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基于Docker的CI/CD流水线构建：从代码提交到生产部署的自动化流程

StaleArthur
StaleArthur 2026-02-07T06:17:10+08:00
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引言

在现代软件开发中，持续集成和持续部署（CI/CD）已成为提高开发效率、保证软件质量的重要手段。随着容器化技术的普及，基于Docker的CI/CD流水线成为了业界标准实践。本文将详细介绍如何构建一个完整的CI/CD流水线，涵盖从代码提交到生产部署的全过程自动化。

什么是CI/CD

CI/CD（Continuous Integration/Continuous Deployment）是现代软件开发中的核心实践：

  • 持续集成：开发者频繁地将代码变更合并到主分支，并通过自动化的测试确保代码质量
  • 持续部署：代码通过测试后自动部署到生产环境，实现快速交付

Docker在CI/CD中的作用

Docker作为容器化技术的代表，在CI/CD流程中发挥着关键作用：

优势分析

  1. 环境一致性：开发、测试、生产环境完全一致，避免"在我机器上能运行"的问题
  2. 快速部署：容器启动快，资源占用少
  3. 可移植性：一次构建，多处运行
  4. 版本控制：镜像可以版本化管理

Docker在CI/CD流程中的应用场景

  • 构建应用镜像
  • 运行测试用例
  • 部署应用到不同环境
  • 环境隔离和资源管理

技术栈选择

核心工具

  • Docker：容器化平台
  • Jenkins：CI/CD服务器
  • GitLab/GitHub：代码仓库
  • Docker Registry：镜像仓库
  • Kubernetes（可选）：容器编排

构建基础环境

1. 环境准备

首先需要准备一个基础的开发环境：

# 安装Docker
curl -fsSL https://get.docker.com -o get-docker.sh
sh get-docker.sh

# 验证安装
docker --version
docker run hello-world

# 安装Docker Compose
sudo curl -L "https://github.com/docker/compose/releases/download/v2.20.0/docker-compose-$(uname -s)-$(uname -m)" -o /usr/local/bin/docker-compose
sudo chmod +x /usr/local/bin/docker-compose

2. 创建项目结构

mkdir myapp-cicd
cd myapp-cicd
mkdir src
touch Dockerfile
touch docker-compose.yml

应用代码示例

1. 简单的Node.js应用

创建一个简单的Web应用作为示例：

src/app.js

const express = require('express');
const app = express();
const port = process.env.PORT || 3000;

app.get('/', (req, res) => {
  res.json({
    message: 'Hello CI/CD World!',
    timestamp: new Date().toISOString(),
    environment: process.env.NODE_ENV || 'development'
  });
});

app.get('/health', (req, res) => {
  res.status(200).json({ status: 'OK' });
});

app.listen(port, () => {
  console.log(`App listening at http://localhost:${port}`);
});

src/package.json

{
  "name": "myapp",
  "version": "1.0.0",
  "description": "Sample CI/CD application",
  "main": "app.js",
  "scripts": {
    "start": "node app.js",
    "test": "jest"
  },
  "dependencies": {
    "express": "^4.18.2"
  },
  "devDependencies": {
    "jest": "^29.5.0"
  }
}

Dockerfile构建

1. 基础Dockerfile

Dockerfile

# 使用官方Node.js运行时作为基础镜像
FROM node:18-alpine

# 设置工作目录
WORKDIR /app

# 复制package.json和package-lock.json
COPY package*.json ./

# 安装依赖
RUN npm ci --only=production

# 复制应用代码
COPY . .

# 暴露端口
EXPOSE 3000

# 创建非root用户
RUN addgroup -g 1001 -S nodejs && \
    adduser -S nextjs -u 1001

USER nextjs

# 启动应用
CMD ["npm", "start"]

2. 多阶段构建优化

Dockerfile.prod

# 构建阶段
FROM node:18-alpine AS builder

WORKDIR /app
COPY package*.json ./
RUN npm ci --only=production

# 生产阶段
FROM node:18-alpine AS production

WORKDIR /app

# 从构建阶段复制依赖
COPY --from=builder /app/node_modules ./node_modules
COPY . .

EXPOSE 3000

# 使用非root用户运行
RUN addgroup -g 1001 -S nodejs && \
    adduser -S nextjs -u 1001

USER nextjs

CMD ["npm", "start"]

Jenkins CI/CD流水线配置

1. Jenkins安装和配置

# 安装Jenkins
docker run -d \
  --name jenkins \
  --publish 8080:8080 \
  --publish 50000:50000 \
  --volume jenkins_home:/var/jenkins_home \
  jenkins/jenkins:lts

# 访问Jenkins：http://localhost:8080

2. Jenkins Pipeline脚本

Jenkinsfile

pipeline {
    agent any
    
    environment {
        DOCKER_REGISTRY = 'your-registry.com'
        IMAGE_NAME = 'myapp'
        IMAGE_TAG = "${env.BUILD_NUMBER}"
        DOCKER_IMAGE = "${DOCKER_REGISTRY}/${IMAGE_NAME}:${IMAGE_TAG}"
        DOCKER_IMAGE_LATEST = "${DOCKER_REGISTRY}/${IMAGE_NAME}:latest"
    }
    
    stages {
        stage('Checkout') {
            steps {
                git branch: 'main', url: 'https://github.com/yourusername/myapp.git'
            }
        }
        
        stage('Build') {
            steps {
                script {
                    echo "Building Docker image..."
                    sh "docker build -t ${DOCKER_IMAGE} -f Dockerfile.prod ."
                    sh "docker tag ${DOCKER_IMAGE} ${DOCKER_IMAGE_LATEST}"
                }
            }
        }
        
        stage('Test') {
            steps {
                script {
                    echo "Running tests..."
                    sh "docker run --rm ${DOCKER_IMAGE} npm test"
                }
            }
        }
        
        stage('Push') {
            steps {
                script {
                    echo "Pushing image to registry..."
                    withCredentials([usernamePassword(credentialsId: 'docker-registry', 
                                                    usernameVariable: 'DOCKER_USERNAME', 
                                                    passwordVariable: 'DOCKER_PASSWORD')]) {
                        sh "docker login -u ${DOCKER_USERNAME} -p ${DOCKER_PASSWORD} ${DOCKER_REGISTRY}"
                        sh "docker push ${DOCKER_IMAGE}"
                        sh "docker push ${DOCKER_IMAGE_LATEST}"
                    }
                }
            }
        }
        
        stage('Deploy') {
            steps {
                script {
                    echo "Deploying to staging..."
                    // 这里可以集成到Kubernetes或其他部署工具
                    withCredentials([file(credentialsId: 'kubeconfig', 
                                        variable: 'KUBECONFIG')]) {
                        sh "kubectl set image deployment/myapp-deployment myapp=${DOCKER_IMAGE}"
                    }
                }
            }
        }
    }
    
    post {
        success {
            echo "Pipeline completed successfully!"
            slackSend channel: '#deployments', message: "✅ Build ${env.BUILD_NUMBER} succeeded for ${env.JOB_NAME}"
        }
        failure {
            echo "Pipeline failed!"
            slackSend channel: '#deployments', message: "❌ Build ${env.BUILD_NUMBER} failed for ${env.JOB_NAME}"
        }
    }
}

GitLab CI/CD配置

1. .gitlab-ci.yml配置文件

# 定义变量
variables:
  DOCKER_REGISTRY: "your-registry.com"
  IMAGE_NAME: "myapp"
  DOCKER_IMAGE: "$DOCKER_REGISTRY/$IMAGE_NAME:$CI_COMMIT_SHORT_SHA"
  DOCKER_IMAGE_LATEST: "$DOCKER_REGISTRY/$IMAGE_NAME:latest"

# 定义阶段
stages:
  - build
  - test
  - deploy

# 构建阶段
build:
  stage: build
  image: docker:latest
  services:
    - docker:dind
  before_script:
    - docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY
  script:
    - echo "Building Docker image..."
    - docker build -t $DOCKER_IMAGE -f Dockerfile.prod .
    - docker tag $DOCKER_IMAGE $DOCKER_IMAGE_LATEST
    - echo "Pushing to registry..."
    - docker push $DOCKER_IMAGE
    - docker push $DOCKER_IMAGE_LATEST
  only:
    - main

# 测试阶段
test:
  stage: test
  image: $DOCKER_IMAGE
  script:
    - echo "Running tests..."
    - npm test
  only:
    - main

# 部署阶段
deploy:
  stage: deploy
  image: bitnami/kubectl:latest
  script:
    - echo "Deploying to Kubernetes..."
    - kubectl set image deployment/myapp-deployment myapp=$DOCKER_IMAGE
  environment:
    name: production
    url: https://myapp.example.com
  only:
    - main

Docker Compose部署配置

1. 开发环境配置

docker-compose.yml

version: '3.8'

services:
  app:
    build: .
    ports:
      - "3000:3000"
    environment:
      - NODE_ENV=development
      - PORT=3000
    volumes:
      - .:/app
      - /app/node_modules
    depends_on:
      - redis
    networks:
      - app-network

  redis:
    image: redis:alpine
    ports:
      - "6379:6379"
    networks:
      - app-network

networks:
  app-network:
    driver: bridge

2. 生产环境配置

docker-compose.prod.yml

version: '3.8'

services:
  app:
    image: your-registry.com/myapp:latest
    ports:
      - "3000:3000"
    environment:
      - NODE_ENV=production
      - PORT=3000
    restart: unless-stopped
    networks:
      - app-network

  nginx:
    image: nginx:alpine
    ports:
      - "80:80"
      - "443:443"
    volumes:
      - ./nginx.conf:/etc/nginx/nginx.conf
    depends_on:
      - app
    networks:
      - app-network

networks:
  app-network:
    driver: bridge

安全最佳实践

1. Docker镜像安全

# 使用最小基础镜像
FROM alpine:latest

# 避免使用root用户
RUN adduser -D -s /bin/sh appuser
USER appuser

# 清理不必要的包
RUN apk --no-cache add nodejs npm && \
    rm -rf /var/cache/apk/*

# 设置安全权限
RUN chmod 600 /app/config.json

2. 密钥管理

# GitLab CI中使用密钥
deploy:
  stage: deploy
  script:
    - |
      if [ "$CI_COMMIT_BRANCH" = "main" ]; then
        echo "Deploying to production..."
        # 使用GitLab的密钥管理
        kubectl create secret generic app-secrets \
          --from-literal=database-password=$DB_PASSWORD \
          --from-literal=api-key=$API_KEY
      fi

监控和日志

1. 日志收集配置

docker-compose.logging.yml

version: '3.8'

services:
  app:
    image: your-registry.com/myapp:latest
    logging:
      driver: "json-file"
      options:
        max-size: "10m"
        max-file: "3"
    environment:
      - NODE_ENV=production
    networks:
      - app-network

  fluentd:
    image: fluent/fluentd:v1.14-debian-1
    ports:
      - "24224:24224"
    volumes:
      - ./fluentd.conf:/fluentd/etc/fluent.conf
    networks:
      - app-network

networks:
  app-network:
    driver: bridge

2. 健康检查

# 在Dockerfile中添加健康检查
HEALTHCHECK --interval=30s --timeout=30s --start-period=5s --retries=3 \
  CMD curl -f http://localhost:3000/health || exit 1

性能优化策略

1. 镜像层缓存优化

# 最佳实践：利用Docker层缓存
FROM node:18-alpine

WORKDIR /app

# 先复制package文件，利用层缓存
COPY package*.json ./

# 安装依赖（如果package.json未改变，会使用缓存）
RUN npm ci --only=production && \
    npm cache clean --force

# 复制应用代码
COPY . .

# 暴露端口
EXPOSE 3000

# 启动命令
CMD ["npm", "start"]

2. 并行构建优化

stage('Parallel Build') {
    steps {
        script {
            parallel {
                stage('Build Frontend') {
                    steps {
                        sh 'docker build -t frontend:latest -f Dockerfile.frontend .'
                    }
                }
                stage('Build Backend') {
                    steps {
                        sh 'docker build -t backend:latest -f Dockerfile.backend .'
                    }
                }
            }
        }
    }
}

部署策略

1. 蓝绿部署

# 蓝绿部署配置
version: '3.8'

services:
  app-blue:
    image: your-registry.com/myapp:${BUILD_NUMBER}
    environment:
      - ENV=blue
    labels:
      - "traefik.http.routers.app-blue.rule=Host(`app.example.com`)"
      - "traefik.http.services.app-blue.loadbalancer.server.port=3000"

  app-green:
    image: your-registry.com/myapp:${BUILD_NUMBER}
    environment:
      - ENV=green
    labels:
      - "traefik.http.routers.app-green.rule=Host(`app.example.com`)"
      - "traefik.http.services.app-green.loadbalancer.server.port=3000"

2. 滚动更新

# Kubernetes滚动更新配置
apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp-deployment
spec:
  replicas: 3
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
  selector:
    matchLabels:
      app: myapp
  template:
    metadata:
      labels:
        app: myapp
    spec:
      containers:
      - name: myapp
        image: your-registry.com/myapp:${BUILD_NUMBER}
        ports:
        - containerPort: 3000

故障恢复和回滚

1. 自动化回滚脚本

#!/bin/bash
# rollback.sh

echo "Starting rollback process..."

# 获取当前部署的镜像版本
CURRENT_VERSION=$(kubectl get deployment myapp-deployment -o jsonpath='{.spec.template.spec.containers[0].image}')
echo "Current version: $CURRENT_VERSION"

# 回滚到上一个版本（这里简化处理）
if [[ $CURRENT_VERSION == *"latest"* ]]; then
    echo "Rolling back to previous version..."
    # 实际应用中需要更复杂的逻辑来获取历史版本
    kubectl rollout undo deployment/myapp-deployment
else
    echo "No rollback needed"
fi

echo "Rollback completed."

2. 监控告警配置

# Prometheus监控配置
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  name: myapp-monitor
spec:
  selector:
    matchLabels:
      app: myapp
  endpoints:
  - port: http
    path: /metrics
    interval: 30s

总结

通过本文的详细介绍，我们构建了一个完整的基于Docker的CI/CD流水线。这个流程涵盖了从代码提交到生产部署的全过程：

  1. 代码管理：使用Git进行版本控制
  2. 自动化构建：Docker容器化应用
  3. 持续测试：集成测试验证
  4. 安全部署：镜像安全和密钥管理
  5. 监控告警：实时监控和故障处理

最佳实践建议

  1. 环境一致性：确保所有环境使用相同的Docker镜像
  2. 安全优先：定期更新基础镜像，使用最小权限原则
  3. 性能优化：合理利用Docker缓存，优化镜像大小
  4. 监控完善：建立完整的日志和指标收集体系
  5. 文档化：详细记录CI/CD流程和配置

这个CI/CD流水线可以根据具体需求进行扩展和定制，为团队提供高效的持续交付能力。通过自动化流程，可以显著提高开发效率，减少人为错误，确保软件质量。

# Docker # DevOps # CICD
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