{
  "schema": "https://ai-atoms.com/schemas/skill-v1.json",
  "type": "skill",
  "id": "skill/multi-cloud-architecture",
  "version": "1.0.0",
  "name": "Multi Cloud Architecture",
  "description": "Design multi-cloud architectures using a decision framework to select and integrate services across AWS, Azure, and GCP. Use when building multi-cloud systems, avoiding vendor lock-in, or leveragin...",
  "system_prompt_fragment": "# Multi-Cloud Architecture\n\nDecision framework and patterns for architecting applications across AWS, Azure, and GCP.\n\n## Do not use this skill when\n\n- The task is unrelated to multi-cloud architecture\n- You need a different domain or tool outside this scope\n\n## Instructions\n\n- Clarify goals, constraints, and required inputs.\n- Apply relevant best practices and validate outcomes.\n- Provide actionable steps and verification.\n- If detailed examples are required, open `resources/implementation-playbook.md`.\n\n## Purpose\n\nDesign cloud-agnostic architectures and make informed decisions about service selection across cloud providers.\n\n## Use this skill when\n\n- Design multi-cloud strategies\n- Migrate between cloud providers\n- Select cloud services for specific workloads\n- Implement cloud-agnostic architectures\n- Optimize costs across providers\n\n## Cloud Service Comparison\n\n### Compute Services\n\n| AWS | Azure | GCP | Use Case |\n|-----|-------|-----|----------|\n| EC2 | Virtual Machines | Compute Engine | IaaS VMs |\n| ECS | Container Instances | Cloud Run | Containers |\n| EKS | AKS | GKE | Kubernetes |\n| Lambda | Functions | Cloud Functions | Serverless |\n| Fargate | Container Apps | Cloud Run | Managed containers |\n\n### Storage Services\n\n| AWS | Azure | GCP | Use Case |\n|-----|-------|-----|----------|\n| S3 | Blob Storage | Cloud Storage | Object storage |\n| EBS | Managed Disks | Persistent Disk | Block storage |\n| EFS | Azure Files | Filestore | File storage |\n| Glacier | Archive Storage | Archive Storage | Cold storage |\n\n### Database Services\n\n| AWS | Azure | GCP | Use Case |\n|-----|-------|-----|----------|\n| RDS | SQL Database | Cloud SQL | Managed SQL |\n| DynamoDB | Cosmos DB | Firestore | NoSQL |\n| Aurora | PostgreSQL/MySQL | Cloud Spanner | Distributed SQL |\n| ElastiCache | Cache for Redis | Memorystore | Caching |\n\n**Reference:** See `references/service-comparison.md` for complete comparison\n\n## Multi-Cloud Patterns\n\n### Pattern 1: Single Provider with DR\n\n- Primary workload in one cloud\n- Disaster recovery in another\n- Database replication across clouds\n- Automated failover\n\n### Pattern 2: Best-of-Breed\n\n- Use best service from each provider\n- AI/ML on GCP\n- Enterprise apps on Azure\n- General compute on AWS\n\n### Pattern 3: Geographic Distribution\n\n- Serve users from nearest cloud region\n- Data sovereignty compliance\n- Global load balancing\n- Regional failover\n\n### Pattern 4: Cloud-Agnostic Abstraction\n\n- Kubernetes for compute\n- PostgreSQL for database\n- S3-compatible storage (MinIO)\n- Open source tools\n\n## Cloud-Agnostic Architecture\n\n### Use Cloud-Native Alternatives\n\n- **Compute:** Kubernetes (EKS/AKS/GKE)\n- **Database:** PostgreSQL/MySQL (RDS/SQL Database/Cloud SQL)\n- **Message Queue:** Apache Kafka (MSK/Event Hubs/Confluent)\n- **Cache:** Redis (ElastiCache/Azure Cache/Memorystore)\n- **Object Storage:** S3-compatible API\n- **Monitoring:** Prometheus/Grafana\n- **Service Mesh:** Istio/Linkerd\n\n### Abstraction Layers\n\n```\nApplication Layer\n    ↓\nInfrastructure Abstraction (Terraform)\n    ↓\nCloud Provider APIs\n    ↓\nAWS / Azure / GCP\n```\n\n## Cost Comparison\n\n### Compute Pricing Factors\n\n- **AWS:** On-demand, Reserved, Spot, Savings Plans\n- **Azure:** Pay-as-you-go, Reserved, Spot\n- **GCP:** On-demand, Committed use, Preemptible\n\n### Cost Optimization Strategies\n\n1. Use reserved/committed capacity (30-70% savings)\n2. Leverage spot/preemptible instances\n3. Right-size resources\n4. Use serverless for variable workloads\n5. Optimize data transfer costs\n6. Implement lifecycle policies\n7. Use cost allocation tags\n8. Monitor with cloud cost tools\n\n**Reference:** See `references/multi-cloud-patterns.md`\n\n## Migration Strategy\n\n### Phase 1: Assessment\n- Inventory current infrastructure\n- Identify dependencies\n- Assess cloud compatibility\n- Estimate costs\n\n### Phase 2: Pilot\n- Select pilot workload\n- Implement in target cloud\n- Test thoroughly\n- Document learnings\n\n### Phase 3: Migration\n- Migrate workloads incrementally\n- Maintain dual-run period\n- Monitor performance\n- Validate functionality\n\n### Phase 4: Optimization\n- Right-size resources\n- Implement cloud-native services\n- Optimize costs\n- Enhance security\n\n## Best Practices\n\n1. **Use infrastructure as code** (Terraform/OpenTofu)\n2. **Implement CI/CD pipelines** for deployments\n3. **Design for failure** across clouds\n4. **Use managed services** when possible\n5. **Implement comprehensive monitoring**\n6. **Automate cost optimization**\n7. **Follow security best practices**\n8. **Document cloud-specific configurations**\n9. **Test disaster recovery** procedures\n10. **Train teams** on multiple clouds\n\n## Reference Files\n\n- `references/service-comparison.md` - Complete service comparison\n- `references/multi-cloud-patterns.md` - Architecture patterns\n\n## Related Skills\n\n- `terraform-module-library` - For IaC implementation\n- `cost-optimization` - For cost management\n- `hybrid-cloud-networking` - For connectivity",
  "applicable_domains": [
    "devops"
  ],
  "category": "devops",
  "invocation": [
    "/multi-cloud-architecture"
  ],
  "authored_by": "claudeskills.in community",
  "source_url": "https://claudeskills.in/skill/multi-cloud-architecture",
  "provenance": {
    "source": "claudeskills.in",
    "source_url": "https://claudeskills.in/skill/multi-cloud-architecture",
    "license": "unknown",
    "imported_at": "2026-09-03",
    "notes": "Aggregated by claudeskills.in from community GitHub lists."
  },
  "tags": [
    "claudeskills",
    "devops"
  ],
  "lifecycle": "draft"
}