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AGENT SKILL

docker-containerization

docker-containerization 是面向效率工具、开发运维、软件开发的 Agent Skill,来自 ailabs-393/ai-labs-claude-skills。查看技能说明、操作步骤与使用约定,并通过原项目了解详细用法。

This skill should be used when containerizing applications with Docker, creating Dockerfiles, docker-compose configurations, or deploying containers to various platforms. Ideal for Next.js, React, Node.js applications requiring containerization for development, production, or CI/CD pipelines. Use this skill when users need Docker configurations, multi-stage builds, container orchestration, or deployment to Kubernetes, ECS, Cloud Run, etc.

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namedocker-containerization
descriptionThis skill should be used when containerizing applications with Docker, creating Dockerfiles, docker-compose configurations, or deploying containers to various platforms. Ideal for Next.js, React, Node.js applications requiring containerization for development, production, or CI/CD pipelines. Use this skill when users need Docker configurations, multi-stage builds, container orchestration, or deployment to Kubernetes, ECS, Cloud Run, etc.

Docker Containerization Skill

Overview

Generate production-ready Docker configurations for modern web applications, particularly Next.js and Node.js projects. This skill provides Dockerfiles, docker-compose setups, bash scripts for container management, and comprehensive deployment guides for various orchestration platforms.

Core Capabilities

1. Dockerfile Generation

Create optimized Dockerfiles for different environments:

Production (assets/Dockerfile.production): - Multi-stage build reducing image size by 85% - Alpine Linux base (~180MB final image) - Non-root user execution for security - Health checks and resource limits

Development (assets/Dockerfile.development): - Hot reload support - All dev dependencies included - Volume mounts for live code updates

Nginx Static (assets/Dockerfile.nginx): - Static export optimization - Nginx reverse proxy included - Smallest possible footprint

2. Docker Compose Configuration

Multi-container orchestration with assets/docker-compose.yml: - Development and production services - Network and volume management - Health checks and logging - Restart policies

3. Bash Scripts for Container Management

docker-build.sh - Build images with comprehensive options:

./docker-build.sh -e prod -t v1.0.0
./docker-build.sh -n my-app --no-cache --platform linux/amd64

docker-run.sh - Run containers with full configuration:

./docker-run.sh -i my-app -t v1.0.0 -d
./docker-run.sh -p 8080:3000 --env-file .env.production

docker-push.sh - Push to registries (Docker Hub, ECR, GCR, ACR):

./docker-push.sh -n my-app -t v1.0.0 --repo username/my-app
./docker-push.sh -r gcr.io/project --repo my-app --also-tag stable

docker-cleanup.sh - Free disk space:

./docker-cleanup.sh --all --dry-run  # Preview cleanup
./docker-cleanup.sh --containers --images  # Clean specific resources

4. Configuration Files

  • .dockerignore: Excludes unnecessary files (node_modules, .git, logs)
  • nginx.conf: Production-ready Nginx configuration with compression, caching, security headers

5. Reference Documentation

docker-best-practices.md covers: - Multi-stage builds explained - Image optimization techniques (50-85% size reduction) - Security best practices (non-root users, vulnerability scanning) - Performance optimization - Health checks and logging - Troubleshooting guide

container-orchestration.md covers deployment to: - Docker Compose (local development) - Kubernetes (enterprise scale with auto-scaling) - Amazon ECS (AWS-native orchestration) - Google Cloud Run (serverless containers) - Azure Container Instances - Digital Ocean App Platform

Includes configuration examples, commands, auto-scaling setup, and monitoring.

Workflow Decision Tree

1. What environment?

  • Development → Dockerfile.development (hot reload, all dependencies)
  • Production → Dockerfile.production (minimal, secure, optimized)
  • Static Export → Dockerfile.nginx (smallest footprint)

2. Single or Multi-container?

  • Single → Generate Dockerfile only
  • Multi → Generate docker-compose.yml (app + database, microservices)

3. Which registry?

  • Docker Hub → docker.io/username/image
  • AWS ECR → 123456789012.dkr.ecr.region.amazonaws.com/image
  • Google GCR → gcr.io/project-id/image
  • Azure ACR → registry.azurecr.io/image

4. Deployment platform?

  • Kubernetes → See references/container-orchestration.md K8s section
  • ECS → See ECS task definition examples
  • Cloud Run → See deployment commands
  • Docker Compose → Use provided compose file

5. Optimizations needed?

  • Image size → Multi-stage builds, Alpine base
  • Build speed → Layer caching, BuildKit
  • Security → Non-root user, vulnerability scanning
  • Performance → Resource limits, health checks

Usage Examples

Example 1: Containerize Next.js App for Production

User: "Containerize my Next.js app for production"

Steps: 1. Copy assets/Dockerfile.production to project root as Dockerfile 2. Copy assets/.dockerignore to project root 3. Build: ./docker-build.sh -e prod -n my-app -t v1.0.0 4. Test: ./docker-run.sh -i my-app -t v1.0.0 -p 3000:3000 -d 5. Push: ./docker-push.sh -n my-app -t v1.0.0 --repo username/my-app

Example 2: Development with Docker Compose

User: "Set up Docker Compose for local development"

Steps: 1. Copy assets/Dockerfile.development and assets/docker-compose.yml to project 2. Customize services in docker-compose.yml 3. Start: docker-compose up -d 4. Logs: docker-compose logs -f app-dev

Example 3: Deploy to Kubernetes

User: "Deploy my containerized app to Kubernetes"

Steps: 1. Build and push image to registry 2. Review references/container-orchestration.md Kubernetes section 3. Create K8s manifests (deployment, service, ingress) 4. Apply: kubectl apply -f deployment.yaml 5. Verify: kubectl get pods && kubectl logs -f deployment/app

Example 4: Deploy to AWS ECS

User: "Deploy to AWS ECS Fargate"

Steps: 1. Build and push to ECR 2. Review references/container-orchestration.md ECS section 3. Create task definition JSON 4. Register: aws ecs register-task-definition --cli-input-json file://task-def.json 5. Create service: aws ecs create-service --cluster my-cluster --service-name app --desired-count 3

Best Practices

Security

✅ Use multi-stage builds for production ✅ Run as non-root user ✅ Use specific image tags (not latest) ✅ Scan for vulnerabilities ✅ Never hardcode secrets ✅ Implement health checks

Performance

✅ Optimize layer caching order ✅ Use Alpine images (~85% smaller) ✅ Enable BuildKit for parallel builds ✅ Set resource limits ✅ Use compression

Maintainability

✅ Add comments for complex steps ✅ Use build arguments for flexibility ✅ Keep Dockerfiles DRY ✅ Version control all configs ✅ Document environment variables

Troubleshooting

Image too large (>500MB) → Use multi-stage builds, Alpine base, comprehensive .dockerignore

Build is slow → Optimize layer caching, use BuildKit, review dependencies

Container exits immediately → Check logs: docker logs container-name → Verify CMD/ENTRYPOINT, check port conflicts

Changes not reflecting → Rebuild without cache, check .dockerignore, verify volume mounts

Quick Reference

# Build
./docker-build.sh -e prod -t latest

# Run
./docker-run.sh -i app -t latest -d

# Logs
docker logs -f app

# Execute
docker exec -it app sh

# Cleanup
./docker-cleanup.sh --all --dry-run  # Preview
./docker-cleanup.sh --all            # Execute

Integration with CI/CD

GitHub Actions

- run: |
    chmod +x docker-build.sh docker-push.sh
    ./docker-build.sh -e prod -t ${{ github.sha }}
    ./docker-push.sh -n app -t ${{ github.sha }} --repo username/app

GitLab CI

build:
  script:
    - chmod +x docker-build.sh
    - ./docker-build.sh -e prod -t $CI_COMMIT_SHA

Resources

Scripts (scripts/)

Production-ready bash scripts with comprehensive features: - docker-build.sh - Build images (400+ lines, colorized output) - docker-run.sh - Run containers (400+ lines, auto conflict resolution) - docker-push.sh - Push to registries (multi-registry support) - docker-cleanup.sh - Clean resources (dry-run mode, selective cleanup)

References (references/)

Detailed documentation loaded as needed: - docker-best-practices.md - Comprehensive Docker best practices (~500 lines) - container-orchestration.md - Deployment guides for 6+ platforms (~600 lines)

Assets (assets/)

Ready-to-use templates: - Dockerfile.production - Multi-stage production Dockerfile - Dockerfile.development - Development Dockerfile - Dockerfile.nginx - Static export with Nginx - docker-compose.yml - Multi-container orchestration - .dockerignore - Optimized exclusion rules - nginx.conf - Production Nginx configuration

来源:ailabs-393/ai-labs-claude-skills · MIT 许可 · 许可原文 · MD 为来源页保存的历史版本