100 个 Agent Skills 盘点（五）：云服务与 DevOps

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# Agent 生成的多阶段构建 Dockerfile
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FROM node:20-alpine AS builder
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WORKDIR /app
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COPY package*.json ./
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RUN npm ci --only=production
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COPY . .
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RUN npm run build
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FROM node:20-alpine AS runner
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WORKDIR /app
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RUN addgroup --system --gid 1001 nodejs
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RUN adduser --system --uid 1001 appuser
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COPY --from=builder --chown=appuser:nodejs /app/dist ./dist
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COPY --from=builder --chown=appuser:nodejs /app/node_modules ./node_modules
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USER appuser
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EXPOSE 3000
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CMD ["node", "dist/main.js"]

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# Agent 生成的 K8s 部署配置
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apiVersion: apps/v1
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kind: Deployment
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metadata:
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  name: myapp
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  labels:
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    app: myapp
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spec:
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  replicas: 3
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  selector:
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    matchLabels:
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      app: myapp
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  template:
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    metadata:
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      labels:
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        app: myapp
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    spec:
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      containers:
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      - name: myapp
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        image: myapp:latest
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        ports:
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        - containerPort: 3000
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        resources:
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          requests:
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            memory: "256Mi"
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            cpu: "250m"
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          limits:
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            memory: "512Mi"
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            cpu: "500m"
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        livenessProbe:
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          httpGet:
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            path: /health
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            port: 3000
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          initialDelaySeconds: 30
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          periodSeconds: 10
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        readinessProbe:
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          httpGet:
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            path: /ready
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            port: 3000
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          initialDelaySeconds: 5
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          periodSeconds: 5

1
# Agent 生成的 VPC 和 EKS 配置
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module "vpc" {
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  source  = "terraform-aws-modules/vpc/aws"
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  version = "5.0.0"
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  name = "my-vpc"
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  cidr = "10.0.0.0/16"
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  azs             = ["us-east-1a", "us-east-1b", "us-east-1c"]
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  private_subnets = ["10.0.1.0/24", "10.0.2.0/24", "10.0.3.0/24"]
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  public_subnets  = ["10.0.101.0/24", "10.0.102.0/24", "10.0.103.0/24"]
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  enable_nat_gateway = true
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  single_nat_gateway = true
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  tags = {
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    Environment = "production"
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    ManagedBy   = "terraform"
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  }
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}
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module "eks" {
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  source          = "terraform-aws-modules/eks/aws"
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  version         = "19.0.0"
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  cluster_name    = "my-cluster"
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  cluster_version = "1.28"
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  vpc_id     = module.vpc.vpc_id
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  subnet_ids = module.vpc.private_subnets
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  eks_managed_node_groups = {
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    general = {
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      desired_size = 3
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      min_size     = 2
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      max_size     = 10
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      instance_types = ["t3.medium"]
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    }
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  }
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}

1
# Agent 生成的 GitHub Actions 工作流
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name: CI/CD Pipeline
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on:
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  push:
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    branches: [main]
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  pull_request:
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    branches: [main]
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jobs:
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  test:
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    runs-on: ubuntu-latest
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    strategy:
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      matrix:
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        node-version: [18, 20, 22]
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    steps:
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      - uses: actions/checkout@v4
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      - uses: actions/setup-node@v4
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        with:
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          node-version: ${{ matrix.node-version }}
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          cache: 'pnpm'
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      - run: pnpm install --frozen-lockfile
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      - run: pnpm run lint
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      - run: pnpm run type-check
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      - run: pnpm run test --coverage
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      - uses: codecov/codecov-action@v3
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  deploy:
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    needs: test
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    if: github.ref == 'refs/heads/main'
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    runs-on: ubuntu-latest
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    environment: production
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    steps:
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      - uses: actions/checkout@v4
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      - name: Deploy to production
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        run: |
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          docker build -t myapp:${{ github.sha }} .
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          docker push myregistry/myapp:${{ github.sha }}
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          kubectl set image deployment/myapp myapp=myregistry/myapp:${{ github.sha }}

1
# Agent 用 Python 分析应用日志
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import re
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from collections import Counter
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def analyze_logs(log_file):
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    error_pattern = re.compile(r'ERROR.*?(\w+Error): (.+)')
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    errors = Counter()
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    with open(log_file) as f:
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        for line in f:
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            match = error_pattern.search(line)
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            if match:
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                error_type, message = match.groups()
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                errors[f"{error_type}: {message[:50]}"] += 1
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    print("🔥 Top Errors:")
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    for error, count in errors.most_common(10):
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        print(f"  {count:5d} | {error}")

1
# Agent 生成的 Prometheus 告警规则
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groups:
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  - name: application
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    rules:
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      - alert: HighErrorRate
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        expr: |
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          sum(rate(http_requests_total{status=~"5.."}[5m]))
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          /
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          sum(rate(http_requests_total[5m]))
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          > 0.05
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        for: 5m
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        labels:
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          severity: critical
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        annotations:
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          summary: "High error rate detected"
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          description: "Error rate is {{ $value | humanizePercentage }} (threshold: 5%)"
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      - alert: HighLatency
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        expr: |
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          histogram_quantile(0.95, rate(http_request_duration_seconds_bucket[5m])) > 2
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        for: 10m
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        labels:
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          severity: warning
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        annotations:
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          summary: "High P95 latency"
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          description: "P95 latency is {{ $value }}s (threshold: 2s)"

1
// Agent 通过 MCP 调用 Cloudflare 能力
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// 部署一个 Worker 到边缘节点
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await mcp.call("cloudflare", "deploy_worker", {
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  name: "api-gateway",
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  script: `
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    export default {
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      async fetch(request, env) {
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        const url = new URL(request.url);
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        // 从 KV 读取路由配置
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        const route = await env.ROUTER_KV.get(url.pathname);
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        if (route) {
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          return fetch(route + url.pathname + url.search);
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        }
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        return new Response("Not Found", { status: 404 });
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      }
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    }
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  `,
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  bindings: [{ name: "ROUTER_KV", type: "kv_namespace" }]
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});
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// 配置 DNS 记录
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await mcp.call("cloudflare", "dns_create", {
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  zone: "example.com",
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  type: "A",
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  name: "api",
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  content: "1.2.3.4",
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  proxied: true
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});
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// 设置 WAF 安全规则
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await mcp.call("cloudflare", "firewall_rule_create", {
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  zone: "example.com",
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  expression: '(http.request.uri.path contains "/admin") and not ip.src in {10.0.0.0/8}',
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  action: "block"
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});

1
// Agent 通过 E2B 沙箱执行数据分析代码
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import { Sandbox } from "@e2b/code-interpreter";
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const sandbox = await Sandbox.create();
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// 安装依赖并执行 Python 脚本
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const result = await sandbox.runCode(`
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import pandas as pd
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import matplotlib.pyplot as plt
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# 读取数据
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df = pd.read_csv('/tmp/sales.csv')
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# 数据分析
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monthly = df.groupby('month')['revenue'].sum()
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print("月度收入汇总:")
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print(monthly.to_string())
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# 生成图表
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plt.figure(figsize=(10, 6))
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monthly.plot(kind='bar', color='#6366f1')
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plt.title('Monthly Revenue')
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plt.savefig('/tmp/chart.png', dpi=150, bbox_inches='tight')
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print("图表已保存")
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`);
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console.log(result.logs.stdout.join('\n'));
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// 读取生成的文件
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const chart = await sandbox.files.read('/tmp/chart.png');
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await sandbox.kill(); // 用完销毁，不留痕迹

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// Agent 用沙箱验证代码片段
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const sandbox = await Sandbox.create({ timeoutMs: 30000 });
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const testResult = await sandbox.runCode(`
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def fibonacci(n):
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    if n <= 1:
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        return n
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    a, b = 0, 1
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    for _ in range(2, n + 1):
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        a, b = b, a + b
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    return b
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# 测试
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for i in [10, 50, 100]:
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    print(f"fib({i}) = {fibonacci(i)}")
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`);
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console.log(testResult.logs.stdout);
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await sandbox.kill();

1
// Agent 用 Pulumi 管理多云资源
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import * as aws from "@pulumi/aws";
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import * as gcp from "@pulumi/gcp";
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// AWS 上部署主应用
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const appCluster = new aws.ecs.Cluster("app-cluster");
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const appService = new aws.ecs.Service("app-service", {
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  cluster: appCluster.arn,
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  desiredCount: 3,
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  taskDefinition: appTaskDef.arn,
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});
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// GCP 上部署数据分析
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const dataCluster = new gcp.container.Cluster("data-cluster", {
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  initialNodeCount: 3,
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  nodeConfig: {
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    machineType: "e2-standard-4",
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  },
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});
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// 跨云数据同步
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const dataSync = new aws.s3.Bucket("data-sync");
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const gcsBucket = new gcp.storage.Bucket("gcs-backup");