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dockerDocker 容器开发

Agent Skill

用于辅助云资源、部署、容器、基础设施和运维自动化任务。它适合让 Agent 检查配置、整理部署步骤、分析资源状态、生成排障思路或辅助云服务接入。使用时需要明确目标环境、账号权限、区域和资源组,区分本地测试与生产操作;涉及删除资源、重启服务、修改网络或权限配置时,应先确认影响范围。

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:docker(Docker 容器开发)
来源仓库:https://github.com/bobmatnyc/claude-mpm-skills
仓库路径:skills/docker
安装命令:
npx skills add https://github.com/bobmatnyc/claude-mpm-skills --skill docker
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/bobmatnyc/claude-mpm-skills --skill docker

简介

使用隔离的便携式单元对应用程序进行容器化,确保开发、测试和生产的一致性。

  • 支持三个核心工作流程:具有热重载卷的本地开发、CI/CD 映像构建和测试以及具有运行状况检查和资源限制的生产部署
  • 包括用于优化图像大小的多阶段构建、层缓存策略和用于更快构建的 .dockerignore 模式
  • Docker Compose 在单个 YAML 文件中启用具有服务依赖关系、网络和卷管理的多容器应用程序
  • 涵盖 Node.js、Python、TypeScript 和 Go 的框架特定模式,以及安全最佳实践,包括非 root 用户、最小基础映像和秘密管理
  • 提供调试工具(日志、执行、检查、统计)以及端口冲突、权限错误和性能瓶颈等常见问题的故障排除指南

SKILL.md

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 --from=builder /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 --from=builder /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 --from=builder /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 --interval=30s --timeout=5s --start-period=10s --retries=3 \
  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 --chown=appuser:appuser . .

# 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 --from=deps /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 --from=builder /app/public ./public
COPY --from=builder --chown=nextjs:nodejs /app/.next/standalone ./
COPY --from=builder --chown=nextjs:nodejs /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 --from=builder /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

FeatureDocker ComposeDocker SwarmKubernetes
ComplexityLowMediumHigh
Use CaseLocal devSmall clustersProduction at scale
SetupSingle fileBuilt-inSeparate installation
ScalingManualAutomaticAutomatic + Advanced
HANoYesYes
EcosystemLimitedDockerMassive

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.yml runs mcp-server with a port range 8875-8895 and optional chrome profile.
  • 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) and tools (dev tools container).

mcp-browser Dockerfile.dev

  • ARG PYTHON_VERSION=3.11, install watchdog + 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/venv and python:3.11-slim.
  • Runtime installs curl for healthcheck, sets PYTHONPATH=/app.
  • Uses non-root user and CMD ["python", "run_api_server.py"] with /health check.

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

  1. Order by Change Frequency: Least frequently changed first
  2. Combine RUN Commands: Reduce layers
  3. 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

  1. Use Alpine Images: 5MB vs 100MB+ for full Linux
  2. Multi-Stage Builds: Exclude build tools from final image
  3. Remove Unnecessary Files: Docs, examples, tests
  4. 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 --from=builder /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 --interval=30s --timeout=3s --start-period=40s --retries=3 \
  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:

  1. Development: docker-compose with hot reload volumes
  2. CI/CD: Build, test, push images to registry
  3. 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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

27.77%
按下载量换算1,629

OpenCode

26.61%
按下载量换算1,561

Gemini CLI

17.89%
按下载量换算1,050

Antigravity

13.16%
按下载量换算772

Codex

8.58%
按下载量换算503

Cursor

3.78%
按下载量换算222

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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