Agent skill

devops-cloud

Quellcode ansehen: travisjneuman/.claude

#201Globales Ranking · von 201 SkillsCritical

Installation

npx skills add travisjneuman/.claude --skill devops-cloud

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DevOps & Cloud Infrastructure

Comprehensive guide for cloud platforms, infrastructure as code, and DevOps practices.

Cloud Platforms

AWS (Amazon Web Services)

Compute:

# EC2 Instance Types
General Purpose: t3, m6i, m7g (ARM)
Compute Optimized: c6i, c7g
Memory Optimized: r6i, x2idn
Storage Optimized: i3, d3

# Auto Scaling
aws autoscaling create-auto-scaling-group \
  --auto-scaling-group-name my-asg \
  --launch-template LaunchTemplateId=lt-xxx \
  --min-size 1 --max-size 10 --desired-capacity 2 \
  --vpc-zone-identifier "subnet-xxx,subnet-yyy"

Serverless:

// Lambda with TypeScript
import { APIGatewayProxyHandler } from "aws-lambda";

export const handler: APIGatewayProxyHandler = async (event) => {
  return {
    statusCode: 200,
    body: JSON.stringify({ message: "Success" }),
  };
};

Storage:

Service Use Case Durability
S3 Object storage 99.999999999%
EBS Block storage (EC2) 99.999%
EFS Shared file system 99.999999999%
FSx Windows/Lustre 99.999999999%

GCP (Google Cloud Platform)

Key Services:

# GKE cluster
gcloud container clusters create my-cluster \
  --zone us-central1-a \
  --num-nodes 3 \
  --machine-type e2-medium \
  --enable-autoscaling --min-nodes 1 --max-nodes 10

# Cloud Run (serverless containers)
gcloud run deploy my-service \
  --image gcr.io/project/image:tag \
  --platform managed \
  --region us-central1 \
  --allow-unauthenticated

Azure

Key Services:

# AKS cluster
az aks create \
  --resource-group myRG \
  --name myAKS \
  --node-count 3 \
  --enable-addons monitoring \
  --generate-ssh-keys

# Azure Functions
func init MyFunctionApp --typescript
func new --name HttpTrigger --template "HTTP trigger"

Kubernetes

Core Concepts

# Deployment
apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-app
  labels:
    app: my-app
spec:
  replicas: 3
  selector:
    matchLabels:
      app: my-app
  template:
    metadata:
      labels:
        app: my-app
    spec:
      containers:
        - name: my-app
          image: my-app:1.0.0
          ports:
            - containerPort: 8080
          resources:
            requests:
              memory: "128Mi"
              cpu: "250m"
            limits:
              memory: "256Mi"
              cpu: "500m"
          livenessProbe:
            httpGet:
              path: /health
              port: 8080
            initialDelaySeconds: 30
            periodSeconds: 10
          readinessProbe:
            httpGet:
              path: /ready
              port: 8080
            initialDelaySeconds: 5
            periodSeconds: 5

Service Types

# ClusterIP (internal)
apiVersion: v1
kind: Service
metadata:
  name: my-service
spec:
  type: ClusterIP
  selector:
    app: my-app
  ports:
    - port: 80
      targetPort: 8080

---
# LoadBalancer (external)
apiVersion: v1
kind: Service
metadata:
  name: my-service-lb
spec:
  type: LoadBalancer
  selector:
    app: my-app
  ports:
    - port: 80
      targetPort: 8080

Ingress with TLS

apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: my-ingress
  annotations:
    kubernetes.io/ingress.class: nginx
    cert-manager.io/cluster-issuer: letsencrypt-prod
spec:
  tls:
    - hosts:
        - app.example.com
      secretName: app-tls
  rules:
    - host: app.example.com
      http:
        paths:
          - path: /
            pathType: Prefix
            backend:
              service:
                name: my-service
                port:
                  number: 80

Helm Charts

# values.yaml
replicaCount: 3
image:
  repository: my-app
  tag: "1.0.0"
  pullPolicy: IfNotPresent
service:
  type: ClusterIP
  port: 80
ingress:
  enabled: true
  hosts:
    - host: app.example.com
      paths: ["/"]
resources:
  limits:
    cpu: 500m
    memory: 256Mi
  requests:
    cpu: 250m
    memory: 128Mi

Terraform

AWS Infrastructure

# main.tf
terraform {
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
  }

  backend "s3" {
    bucket = "my-terraform-state"
    key    = "prod/terraform.tfstate"
    region = "us-east-1"
  }
}

provider "aws" {
  region = var.aws_region
}

# VPC
module "vpc" {
  source  = "terraform-aws-modules/vpc/aws"
  version = "5.0.0"

  name = "my-vpc"
  cidr = "10.0.0.0/16"

  azs             = ["us-east-1a", "us-east-1b", "us-east-1c"]
  private_subnets = ["10.0.1.0/24", "10.0.2.0/24", "10.0.3.0/24"]
  public_subnets  = ["10.0.101.0/24", "10.0.102.0/24", "10.0.103.0/24"]

  enable_nat_gateway = true
  single_nat_gateway = false
}

# EKS Cluster
module "eks" {
  source  = "terraform-aws-modules/eks/aws"
  version = "19.0.0"

  cluster_name    = "my-cluster"
  cluster_version = "1.28"

  vpc_id     = module.vpc.vpc_id
  subnet_ids = module.vpc.private_subnets

  eks_managed_node_groups = {
    default = {
      min_size     = 1
      max_size     = 10
      desired_size = 3
      instance_types = ["t3.medium"]
    }
  }
}

Variables and Outputs

# variables.tf
variable "aws_region" {
  description = "AWS region"
  type        = string
  default     = "us-east-1"
}

variable "environment" {
  description = "Environment name"
  type        = string
  validation {
    condition     = contains(["dev", "staging", "prod"], var.environment)
    error_message = "Environment must be dev, staging, or prod."
  }
}

# outputs.tf
output "cluster_endpoint" {
  description = "EKS cluster endpoint"
  value       = module.eks.cluster_endpoint
}

output "cluster_name" {
  description = "EKS cluster name"
  value       = module.eks.cluster_name
}

CI/CD Pipelines

GitHub Actions

# .github/workflows/deploy.yml
name: Deploy

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

env:
  REGISTRY: ghcr.io
  IMAGE_NAME: ${{ github.repository }}

jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with:
          node-version: "20"
          cache: "npm"
      - run: npm ci
      - run: npm test
      - run: npm run build

  build-and-push:
    needs: test
    runs-on: ubuntu-latest
    if: github.event_name == 'push'
    permissions:
      contents: read
      packages: write
    steps:
      - uses: actions/checkout@v4

      - name: Log in to registry
        uses: docker/login-action@v3
        with:
          registry: ${{ env.REGISTRY }}
          username: ${{ github.actor }}
          password: ${{ secrets.GITHUB_TOKEN }}

      - name: Build and push
        uses: docker/build-push-action@v5
        with:
          context: .
          push: true
          tags: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.sha }}

  deploy:
    needs: build-and-push
    runs-on: ubuntu-latest
    if: github.ref == 'refs/heads/main'
    steps:
      - uses: actions/checkout@v4

      - name: Deploy to Kubernetes
        uses: azure/k8s-deploy@v4
        with:
          manifests: k8s/
          images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.sha }}

GitLab CI

# .gitlab-ci.yml
stages:
  - test
  - build
  - deploy

variables:
  DOCKER_IMAGE: $CI_REGISTRY_IMAGE:$CI_COMMIT_SHA

test:
  stage: test
  image: node:20
  script:
    - npm ci
    - npm test
    - npm run build
  cache:
    paths:
      - node_modules/

build:
  stage: build
  image: docker:24
  services:
    - docker:24-dind
  script:
    - docker login -u $CI_REGISTRY_USER -p $CI_REGISTRY_PASSWORD $CI_REGISTRY
    - docker build -t $DOCKER_IMAGE .
    - docker push $DOCKER_IMAGE
  only:
    - main

deploy:
  stage: deploy
  image: bitnami/kubectl:latest
  script:
    - kubectl set image deployment/my-app my-app=$DOCKER_IMAGE
  only:
    - main
  environment:
    name: production

Docker

Multi-Stage Builds

# Build stage
FROM node:20-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build

# Production stage
FROM node:20-alpine AS production
WORKDIR /app
RUN addgroup -g 1001 -S nodejs && \
    adduser -S nextjs -u 1001
COPY --from=builder --chown=nextjs:nodejs /app/dist ./dist
COPY --from=builder --chown=nextjs:nodejs /app/node_modules ./node_modules
USER nextjs
EXPOSE 3000
CMD ["node", "dist/main.js"]

Docker Compose

# docker-compose.yml
version: "3.8"

services:
  app:
    build: .
    ports:
      - "3000:3000"
    environment:
      - DATABASE_URL=postgres://user:pass@db:5432/mydb
      - REDIS_URL=redis://redis:6379
    depends_on:
      db:
        condition: service_healthy
      redis:
        condition: service_started
    healthcheck:
      test: ["CMD", "curl", "-f", "http://localhost:3000/health"]
      interval: 30s
      timeout: 10s
      retries: 3

  db:
    image: postgres:16-alpine
    environment:
      POSTGRES_USER: user
      POSTGRES_PASSWORD: pass
      POSTGRES_DB: mydb
    volumes:
      - postgres_data:/var/lib/postgresql/data
    healthcheck:
      test: ["CMD-SHELL", "pg_isready -U user -d mydb"]
      interval: 10s
      timeout: 5s
      retries: 5

  redis:
    image: redis:7-alpine
    volumes:
      - redis_data:/data

volumes:
  postgres_data:
  redis_data:

Monitoring & Observability

Prometheus + Grafana

# prometheus.yml
global:
  scrape_interval: 15s

scrape_configs:
  - job_name: "kubernetes-pods"
    kubernetes_sd_configs:
      - role: pod
    relabel_configs:
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
        action: keep
        regex: true

Application Metrics

// metrics.ts
import { Counter, Histogram, Registry } from "prom-client";

export const register = new Registry();

export const httpRequestsTotal = new Counter({
  name: "http_requests_total",
  help: "Total HTTP requests",
  labelNames: ["method", "path", "status"],
  registers: [register],
});

export const httpRequestDuration = new Histogram({
  name: "http_request_duration_seconds",
  help: "HTTP request duration",
  labelNames: ["method", "path"],
  buckets: [0.1, 0.5, 1, 2, 5],
  registers: [register],
});

Security Best Practices

Secrets Management

# AWS Secrets Manager
aws secretsmanager create-secret \
  --name prod/db-credentials \
  --secret-string '{"username":"admin","password":"xxx"}'

# Kubernetes Secrets (external-secrets)
apiVersion: external-secrets.io/v1beta1
kind: ExternalSecret
metadata:
  name: db-credentials
spec:
  secretStoreRef:
    kind: ClusterSecretStore
    name: aws-secrets
  target:
    name: db-credentials
  data:
    - secretKey: username
      remoteRef:
        key: prod/db-credentials
        property: username

Network Policies

apiVersion: networking.k8s.io/v1
kind: NetworkPolicy
metadata:
  name: api-network-policy
spec:
  podSelector:
    matchLabels:
      app: api
  policyTypes:
    - Ingress
    - Egress
  ingress:
    - from:
        - podSelector:
            matchLabels:
              app: frontend
      ports:
        - protocol: TCP
          port: 8080
  egress:
    - to:
        - podSelector:
            matchLabels:
              app: database
      ports:
        - protocol: TCP
          port: 5432

Checklist

Pre-Deployment

  • Infrastructure as Code reviewed
  • Secrets in secrets manager (not env files)
  • Resource limits set
  • Health checks configured
  • Logging and monitoring enabled
  • Network policies defined
  • Backup strategy in place

Production Readiness

  • Multi-AZ deployment
  • Auto-scaling configured
  • SSL/TLS enabled
  • WAF rules configured
  • Disaster recovery tested
  • Runbooks documented

Installationen

Installationen193
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So verwenden Sie diesen Skill

1

Install devops-cloud by running npx skills add travisjneuman/.claude --skill devops-cloud in your project directory. Führen Sie den obigen Installationsbefehl in Ihrem Projektverzeichnis aus. Die Skill-Datei wird von GitHub heruntergeladen und in Ihrem Projekt platziert.

2

Keine Konfiguration erforderlich. Ihr KI-Agent (Claude Code, Cursor, Windsurf usw.) erkennt installierte Skills automatisch und nutzt sie als Kontext bei der Code-Generierung.

3

Der Skill verbessert das Verständnis Ihres Agenten für devops-cloud, und hilft ihm, etablierte Muster zu befolgen, häufige Fehler zu vermeiden und produktionsreifen Code zu erzeugen.

Was Sie erhalten

Skills sind Klartext-Anweisungsdateien — kein ausführbarer Code. Sie kodieren Expertenwissen über Frameworks, Sprachen oder Tools, das Ihr KI-Agent liest, um seine Ausgabe zu verbessern. Das bedeutet null Laufzeit-Overhead, keine Abhängigkeitskonflikte und volle Transparenz: Sie können jede Anweisung vor der Installation lesen und prüfen.

Kompatibilität

Dieser Skill funktioniert mit jedem KI-Coding-Agenten, der das skills.sh-Format unterstützt, einschließlich Claude Code (Anthropic), Cursor, Windsurf, Cline, Aider und anderen Tools, die projektbezogene Kontextdateien lesen. Skills sind auf Transportebene framework-agnostisch — der Inhalt bestimmt, für welche Sprache oder welches Framework er gilt.

Data sourced from the skills.sh registry and GitHub. Install counts and security audits are updated regularly.