multi-cloud-architecture — Claude Code skill: what it does, install
This skill helps design systems across AWS, Azure, GCP, and OCI, compare services, and choose a migration or disaster recovery pattern.
/plugin marketplace add wshobson/agents
/plugin install cloud-infrastructure@claude-code-workflowsWhat multi-cloud-architecture does
multi-cloud-architecture provides a decision framework for selecting services across AWS, Azure, GCP, and OCI. It includes comparison tables for compute, storage, databases, and caching, plus patterns for disaster recovery, best-of-breed services, geographic distribution, and cloud-agnostic systems.
The skill connects application design with Kubernetes, PostgreSQL, Redis, S3-compatible APIs, Prometheus/Grafana, and Terraform. It also covers cost factors, staged migration, CI/CD, security, and disaster recovery tests. Install it when you are planning a multi-cloud system or moving workloads between providers; a single-cloud project may not need this material.
What it helps with
- compare AWS, Azure, GCP, and OCI services
- design disaster recovery across cloud providers
- choose services for a specific workload
- plan a staged migration between providers
- reduce dependence on one cloud
Example prompts for the agent
- Compare AWS, Azure, GCP, and OCI for this workload and propose an architecture.
- Plan a staged migration from AWS to Azure with validation steps and a dual-run period.
- Design a cloud-agnostic stack using Kubernetes, PostgreSQL, Redis, and Terraform.
How to install multi-cloud-architecture
1Plugin marketplace
/plugin marketplace add wshobson/agents/plugin install cloud-infrastructure@claude-code-workflowsThis installs the whole cloud-infrastructure plugin with all its skills
2Skills CLI (Vercel)
npx skills add wshobson/agents --skill multi-cloud-architecture -a claude-code3Manually: put the files in place
~/.claude/skills/multi-cloud-architecture/SKILL.mdCopy the whole skill folder; for one project use .claude/skills/multi-cloud-architecture/
1Skills CLI (Vercel)
npx skills add wshobson/agents --skill multi-cloud-architecture -a codex2Manually: put the files in place
.agents/skills/multi-cloud-architecture/SKILL.mdFor all projects use ~/.agents/skills/
1Skills CLI (Vercel)
npx skills add wshobson/agents --skill multi-cloud-architecture -a cursor2Manually: put the files in place
.cursor/skills/multi-cloud-architecture/SKILL.mdCursor also reads .agents/skills/ and .claude/skills/
1GitHub CLI
gh skill install wshobson/agents multi-cloud-architecture2Manually: put the files in place
.github/skills/multi-cloud-architecture/SKILL.mdPlatform CLI
gemini skills install https://github.com/wshobson/agents --path plugins/cloud-infrastructure/skills/multi-cloud-architectureManually: put the files in place
.devin/skills/multi-cloud-architecture/SKILL.mdThe legacy .windsurf/skills/ path still works
Claude.ai
Zip the folder and upload it in Settings → Capabilities → Skills
From the same set213
The whole set →Similar
Questions about multi-cloud-architecture
How do I install multi-cloud-architecture in Claude Code?
Run npx skills add wshobson/agents --skill multi-cloud-architecture -a claude-code. The skill file is placed at ~/.claude/skills/multi-cloud-architecture/SKILL.md.
What does multi-cloud-architecture do?
It helps select and connect services across AWS, Azure, GCP, and OCI. The skill covers disaster recovery, migration, geographic distribution, and cloud-agnostic architecture patterns.
Which tools does it use for cloud-agnostic architecture?
The source covers Kubernetes for compute, PostgreSQL or MySQL for databases, Redis for caching, S3-compatible storage, Prometheus/Grafana, and Terraform for infrastructure abstraction.
Source text
SKILL.md · MIT
---
name: multi-cloud-architecture
description: 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.
---
# 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
- 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
1. **Use infrastructure as code** (Terraform/OpenTofu)
2. **Implement CI/CD pipelines** for deployments
3. **Design for failure** across clouds
4. **Use managed services** when possible
5. **Implement comprehensive monitoring**
6. **Automate cost optimization**
7. **Follow security best practices**
8. **Document cloud-specific configurations**
9. **Test disaster recovery** procedures
10. **Train teams** on multiple clouds
## Related Skills
- `terraform-module-library` - For IaC implementation
- `cost-optimization` - For cost management
- `hybrid-cloud-networking` - For connectivity
© Seth Hobson · MIT · wshobson/agents