Token导航 LogoToken导航TokenDH.com
云服务external-servicegithub未标认证来源可访问许可证需确认审计未展示

aws-&-azure-multi-cloud-expertAWS Azure multi cloud expert 部署

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

3,769

周安装

165

GitHub Stars

公开资料未说明

下载量

2,303
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:aws-&-azure-multi-cloud-expert(AWS Azure multi cloud expert 部署)
来源仓库:https://github.com/krosebrook/source-of-truth-monorepo
仓库路径:skills/aws-&-azure-multi-cloud-expert
安装命令:
npx skills add krosebrook/source-of-truth-monorepo --skill "aws-&-azure-multi-cloud-expert"
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。

AgentSkills.tonpx skills
npx skills add krosebrook/source-of-truth-monorepo --skill "aws-&-azure-multi-cloud-expert"

简介

该技能用于辅助多云环境下的 AWS 和 Azure 资源部署与管理。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中进行跨云平台架构设计。
  • 通过 npx skills add krosebrook/source-of-truth-monorepo --skill "aws-&-azure-multi-cloud-expert" 安装。
  • 需分别配置 AWS 和 Azure 凭证,注意区域和资源组隔离。
  • 建议先在沙箱环境验证后再应用于正式项目。

SKILL.md

AWS & Azure Multi-Cloud Expert

Production deployment patterns for AWS and Azure.

AWS Deployment Patterns

Serverless with Lambda + API Gateway

// AWS CDK Stack
import * as cdk from 'aws-cdk-lib';
import * as lambda from 'aws-cdk-lib/aws-lambda';
import * as apigateway from 'aws-cdk-lib/aws-apigateway';
import * as dynamodb from 'aws-cdk-lib/aws-dynamodb';

export class ServerlessStack extends cdk.Stack {
  constructor(scope: cdk.App, id: string, props?: cdk.StackProps) {
    super(scope, id, props);

    // DynamoDB Table
    const table = new dynamodb.Table(this, 'Table', {
      partitionKey: { name: 'id', type: dynamodb.AttributeType.STRING },
      billingMode: dynamodb.BillingMode.PAY_PER_REQUEST,
    });

    // Lambda Function
    const handler = new lambda.Function(this, 'Handler', {
      runtime: lambda.Runtime.NODEJS_18_X,
      code: lambda.Code.fromAsset('lambda'),
      handler: 'index.handler',
      environment: {
        TABLE_NAME: table.tableName,
      },
    });

    table.grantReadWriteData(handler);

    // API Gateway
    const api = new apigateway.RestApi(this, 'API', {
      restApiName: 'Serverless API',
      deployOptions: {
        stageName: 'prod',
        throttlingBurstLimit: 100,
        throttlingRateLimit: 50,
      },
    });

    const integration = new apigateway.LambdaIntegration(handler);
    api.root.addMethod('ANY', integration);
    api.root.addResource('{proxy+}').addMethod('ANY', integration);
  }
}

ECS Fargate Deployment

import * as ecs from 'aws-cdk-lib/aws-ecs';
import * as ec2 from 'aws-cdk-lib/aws-ec2';
import * as elbv2 from 'aws-cdk-lib/aws-elasticloadbalancingv2';

export class FargateStack extends cdk.Stack {
  constructor(scope: cdk.App, id: string) {
    super(scope, id);

    const vpc = new ec2.Vpc(this, 'VPC', { maxAzs: 2 });

    const cluster = new ecs.Cluster(this, 'Cluster', { vpc });

    const taskDefinition = new ecs.FargateTaskDefinition(this, 'TaskDef', {
      memoryLimitMiB: 512,
      cpu: 256,
    });

    taskDefinition.addContainer('app', {
      image: ecs.ContainerImage.fromRegistry('myapp:latest'),
      portMappings: [{ containerPort: 8000 }],
      environment: {
        NODE_ENV: 'production',
      },
      logging: ecs.LogDrivers.awsLogs({ streamPrefix: 'app' }),
    });

    const service = new ecs.FargateService(this, 'Service', {
      cluster,
      taskDefinition,
      desiredCount: 2,
    });

    const lb = new elbv2.ApplicationLoadBalancer(this, 'LB', {
      vpc,
      internetFacing: true,
    });

    const listener = lb.addListener('Listener', { port: 80 });
    listener.addTargets('ECS', {
      port: 8000,
      targets: [service],
      healthCheck: { path: '/health' },
    });
  }
}

S3 + CloudFront CDN

import * as s3 from 'aws-cdk-lib/aws-s3';
import * as cloudfront from 'aws-cdk-lib/aws-cloudfront';
import * as origins from 'aws-cdk-lib/aws-cloudfront-origins';

const bucket = new s3.Bucket(this, 'WebsiteBucket', {
  websiteIndexDocument: 'index.html',
  publicReadAccess: true,
  removalPolicy: cdk.RemovalPolicy.DESTROY,
});

const distribution = new cloudfront.Distribution(this, 'Distribution', {
  defaultBehavior: {
    origin: new origins.S3Origin(bucket),
    viewerProtocolPolicy: cloudfront.ViewerProtocolPolicy.REDIRECT_TO_HTTPS,
    cachePolicy: cloudfront.CachePolicy.CACHING_OPTIMIZED,
  },
  defaultRootObject: 'index.html',
});

Azure Deployment Patterns

Azure Functions

// function.ts
import { AzureFunction, Context, HttpRequest } from "@azure/functions";

const httpTrigger: AzureFunction = async function (
  context: Context,
  req: HttpRequest
): Promise<void> {
  context.log('HTTP trigger function processed a request.');

  const name = req.query.name || (req.body && req.body.name);
  const responseMessage = name
    ? `Hello, ${name}!`
    : "Please pass a name on the query string or in the request body";

  context.res = {
    status: 200,
    body: responseMessage
  };
};

export default httpTrigger;
// host.json
{
  "version": "2.0",
  "logging": {
    "applicationInsights": {
      "samplingSettings": {
        "isEnabled": true,
        "maxTelemetryItemsPerSecond": 20
      }
    }
  }
}

Azure Container Apps

# Deploy container to Azure Container Apps
az containerapp create \
  --name myapp \
  --resource-group myResourceGroup \
  --environment myEnvironment \
  --image myregistry.azurecr.io/myapp:latest \
  --target-port 8000 \
  --ingress external \
  --min-replicas 2 \
  --max-replicas 10 \
  --cpu 0.5 \
  --memory 1.0Gi \
  --env-vars \
    DATABASE_URL=secretref:db-url \
    REDIS_URL=secretref:redis-url

Terraform for Multi-Cloud

# main.tf
terraform {
  required_providers {
    aws = {
      source  = "hashicorp/aws"
      version = "~> 5.0"
    }
    azurerm = {
      source  = "hashicorp/azurerm"
      version = "~> 3.0"
    }
  }
}

# AWS Resources
resource "aws_s3_bucket" "data" {
  bucket = "my-data-bucket"
  acl    = "private"
}

# Azure Resources
resource "azurerm_storage_account" "data" {
  name                     = "mydatastorageaccount"
  resource_group_name      = azurerm_resource_group.rg.name
  location                 = azurerm_resource_group.rg.location
  account_tier             = "Standard"
  account_replication_type = "GRS"
}

Deployment Scripts

# AWS Deploy Script
#!/bin/bash
set -e

# Build and push Docker image
docker build -t myapp:latest .
docker tag myapp:latest 123456789.dkr.ecr.us-east-1.amazonaws.com/myapp:latest
aws ecr get-login-password --region us-east-1 | \
  docker login --username AWS --password-stdin 123456789.dkr.ecr.us-east-1.amazonaws.com
docker push 123456789.dkr.ecr.us-east-1.amazonaws.com/myapp:latest

# Update ECS service
aws ecs update-service \
  --cluster my-cluster \
  --service my-service \
  --force-new-deployment
# Azure Deploy Script
#!/bin/bash
set -e

# Build and push Docker image
az acr build \
  --registry myregistry \
  --image myapp:latest \
  --file Dockerfile .

# Update Container App
az containerapp update \
  --name myapp \
  --resource-group myResourceGroup \
  --image myregistry.azurecr.io/myapp:latest

Best Practices

✅ Use Infrastructure as Code (CDK, Terraform) ✅ Implement least-privilege IAM policies ✅ Enable logging and monitoring ✅ Use managed services when possible ✅ Implement auto-scaling ✅ Use secrets management (Secrets Manager, Key Vault) ✅ Enable encryption at rest and in transit ✅ Implement proper backup strategies ✅ Use cost optimization tools ✅ Implement multi-region redundancy


When to Use: Cloud deployments, AWS/Azure infrastructure, serverless applications, multi-cloud strategies.

适合场景

01

Azure 资源规划

02

云服务升级

03

基础设施检查

04

企业云环境自动化

能力概览

能力 1

整理 Azure 服务操作流程

能力 2

提示 CLI/MCP 前置条件

能力 3

辅助云资源检查和规划

能力 4

保留官方服务来源线索

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

35.96%
按下载量换算828

Claude

28.55%
按下载量换算658

Cursor

17.58%
按下载量换算405

Gemini CLI

10.41%
按下载量换算240

安全审计

暂无安全审计结果可展示。

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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

继续浏览同类 Skills