docker-production

Q: How do I install docker-production?

Run npx skills add https://github.com/full-stack-skills/docker-skills --skill docker-production in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/docker-production/ (personal) or .claude/skills/docker-production/ (project).

by full-stack-skillsDevOps & Cloud

Guidance for deploying Docker in production environments. Covers Docker Swarm (init, join, stack deploy, service scaling, rolling updates), Kubernetes migration (kompose conversion, Helm charts, differences), resource quotas and limits, zero-downtime deployment patterns, monitoring with cAdvisor + Prometheus + Grafana, Docker with systemd, and production hardening. Use when the user asks about production Docker, swarm, stack deploy, K8s migration, zero-downtime, container monitoring, or needs to deploy Docker in production. 使用场景：生产部署、docker swarm、docker stack、K8s迁移、零停机部署、容器监控、生产环境.

Installs: 106
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/full-stack-skills/docker-skills --skill docker-production

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads docker-production automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Docker Production — 生产环境部署

Guidance for deploying and managing Docker in production.

When to Use

ALWAYS use this skill when the user mentions:

"生产部署", "production Docker"
"docker swarm", "docker stack", "swarm cluster"
"Kubernetes migration", "kompose", "K8s"
"零停机部署", "rolling update"
"容器监控", "监控", "Prometheus"

Docker Swarm Quick Start

# Initialize cluster
docker swarm init --advertise-addr <MANAGER-IP>

# Join workers (run on worker nodes)
docker swarm join --token <TOKEN> <MANAGER-IP>:2377

# Deploy a stack
docker stack deploy -c docker-compose.yml myapp

# Manage services
docker service ls
docker service scale myapp_web=5
docker service update --image myapp:v2 myapp_web
docker service logs -f myapp_web

Swarm Compose Example

version: '3.8'
services:
  web:
    image: myapp:${TAG:-latest}
    deploy:
      replicas: 3
      update_config:
        parallelism: 1
        delay: 10s
        order: start-first
      rollback_config:
        parallelism: 1
        delay: 10s
      resources:
        limits:
          cpus: '0.5'
          memory: 512M
    ports:
      - "80:8080"

Zero-Downtime Deployment

Rolling Update Flow:

┌──────┐  ┌──────┐  ┌──────┐     Old replicas (v1)
│ v1  │  │ v1  │  │ v1  │
└──────┘  └──────┘  └──────┘

docker service update --image myapp:v2 web

Step 1: Start v2
┌──────┐  ┌──────┐  ┌──────┐  ┌──────┐
│ v1  │  │ v1  │  │ v1  │  │ v2  │    ← 1 new
└──────┘  └──────┘  └──────┘  └──────┘

Step 2: Replace one v1 with v2
┌──────┐  ┌──────┐  ┌──────┐  ┌──────┐
│ v1  │  │ v1  │  │ v2  │  │ v2  │    ← 2 new
└──────┘  └──────┘  └──────┘  └──────┘

... until all v2

Kubernetes Migration

# Convert compose to K8s
kompose convert -f docker-compose.yml

# Output:
# web-deployment.yaml
# web-service.yaml
# ...

# Apply
kubectl apply -f .

Compose	K8s
services	Deployments + Services
networks	Network Policies
volumes	PersistentVolumeClaims
deploy.replicas	Deployment.spec.replicas
secrets	Secrets

Monitoring Stack

cAdvisor + Prometheus + Grafana

# docker-compose.monitoring.yml
services:
  cadvisor:
    image: gcr.io/cadvisor/cadvisor:latest
    ports: ["8080:8080"]
    volumes:
      - /:/rootfs:ro
      - /var/run/docker.sock:/var/run/docker.sock:ro
      - /sys:/sys:ro

  prometheus:
    image: prom/prometheus:latest
    ports: ["9090:9090"]
    volumes:
      - ./prometheus.yml:/etc/prometheus/prometheus.yml

  grafana:
    image: grafana/grafana:latest
    ports: ["3000:3000"]

Workflow — 推荐部署流程

Step 1: 单机部署: compose.yml + restart: unless-stopped + systemd 守护 Step 2: Swarm 集群: docker swarm init → docker stack deploy -c compose.yml myapp Step 3: 滚动更新: docker service update --image myapp:v2 + health check + rollback Step 4: 监控接入: Prometheus + cAdvisor + Grafana 绑定额仪表盘 Step 5: K8s 迁移: kompose convert → 手动添加资源限制+健康检查 → Helm Chart

Gotchas — Common Pitfalls

Single Swarm manager: If the only manager goes down, the cluster is unresponsive. → Recovery: Use 3 or 5 managers; docker node promote <worker> to add manager; back up /var/lib/docker/swarm/ regularly.
Rolling update health check: Without health checks, updates may deploy broken containers. → Recovery: Define HEALTHCHECK in Dockerfile + service health check; use --update-failure-action rollback.
Data without volumes: Production databases MUST use volumes. Container restart = new filesystem without volumes. → Recovery: docker service create --mount type=volume,src=db_data,target=/var/lib/mysql.
Direct K8s migration: kompose is a starting point, not production-ready K8s configs. → Recovery: After kompose convert, manually add resource limits, health checks, init containers, and ConfigMap/Secret references.

Boundary — 能力边界（适用与不适用场景）

分类	场景	说明
✅ 能做	单机 Compose 生产部署	compose.yml + systemd 守护
✅ 能做	Swarm 集群管理	init/join/stack deploy/rolling update
✅ 能做	K8s 迁移方案	kompose + 手动调整 + Helm Chart
✅ 能做	生产监控搭建	Prometheus + cAdvisor + Grafana + Loki
⚠️ 需条件	多数据中心 Swarm	需 overlay 网络 + 低延迟连接
⚠️ 需条件	零停机迁移 K8s	需蓝绿/金丝雀发布策略
❌ 超范围	应用代码部署	各语言 CI/CD 管道
❌ 超范围	K8s 集群搭建	使用 K8s 官方文档
❌ 超范围	数据库高可用	DBA 专业领域 + 数据库原生方案

When NOT to Use

❌ Skip	✅ Use Instead
Development/debugging	`docker-run`
Single-container apps	`docker-run` + systemd
K8s-native from start	Skip Swarm, use K8s directly
Docker basics	`docker-basics`

Security & Stability

Rotate Swarm join tokens regularly. Leaked worker tokens allow unauthorized node joining.
Use Docker Secrets for all sensitive configuration in production stacks.
Enable TLS for Docker daemon in production (tlsverify mode).
Implement resource limits on all production services to prevent noisy-neighbor issues.
Back up Swarm raft data regularly: /var/lib/docker/swarm/.
Monitor node health and set up alerts for node failures.

📚 官方文档参考

文档	地址
Docker Swarm	https://docs.docker.com/engine/swarm/
Docker Stack	https://docs.docker.com/engine/swarm/stack-deploy/
管理指南	https://docs.docker.com/admin/
生产环境 Compose	https://docs.docker.com/compose/production/
安全部署	https://docs.docker.com/engine/security/
Docker 引擎	https://docs.docker.com/engine/

🧭 Docker Skills Journey

📍 You are here: docker-production — 生产部署

← Previous: docker-cicd | → Next: docker-troubleshooting

FAQ

Q1: 如何快速上手此技能？ A: 参考上方的快速开始章节，按步骤操作即可。

Q2: 遇到版本不兼容问题怎么办？ A: 检查依赖版本，使用 lock 文件锁定，参考常见陷阱章节。

Q3: 如何在生产环境使用？ A: 参考最佳实践章节，确保配置正确，做好监控和日志。

Q4: 性能如何优化？ A: 参考性能优化相关文档，使用缓存、索引等手段。

Q5: 如何贡献或反馈问题？ A: 在 GitHub 仓库提交 Issue 或 Pull Request。

Q6: 是否支持中文？ A: 支持中文文档和中文注释，详见国内适配章节。

FAQ

What does the docker-production skill do?

How do I install docker-production?

Run npx skills add https://github.com/full-stack-skills/docker-skills --skill docker-production in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/docker-production/ (personal) or .claude/skills/docker-production/ (project).

Which AI agents can use docker-production?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is docker-production safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains docker-production?

It is published by full-stack-skills in full-stack-skills/docker-skills. It has 106 recorded installs.