多云架构指南：AWS、Azure、GCP 决策框架、模式与成本优化策略

multi-cloud-architecture by sickn33/antigravity-awesome-skills

90 周安装量

27,100 GitHub Stars

GitHub

安装命令

npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill multi-cloud-architecture

云服务开发运维系统架构

🇨🇳中文介绍

多云架构

适用于在 AWS、Azure 和 GCP 上架构应用程序的决策框架和模式。

不应使用此技能的情况

任务与多云架构无关
你需要此范围之外的不同领域或工具

使用说明

明确目标、约束条件和所需输入。
应用相关最佳实践并验证结果。
提供可操作的步骤和验证方法。
如果需要详细示例，请打开 resources/implementation-playbook.md。

目的

设计云无关的架构，并在云服务提供商之间做出明智的服务选择决策。

应使用此技能的情况

设计多云策略
在云服务提供商之间迁移
为特定工作负载选择云服务
实施云无关的架构
跨提供商优化成本

云服务对比

计算服务

AWS	Azure	GCP	使用场景
EC2	Virtual Machines	Compute Engine	IaaS 虚拟机
ECS

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AWS	Azure	GCP	使用场景
S3	Blob Storage	Cloud Storage	对象存储
EBS	Managed Disks	Persistent Disk	块存储
EFS	Azure Files	Filestore	文件存储
Glacier	Archive Storage	Archive Storage	冷存储

AWS	Azure	GCP	使用场景
RDS	SQL Database	Cloud SQL	托管 SQL
DynamoDB	Cosmos DB	Firestore	NoSQL
Aurora	PostgreSQL/MySQL	Cloud Spanner	分布式 SQL
ElastiCache	Cache for Redis	Memorystore	缓存

模式 1：单一提供商 + 灾难恢复

主要工作负载在一个云中
灾难恢复在另一个云中
跨云数据库复制
自动故障转移

模式 2：最佳组合

使用每个提供商的最佳服务
AI/ML 在 GCP
企业应用在 Azure
通用计算在 AWS

模式 3：地理分布

从最近的云区域为用户提供服务
数据主权合规
全局负载均衡
区域故障转移

模式 4：云无关抽象

使用 Kubernetes 进行计算
使用 PostgreSQL 作为数据库
使用 S3 兼容存储（MinIO）
使用开源工具

使用云原生替代方案

计算： Kubernetes (EKS/AKS/GKE)
数据库： PostgreSQL/MySQL (RDS/SQL Database/Cloud SQL)
消息队列： Apache Kafka (MSK/Event Hubs/Confluent)
缓存： Redis (ElastiCache/Azure Cache/Memorystore)
对象存储： S3 兼容 API
监控： Prometheus/Grafana
服务网格： Istio/Linkerd

Application Layer
    ↓
Infrastructure Abstraction (Terraform)
    ↓
Cloud Provider APIs
    ↓
AWS / Azure / GCP

AWS： 按需、预留、竞价、节省计划
Azure： 即用即付、预留、竞价
GCP： 按需、承诺使用、可抢占

使用预留/承诺容量（节省 30-70%）
利用竞价/可抢占实例
调整资源规模
对可变工作负载使用无服务器
优化数据传输成本
实施生命周期策略
使用成本分配标签
使用云成本工具进行监控

参考： 参见 references/multi-cloud-patterns.md

盘点当前基础设施
识别依赖关系
评估云兼容性
估算成本

选择试点工作负载
在目标云中实施
全面测试
记录经验教训

增量迁移工作负载
保持双运行期
监控性能
验证功能

调整资源规模
实施云原生服务
优化成本
增强安全性

使用基础设施即代码 (Terraform/OpenTofu)
实施 CI/CD 流水线 进行部署
设计跨云容错
尽可能使用托管服务
实施全面的监控
自动化成本优化
遵循安全最佳实践
记录云特定配置
测试灾难恢复 流程
培训团队 掌握多云技能

references/service-comparison.md - 完整的服务对比
references/multi-cloud-patterns.md - 架构模式

terraform-module-library - 用于 IaC 实施
cost-optimization - 用于成本管理
hybrid-cloud-networking - 用于连接性

🇺🇸English

Multi-Cloud Architecture

Decision framework and patterns for architecting applications across AWS, Azure, and GCP.

Do not use this skill when

The task is unrelated to multi-cloud architecture
You need a different domain or tool outside this scope

Instructions

Clarify goals, constraints, and required inputs.
Apply relevant best practices and validate outcomes.
Provide actionable steps and verification.
If detailed examples are required, open resources/implementation-playbook.md.

Purpose

Design cloud-agnostic architectures and make informed decisions about service selection across cloud providers.

Use this skill when

Design multi-cloud strategies
Migrate between cloud providers
Select cloud services for specific workloads
Implement cloud-agnostic architectures
Optimize costs across providers

Cloud Service Comparison

Compute Services

AWS	Azure	GCP	Use Case
EC2	Virtual Machines	Compute Engine	IaaS VMs
ECS	Container Instances	Cloud Run	Containers
EKS	AKS	GKE	Kubernetes
Lambda	Functions	Cloud Functions	Serverless
Fargate	Container Apps	Cloud Run	Managed containers

Storage Services

AWS	Azure	GCP	Use Case
S3	Blob Storage	Cloud Storage	Object storage
EBS	Managed Disks	Persistent Disk	Block storage
EFS	Azure Files	Filestore	File storage
Glacier	Archive Storage	Archive Storage	Cold storage

Database Services

AWS	Azure	GCP	Use Case
RDS	SQL Database	Cloud SQL	Managed SQL
DynamoDB	Cosmos DB	Firestore	NoSQL
Aurora	PostgreSQL/MySQL	Cloud Spanner	Distributed SQL
ElastiCache	Cache for Redis	Memorystore	Caching

Reference: See references/service-comparison.md for complete comparison

Multi-Cloud Patterns

Pattern 1: Single Provider with DR

Primary workload in one cloud
Disaster recovery in another
Database replication across clouds
Automated failover

Pattern 2: Best-of-Breed

Use best service from each provider
AI/ML on GCP
Enterprise apps on Azure
General compute on AWS

Pattern 3: Geographic Distribution

Serve users from nearest cloud region
Data sovereignty compliance
Global load balancing
Regional failover

Pattern 4: Cloud-Agnostic Abstraction

Kubernetes for compute
PostgreSQL for database
S3-compatible storage (MinIO)
Open source tools

Cloud-Agnostic Architecture

Use Cloud-Native Alternatives

Compute: Kubernetes (EKS/AKS/GKE)
Database: PostgreSQL/MySQL (RDS/SQL Database/Cloud SQL)
Message Queue: Apache Kafka (MSK/Event Hubs/Confluent)
Cache: Redis (ElastiCache/Azure Cache/Memorystore)
Object Storage: S3-compatible API
Monitoring: Prometheus/Grafana
Service Mesh: Istio/Linkerd

Abstraction Layers

Application Layer
    ↓
Infrastructure Abstraction (Terraform)
    ↓
Cloud Provider APIs
    ↓
AWS / Azure / GCP

Cost Comparison

Compute Pricing Factors

AWS: On-demand, Reserved, Spot, Savings Plans
Azure: Pay-as-you-go, Reserved, Spot
GCP: On-demand, Committed use, Preemptible

Cost Optimization Strategies

Use reserved/committed capacity (30-70% savings)
Leverage spot/preemptible instances
Right-size resources
Use serverless for variable workloads
Optimize data transfer costs
Implement lifecycle policies
Use cost allocation tags
Monitor with cloud cost tools

Reference: See references/multi-cloud-patterns.md

Migration Strategy

Phase 1: Assessment

Inventory current infrastructure
Identify dependencies
Assess cloud compatibility
Estimate costs

Phase 2: Pilot

Select pilot workload
Implement in target cloud
Test thoroughly
Document learnings

Phase 3: Migration

Migrate workloads incrementally
Maintain dual-run period
Monitor performance
Validate functionality

Phase 4: Optimization

Right-size resources
Implement cloud-native services
Optimize costs
Enhance security

Best Practices

Use infrastructure as code (Terraform/OpenTofu)
Implement CI/CD pipelines for deployments
Design for failure across clouds
Use managed services when possible
Implement comprehensive monitoring
Automate cost optimization
Follow security best practices
Document cloud-specific configurations
Test disaster recovery procedures
Train teams on multiple clouds

Reference Files

references/service-comparison.md - Complete service comparison
references/multi-cloud-patterns.md - Architecture patterns

Related Skills

terraform-module-library - For IaC implementation
cost-optimization - For cost management
hybrid-cloud-networking - For connectivity

Weekly Installs

Repository

sickn33/antigra…e-skills

GitHub Stars

27.1K

First Seen

Jan 28, 2026

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