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devops-automation开发运营自动化

Agent Skill

用于辅助云资源、部署、容器、基础设施和运维自动化任务。它适合让 Agent 检查配置、整理部署步骤、分析资源状态、生成排障思路或辅助云服务接入。使用时需要明确目标环境、账号权限、区域和资源组,区分本地测试与生产操作;涉及删除资源、重启服务、修改网络或权限配置时,应先确认影响范围。

总安装

1,979

周安装

85

GitHub Stars

1,495

下载量

694
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:devops-automation(开发运营自动化)
来源仓库:https://github.com/rohitg00/awesome-claude-code-toolkit
仓库路径:skills/devops-automation
安装命令:
npx skills add https://github.com/rohitg00/awesome-claude-code-toolkit --skill devops-automation
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/rohitg00/awesome-claude-code-toolkit --skill devops-automation

简介

用于辅助云资源和部署任务。devops-automation 属于开发类 Skill,可作为该场景下的辅助能力补充。

  • 适合检查配置、分析资源状态或生成排障思路。
  • 可整理部署步骤但需区分测试与生产环境。
  • 涉及删除资源时应先确认影响范围。
  • 使用前需明确账号权限和资源组。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

DevOps Automation

GitHub Actions Workflow Structure

name: CI/CD
on:
  push:
    branches: [main]
  pull_request:
    branches: [main]

concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true

jobs:
  lint:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with:
          node-version: 22
          cache: 'npm'
      - run: npm ci
      - run: npm run lint

  test:
    runs-on: ubuntu-latest
    needs: lint
    strategy:
      matrix:
        node-version: [20, 22]
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with:
          node-version: ${{ matrix.node-version }}
          cache: 'npm'
      - run: npm ci
      - run: npm test -- --coverage
      - uses: actions/upload-artifact@v4
        with:
          name: coverage-${{ matrix.node-version }}
          path: coverage/

  deploy:
    runs-on: ubuntu-latest
    needs: test
    if: github.ref == 'refs/heads/main'
    environment: production
    steps:
      - uses: actions/checkout@v4
      - run: ./deploy.sh

Key patterns:

  • Use concurrency to cancel outdated runs
  • Cache dependencies with setup action's cache option
  • Use needs for job dependencies
  • Gate deploys with environment protection rules
  • Use matrix for cross-version testing

Docker Multi-Stage Builds

FROM node:22-alpine AS deps
WORKDIR /app
COPY package.json package-lock.json ./
RUN npm ci --production

FROM node:22-alpine AS builder
WORKDIR /app
COPY package.json package-lock.json ./
RUN npm ci
COPY . .
RUN npm run build

FROM node:22-alpine AS runner
WORKDIR /app
RUN addgroup -g 1001 appgroup && adduser -u 1001 -G appgroup -S appuser
COPY --from=deps /app/node_modules ./node_modules
COPY --from=builder /app/dist ./dist
COPY --from=builder /app/package.json ./
USER appuser
EXPOSE 3000
HEALTHCHECK --interval=30s --timeout=3s CMD wget -qO- http://localhost:3000/health || exit 1
CMD ["node", "dist/server.js"]

Rules:

  • Use specific image tags, never latest
  • Run as non-root user
  • Copy only necessary files into final stage
  • Add HEALTHCHECK for orchestrator integration
  • Use .dockerignore to exclude node_modules, .git, tests

Kubernetes Deployment Manifest

apiVersion: apps/v1
kind: Deployment
metadata:
  name: api-server
  labels:
    app: api-server
spec:
  replicas: 3
  selector:
    matchLabels:
      app: api-server
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
  template:
    metadata:
      labels:
        app: api-server
    spec:
      containers:
        - name: api
          image: registry.example.com/api:v1.2.3
          ports:
            - containerPort: 3000
          resources:
            requests:
              cpu: 100m
              memory: 128Mi
            limits:
              cpu: 500m
              memory: 512Mi
          readinessProbe:
            httpGet:
              path: /health
              port: 3000
            initialDelaySeconds: 5
            periodSeconds: 10
          livenessProbe:
            httpGet:
              path: /health
              port: 3000
            initialDelaySeconds: 15
            periodSeconds: 20
          env:
            - name: DATABASE_URL
              valueFrom:
                secretKeyRef:
                  name: api-secrets
                  key: database-url

Always set resource requests and limits. Always define readiness and liveness probes. Use maxUnavailable: 0 for zero-downtime deploys.

Helm Chart Structure

chart/
  Chart.yaml
  values.yaml
  values-staging.yaml
  values-production.yaml
  templates/
    deployment.yaml
    service.yaml
    ingress.yaml
    hpa.yaml
    _helpers.tpl
# values.yaml
replicaCount: 2
image:
  repository: registry.example.com/api
  tag: latest
  pullPolicy: IfNotPresent
resources:
  requests:
    cpu: 100m
    memory: 128Mi
  limits:
    cpu: 500m
    memory: 512Mi
ingress:
  enabled: true
  host: api.example.com
autoscaling:
  enabled: true
  minReplicas: 2
  maxReplicas: 10
  targetCPUUtilization: 70

Use values-{env}.yaml overrides per environment. Lint charts with helm lint. Test with helm template before deploying.

ArgoCD GitOps Pattern

apiVersion: argoproj.io/v1alpha1
kind: Application
metadata:
  name: api-server
  namespace: argocd
spec:
  project: default
  source:
    repoURL: https://github.com/org/k8s-manifests
    targetRevision: main
    path: apps/api-server
  destination:
    server: https://kubernetes.default.svc
    namespace: production
  syncPolicy:
    automated:
      prune: true
      selfHeal: true
    syncOptions:
      - CreateNamespace=true

GitOps principles:

  • Git is the single source of truth for cluster state
  • All changes go through PRs (no kubectl apply in production)
  • ArgoCD auto-syncs from Git to cluster
  • Enable selfHeal to revert manual cluster changes
  • Separate app code repos from deployment manifest repos

Monitoring Stack

# Prometheus ServiceMonitor
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
  name: api-server
spec:
  selector:
    matchLabels:
      app: api-server
  endpoints:
    - port: metrics
      interval: 15s
      path: /metrics

Key metrics to expose:

  • http_request_duration_seconds (histogram) - request latency by route and status
  • http_requests_total (counter) - request count by route and status
  • process_resident_memory_bytes (gauge) - memory usage
  • db_query_duration_seconds (histogram) - database query latency

Alert on: error rate >1%, P99 latency >2s, memory >80% of limit, pod restarts >3 in 10 minutes.

Pipeline Best Practices

  1. Keep CI under 10 minutes (parallelize jobs, cache aggressively)
  2. Run linting and type checking before tests
  3. Use ephemeral environments for PR previews
  4. Pin all action versions to SHA, not tags
  5. Store secrets in GitHub Secrets, never in workflow files
  6. Use OIDC for cloud provider authentication (no long-lived keys)
  7. Tag images with git SHA, not latest
  8. Run security scans (Trivy, Snyk) on container images in CI

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.36%
按下载量换算245

Claude

32.65%
按下载量换算227

Cursor

20.13%
按下载量换算140

Gemini CLI

9.16%
按下载量换算64

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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