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docker-containerizationDocker containerization 部署

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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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-containerization(Docker containerization 部署)
来源仓库:https://github.com/ailabs-393/ai-labs-claude-skills
仓库路径:skills/docker-containerization
安装命令:
npx skills add https://github.com/ailabs-393/ai-labs-claude-skills --skill docker-containerization
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/ailabs-393/ai-labs-claude-skills --skill docker-containerization

简介

为现代 Web 应用生成生产级 Docker 配置,支持 Next.js 和 Node.js 项目。

  • 提供优化的 Dockerfile、docker-compose 编排、容器管理脚本及多平台部署指南。
  • 通过交互式问答明确项目类型、依赖和环境需求后输出完整配置方案。
  • 需确认目标语言栈、构建目标和运行环境,涉及生产部署时应验证镜像安全策略。
  • docker-containerization 属于运维和基础设施类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

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?

  • DevelopmentDockerfile.development (hot reload, all dependencies)
  • ProductionDockerfile.production (minimal, secure, optimized)
  • Static ExportDockerfile.nginx (smallest footprint)

2. Single or Multi-container?

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

3. Which registry?

  • Docker Hubdocker.io/username/image
  • AWS ECR123456789012.dkr.ecr.region.amazonaws.com/image
  • Google GCRgcr.io/project-id/image
  • Azure ACRregistry.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

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

26.23%
按下载量换算1,152

Codex

21.49%
按下载量换算944

OpenCode

16.69%
按下载量换算733

Gemini CLI

13.23%
按下载量换算581

Antigravity

7.29%
按下载量换算320

Cursor

3.13%
按下载量换算137

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

通过

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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。

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