Devops Deploy

DEVOPS-DEPLOY — 从想法到生产

概述

DevOps 和应用部署 — Docker、GitHub Actions CI/CD、AWS Lambda、SAM、Terraform、基础设施即代码和监控。适用于：Docker化应用、配置CI/CD流水线、AWS部署、Lambda、ECS、GitHub Actions配置、Terraform、回滚、蓝绿部署、健康检查、告警。

何时使用此技能

• 当你需要该领域的专业协助时

何时不使用此技能

• 任务与 devops deploy 无关
• 更简单、更具体的工具可以处理该请求
• 用户需要无领域专业知识的一般性协助

工作原理

"快速行动，但不破坏事物。" — 精英工程不是慢的。 它是既快速又可靠的。

优化的 Dockerfile（Python）

FROM python:3.11-slim AS builder
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir --user -r requirements.txt

FROM python:3.11-slim
WORKDIR /app
COPY --from=builder /root/.local /root/.local
COPY . .
ENV PATH=/root/.local/bin:$PATH
ENV PYTHONUNBUFFERED=1
EXPOSE 8000
HEALTHCHECK --interval=30s --timeout=3s CMD curl -f http://localhost:8000/health || exit 1
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

Docker Compose（本地开发）

version: "3.9"
services:
  app:
    build: .
    ports: ["8000:8000"]
    environment:
      - ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
    volumes:
      - .:/app
    depends_on: [db, redis]
  db:
    image: postgres:15
    environment:
      POSTGRES_DB: auri
      POSTGRES_USER: auri
      POSTGRES_PASSWORD: ${DB_PASSWORD}
    volumes:
      - pgdata:/var/lib/postgresql/data
  redis:
    image: redis:7-alpine
volumes:
  pgdata:

SAM 模板（Serverless）

## Template.Yaml

AWSTemplateFormatVersion: '2010-09-09'
Transform: AWS::Serverless-2016-10-31

Globals:
  Function:
    Timeout: 30
    Runtime: python3.11
    Environment:
      Variables:
        ANTHROPIC_API_KEY: !Ref AnthropicApiKey
        DYNAMODB_TABLE: !Ref AuriTable

Resources:
  AuriFunction:
    Type: AWS::Serverless::Function
    Properties:
      CodeUri: src/
      Handler: lambda_function.handler
      MemorySize: 512
      Policies:
        - DynamoDBCrudPolicy:
            TableName: !Ref AuriTable

  AuriTable:
    Type: AWS::DynamoDB::Table
    Properties:
      TableName: auri-users
      BillingMode: PAY_PER_REQUEST
      AttributeDefinitions:
        - AttributeName: userId
          AttributeType: S
      KeySchema:
        - AttributeName: userId
          KeyType: HASH
      TimeToLiveSpecification:
        AttributeName: ttl
        Enabled: true

部署命令

## 构建和部署

sam build
sam deploy --guided  # 首次部署
sam deploy           # 后续部署

## 快速部署（无需确认）

sam deploy --no-confirm-changeset --no-fail-on-empty-changeset

## 实时查看日志

sam logs -n AuriFunction --tail

## 删除堆栈

sam delete

.Github/Workflows/Deploy.Yml

name: Deploy Auri

on: push: branches: [main] pull_request: branches: [main]

jobs: test: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: actions/setup-python@v5 with: { python-version: "3.11" } - run: pip install -r requirements.txt - run: pytest tests/ -v --cov=src --cov-report=xml - uses: codecov/codecov-action@v4

security: runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - run: pip install bandit safety - run: bandit -r src/ -ll - run: safety check -r requirements.txt

deploy: needs: [test, security] if: github.ref == 'refs/heads/main' runs-on: ubuntu-latest steps: - uses: actions/checkout@v4 - uses: aws-actions/setup-sam@v2 - uses: aws-actions/configure-aws-credentials@v4 with: aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }} aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }} aws-region: us-east-1 - run: sam build - run: sam deploy --no-confirm-changeset - name: Notify Telegram on Success run: | curl -s -X POST "https://api.telegram.org/bot${{ secrets.TELEGRAM_BOT_TOKEN }}/sendMessage"
-d "chat_id=${{ secrets.TELEGRAM_CHAT_ID }}"
-d "text=Auri deployed successfully! Commit: ${{ github.sha }}"

---

## 健康检查端点

```python
from fastapi import FastAPI
import time, os

app = FastAPI()
START_TIME = time.time()

@app.get("/health")
async def health():
    return {
        "status": "healthy",
        "uptime_seconds": time.time() - START_TIME,
        "version": os.environ.get("APP_VERSION", "unknown"),
        "environment": os.environ.get("ENV", "production")
    }

CloudWatch 告警

import boto3

def create_error_alarm(function_name: str, sns_topic_arn: str):
    cw = boto3.client("cloudwatch")
    cw.put_metric_alarm(
        AlarmName=f"{function_name}-errors",
        MetricName="Errors",
        Namespace="AWS/Lambda",
        Dimensions=[{"Name": "FunctionName", "Value": function_name}],
        Period=300,
        EvaluationPeriods=1,
        Threshold=5,
        ComparisonOperator="GreaterThanThreshold",
        AlarmActions=[sns_topic_arn],
        TreatMissingData="notBreaching"
    )

5. 生产检查清单

• 通过 Secrets Manager 配置环境变量（绝不硬编码）
• 健康检查端点正常响应
• 结构化日志（JSON）包含 request_id
• 已配置速率限制
• CORS 限制为授权域名
• DynamoDB 已启用自动备份
• Lambda 超时设置合理（10-30秒）
• CloudWatch 告警监控错误和延迟
• 已记录回滚计划
• 上线前进行负载测试

6. 命令

最佳实践

• 提供清晰、具体的项目上下文和需求
• 在应用到生产代码前审查所有建议
• 结合其他互补技能进行全面分析

常见陷阱

• 将此技能用于其专业领域之外的任务
• 在不了解具体上下文的情况下应用建议
• 未提供足够的项目上下文以进行准确分析

局限性

• 仅当任务明确符合上述范围时使用此技能。
• 不要将输出视为环境特定验证、测试或专家审查的替代品。
• 如果缺少必需的输入、权限、安全边界或成功标准，请停下来请求澄清。