Skills multi-cloud-architecture
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multi-cloud-architecture

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Design Multi-Cloud Architectures

Building applications across multiple cloud providers requires careful service selection and architecture decisions. This skill provides a decision framework and patterns for architecting applications across AWS, Azure, and GCP.

Supports: Claude Codex Code(CC)
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Using "multi-cloud-architecture". Compare AWS, Azure, and GCP database services for a high-traffic web application that needs ACID compliance and horizontal scaling.

Expected outcome:

  • AWS: Amazon Aurora with PostgreSQL compatibility - distributed SQL with auto-scaling
  • Azure: Azure SQL Database with Hyperscale - managed SQL with elastic resources
  • GCP: Cloud Spanner - globally distributed relational database with strong consistency
  • Recommendation: For global applications requiring horizontal scaling, Cloud Spanner or Aurora provide the best options. Consider Cloud Spanner if true global distribution is needed.

Using "multi-cloud-architecture". What multi-cloud pattern would you recommend for a healthcare application that must comply with data residency requirements in multiple countries?

Expected outcome:

  • Recommended Pattern: Geographic Distribution
  • Key elements:
  • 1. Deploy application instances in cloud regions matching data residency requirements
  • 2. Use global load balancing to route users to nearest compliant region
  • 3. Implement data replication with sovereignty controls
  • 4. Configure automatic failover between regions within same jurisdiction
  • This pattern ensures data stays within required geographic boundaries while providing high availability.

Using "multi-cloud-architecture". Create a migration strategy for moving our on-premise PostgreSQL database to a cloud-native database.

Expected outcome:

  • Migration Strategy: 4-Phase Approach
  • Phase 1 - Assessment: Inventory database size, dependencies, and features used
  • Phase 2 - Pilot: Deploy to cloud database, test compatibility, measure performance
  • Phase 3 - Migration: Use replication tools, run dual-write period, validate data integrity
  • Phase 4 - Optimization: Right-size resources, implement cloud-native features, optimize costs
  • Cloud-native options: RDS (AWS), Azure Database (Azure), Cloud SQL (GCP)

Security Audit

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v5 • 1/21/2026

This skill contains only documentation (SKILL.md) with no executable code. All static findings are false positives: the analyzer misinterpreted 'EC2' as C2 botnet terminology, markdown formatting backticks as shell command execution, and GitHub URL in metadata as hardcoded URL. No security concerns exist.

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Quality Score

38
Architecture
100
Maintainability
87
Content
29
Community
100
Security
91
Spec Compliance

What You Can Build

Design Multi-Cloud Strategy

Evaluate the benefits and trade-offs of using multiple cloud providers for a new application architecture.

Plan Cloud Migration

Assess an existing single-cloud workload and plan a migration strategy to another cloud provider.

Optimize Multi-Cloud Costs

Compare cost structures across AWS, Azure, and GCP and identify optimization opportunities.

Try These Prompts

Basic Multi-Cloud Question 
What are the equivalent services between AWS, Azure, and GCP for [workload type: compute/database/storage]?
Architecture Pattern Selection 
I need to design a multi-cloud architecture for [workload description]. Which pattern would you recommend and why? Consider [specific requirement: cost/performance/resilience].
Migration Planning 
Help me create a migration plan to move our [workload type] from [current cloud] to [target cloud]. What are the key steps and potential challenges?
Cost Optimization Review 
Compare the total cost of ownership for [specific service type] across AWS, Azure, and GCP. What factors affect pricing and which provider offers the best value for [use case]?

Best Practices

  • Use infrastructure as code (Terraform or OpenTofu) to maintain consistency across cloud environments
  • Design for failure by implementing redundancy and automated failover across providers
  • Implement abstraction layers using Kubernetes and open standards to reduce provider lock-in

Avoid

  • Running identical configurations across all clouds without optimizing for each provider's strengths
  • Using provider-specific services deeply throughout the application, making future migration difficult
  • Neglecting data transfer costs when architecting multi-cloud solutions

Frequently Asked Questions

What is the primary benefit of multi-cloud architecture?
Multi-cloud architecture reduces vendor lock-in, allows leveraging best-of-breed services from each provider, improves resilience through geographic distribution, and provides negotiating leverage with cloud vendors.
How do I avoid vendor lock-in while using cloud-native services?
Use abstraction layers like Kubernetes for compute, open-source databases like PostgreSQL, and cloud-agnostic tools like Terraform. Avoid deep integration with proprietary services that have no equivalent elsewhere.
What are the main cost considerations for multi-cloud?
Key costs include data transfer between clouds (often expensive), duplicated resources across providers, and operational overhead managing multiple environments. Optimize by right-sizing resources and using committed use discounts.
Which multi-cloud pattern is best for disaster recovery?
The Single Provider with DR pattern is most common: run primary workload in one cloud with a disaster recovery environment in another cloud provider. This provides geographic separation without the complexity of active-active deployments.
How do I handle networking between cloud providers?
Use VPN connections, dedicated interconnects (AWS Direct Connect, Azure ExpressRoute, GCP Cloud Interconnect), or third-party SD-WAN solutions. Consider latency, bandwidth requirements, and security when designing cross-cloud networking.
What skills does my team need for multi-cloud management?
Teams need expertise in Terraform or similar IaC tools, understanding of each cloud's specific services, networking across cloud boundaries, and monitoring tools that work across all providers like Prometheus and Grafana.

Developer Details

Author

wshobson

License

MIT

Repository

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

Ref

main

File structure

📄 SKILL.md