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Misc41k · #4829

multi-cloud-architecture

Guides your agent in designing multi-cloud architectures, integrating services from different providers.

What it does

This tool helps plan how to use multiple cloud providers (like AWS, Azure, Google Cloud) for your applications. It compares services and suggests how to combine them to avoid relying on a single vendor or to use the best from each.

When to use it

  • ✓When planning a new system that will use more than one cloud provider.
  • ✓When deciding which cloud services to use for each part of your application.
  • ✓When you want to avoid vendor lock-in.

Example of what to ask your AI

“How can I use Google Cloud for AI and AWS for data storage in my new project?”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/wshobson/agents/blob/main/plugins/cloud-infrastructure/skills/multi-cloud-architecture/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/wshobson/agents/blob/main/plugins/cloud-infrastructure/skills/multi-cloud-architecture/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
View on GitHub ↗Raw file
How it works

The tool uses a decision framework and compares compute, storage, and database services across major cloud providers. It also presents common patterns for combining these services.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add wshobson/agents --skill multi-cloud-architecture

Or download just the file:

curl -L https://raw.githubusercontent.com/wshobson/agents/main/plugins/cloud-infrastructure/skills/multi-cloud-architecture/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

Multi-Cloud Architecture

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

Purpose

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

When to Use

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

Storage Services

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

Database Services

AWS Azure GCP OCI Use Case
RDS SQL Database Cloud SQL MySQL HeatWave Managed SQL
DynamoDB Cosmos DB Firestore NoSQL Database NoSQL
Aurora PostgreSQL/MySQL Cloud Spanner Autonomous Database Distributed SQL
ElastiCache Cache for Redis Memorystore OCI Cache 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
  • Regulated data platforms on OCI
  • 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/OKE)
  • Database: PostgreSQL/MySQL (RDS/SQL Database/Cloud SQL/MySQL HeatWave)
  • Message Queue: Apache Kafka or managed streaming (MSK/Event Hubs/Confluent/OCI Streaming)
  • Cache: Redis (ElastiCache/Azure Cache/Memorystore/OCI Cache)
  • 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 / OCI

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
  • OCI: Pay-as-you-go, annual commitments, burstable/flexible shapes, preemptible instances

Cost Optimization Strategies

  1. Use reserved/committed capacity (30-70% savings)
  2. Leverage spot/preemptible instances
  3. Right-size resources
  4. Use serverless for variable workloads
  5. Optimize data transfer costs
  6. Implement lifecycle policies
  7. Use cost allocation tags
  8. 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

…

FAQ

What does 'avoiding vendor lock-in' mean?

It means not relying exclusively on a single cloud provider, allowing for more flexibility and negotiation power.

What are 'best-of-breed services'?

These are services offered by a cloud provider that are considered the best or most advanced compared to others for a specific task.

What is 'infrastructure as code'?

It's a way to manage and provision cloud infrastructure (servers, networks, etc.) using machine-readable configuration files, rather than manual setup.

Details

Original description by the author

Design multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, GCP, and OCI. Use when building multi-cloud systems, avoiding vendor lock-in, or leveraging best-of-breed services from multiple providers.

repo: wshobson/agents

Popularity

GitHub stars
41k
Ranking position
#4829
License
MIT
Updated
10/15/2026

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