🐳 每个开发人员都应该知道的 10 个 Docker 最佳实践 - 附示例！

由于容器化在现代开发中变得至关重要，以下是实际实现的基本 Docker 实践：

使用多阶段构建

# Build stage
FROM node:16 AS builder
WORKDIR /app
COPY package*.json ./
RUN npm install
COPY . .
RUN npm run build

# Production stage
FROM node:16-slim
COPY --from=builder /app/dist /app
EXPOSE 3000
CMD ["node", "app"]

结果：生产图像尺寸减少了高达 90％！

利用 .dockerignore

node_modules
npm-debug.log
Dockerfile
.git
.env
*.md

通过排除不必要的文件来保持您的构建清洁和安全。

选择特定的基础图像标签

# ❌ Bad practice
FROM node:latest

# ✅ Good practice
FROM node:16.17.0-alpine3.16

确保跨环境的一致性并防止意外中断。

一个容器，一个进程

# ✅ Good practice
FROM nginx:alpine
COPY ./web-app /usr/share/nginx/html
# Single process: nginx
CMD ["nginx", "-g", "daemon off;"]

优化层缓存

# ✅ Good practice
COPY package.json package-lock.json ./
RUN npm install
# Source code changes don't trigger node_modules reinstall
COPY . .

使用非 root 用户

FROM node:16-alpine
# Create app directory and user
RUN mkdir /app && addgroup -S appgroup && adduser -S appuser -G appgroup
WORKDIR /app
# Switch to non-root user
USER appuser
COPY --chown=appuser:appgroup . .

扫描漏洞

# Using Trivy in CI/CD
trivy image your-image:tag

在您的管道中设置自动扫描以确保持续的安全。

保持图像最少

# ✅ Good practice: Using alpine
FROM python:3.9-alpine
RUN apk add --no-cache postgresql-libs
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

明智地缓存依赖项

# ✅ Good practice
COPY package.json yarn.lock ./
RUN yarn install --frozen-lockfile
COPY . .

设置资源限制

# Docker run with limits
docker run -d \
  --name myapp \
  --memory="512m" \
  --cpus="1.0" \
  your-image:tag

Docker Compose 版本：

services:
  web:
    image: your-image:tag
    deploy:
      resources:
        limits:
          cpus: '1.0'
          memory: 512M

🔍 福利：环境变量最佳实践

# ❌ Bad practice: Hardcoding
ENV API_KEY=1234567890

# ✅ Good practice: Using ARG for build-time variables
ARG BUILD_VERSION
ENV APP_VERSION=$BUILD_VERSION

# ✅ Better practice: Using docker-compose.yml
# docker-compose.yml
services:
  app:
    env_file:
      - .env.production

💡 专业提示：始终为你的 Docker 设置维护清晰的文档：

# Service Name
## Build
`docker build -t service-name .`

## Run
`docker run -p 3000:3000 service-name`

## Environment Variables
- `PORT`: Application port (default: 3000)
- `NODE_ENV`: Runtime environment

## Resource Requirements
- Memory: 512MB minimum
- CPU: 1 core recommended

哪些 Docker 实践改善了您的开发工作流程？在下面分享您的经验！

CLIS.CC

🐳 每个开发人员都应该知道的 10 个 Docker 最佳实践 - 附示例！