster, better caching)
DOCKER_BUILDKIT=1 docker build -t myapp .
# Multi-stage builds to reduce layers
# Order instructions by change frequency
# Use .dockerignore to exclude unnecessary files
High Memory Usage
# Set memory limits
docker run -m 512m myapp
# Monitor memory
docker stats container_name
# Check for memory leaks in application
Slow Volume Mounts (Mac/Windows)
# Use delegated consistency (Mac)
volumes:
- ./src:/app/src:delegated
# Or use named volumes instead of bind mounts
volumes:
- node_modules:/app/node_modules
Best Practices
Layer Optimization
- Order by Change Frequency: Least frequently changed first
- Combine RUN Commands: Reduce layers
- Clean Up in Same Layer: Remove temp files immediately
# GOOD
RUN apt-get update && apt-get install -y \
package1 \
package2 \
&& rm -rf /var/lib/apt/lists/*
# BAD (creates 3 layers, apt cache remains in layer 2)
RUN apt-get update
RUN apt-get install -y package1 package2
RUN rm -rf /var/lib/apt/lists/*
Image Size Reduction
- Use Alpine Images: 5MB vs 100MB+ for full Linux
- Multi-Stage Builds: Exclude build tools from final image
- Remove Unnecessary Files: Docs, examples, tests
- Use .dockerignore: Exclude development files
# Before: 800MB
FROM node:18
COPY . .
RUN npm install
CMD ["node", "server.js"]
# After: 120MB
FROM node:18-alpine
COPY package*.json ./
RUN npm ci --only=production
COPY server.js .
CMD ["node", "server.js"]
Security Checklist
- Use official base images from trusted sources
- Specify exact image versions (not
latest) - Run as non-root user
- Scan images for vulnerabilities
- Keep base images updated
- Don’t embed secrets in images
- Use read-only root filesystem when possible
- Minimize attack surface (alpine, distroless)
- Enable Docker Content Trust (image signing)
Development vs Production
Development:
FROM node:18
WORKDIR /app
COPY package*.json ./
RUN npm install # Include dev dependencies
COPY . .
CMD ["npm", "run", "dev"]
Production:
FROM node:18-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build
FROM node:18-alpine
WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production
COPY /app/dist ./dist
USER node
CMD ["node", "dist/server.js"]
Logging Best Practices
# Log to stdout/stderr (Docker captures these)
CMD ["node", "server.js"] # Good
# Don't log to files (lost when container stops)
CMD ["node", "server.js", ">", "app.log"] # Bad
// Application logging
console.log('Info message'); // stdout
console.error('Error message'); // stderr
// Use structured logging
console.log(JSON.stringify({
level: 'info',
timestamp: new Date().toISOString(),
message: 'Request processed',
requestId: '123'
}));
Environment Configuration
# Use ARG for build-time variables
ARG NODE_ENV=production
ENV NODE_ENV=$NODE_ENV
# Use ENV for runtime variables
ENV PORT=3000
ENV LOG_LEVEL=info
# Override at runtime
# docker run -e PORT=8080 -e LOG_LEVEL=debug myapp
Health Checks
HEALTHCHECK \
CMD curl -f http://localhost:3000/health || exit 1
# docker-compose.yml
services:
app:
image: myapp
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:3000/health"]
interval: 30s
timeout: 3s
retries: 3
start_period: 40s
Graceful Shutdown
// Node.js example
process.on('SIGTERM', () => {
console.log('SIGTERM received, closing server...');
server.close(() => {
console.log('Server closed');
process.exit(0);
});
});
# Use exec form to properly handle signals
CMD ["node", "server.js"] # Good
CMD node server.js # Bad (wrapped in /bin/sh, signals not forwarded)
Quick Reference
Essential Commands
# Images
docker build -t name:tag .
docker pull image:tag
docker push image:tag
docker images
docker rmi image:tag
# Containers
docker run -d --name container image
docker ps # Running containers
docker ps -a # All containers
docker stop container
docker start container
docker restart container
docker rm container
docker logs -f container
docker exec -it container /bin/sh
# Cleanup
docker system prune -a # Remove all unused resources
docker container prune # Remove stopped containers
docker image prune # Remove dangling images
docker volume prune # Remove unused volumes
# Compose
docker-compose up -d
docker-compose down
docker-compose logs -f
docker-compose exec service /bin/sh
docker-compose build
Common Flags
# docker run flags
-d # Detached (background)
-it # Interactive with TTY
-p 8080:80 # Port mapping (host:container)
--name myapp # Container name
-e VAR=value # Environment variable
-v /host:/container # Volume mount
--network name # Connect to network
--rm # Remove container on exit
-m 512m # Memory limit
--cpus 1.0 # CPU limit
Dockerfile Instructions
FROM image:tag # Base image
WORKDIR /path # Set working directory
COPY src dst # Copy files
ADD src dst # Copy (with URL/tar support)
RUN command # Execute command
ENV KEY=value # Environment variable
EXPOSE port # Document port
CMD ["executable"] # Default command
ENTRYPOINT ["exec"] # Command prefix
VOLUME /path # Create mount point
USER username # Set user
ARG name=default # Build argument
LABEL key=value # Metadata
HEALTHCHECK CMD command # Health check
Summary
Docker containerization provides:
- Consistency: Identical environments from dev to production
- Isolation: Dependencies don’t conflict between applications
- Portability: Run anywhere Docker runs (cloud, local, CI)
- Efficiency: Lightweight compared to VMs, fast startup
- Scalability: Easy horizontal scaling with orchestration
Key Workflows:
- Development: docker-compose with hot reload volumes
- CI/CD: Build, test, push images to registry
- Production: Pull images, run with resource limits and health checks
Next Steps:
- Master multi-stage builds for optimal image sizes
- Implement health checks and graceful shutdown
- Set up docker-compose for local development
- Integrate Docker into CI/CD pipelines
- Explore orchestration (Swarm or Kubernetes) for production scale