Multi Cloud Architecture

When to use this skill

Use Multi Cloud Architecture when an AI agent needs a reusable SKILL.md workflow for this job: 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.

When not to use it

Skip Multi Cloud Architecture when the task is outside the coding category, or when a more specific skill in this directory already covers the same workflow with clearer triggers.

How to install

1. Personal install: create ~/.claude/skills/multi-cloud-architecture/SKILL.md (and any bundled scripts) so Claude Code, Claude Desktop, and compatible agents can load it in every project.
2. Project install: commit the same folder at .claude/skills/multi-cloud-architecture/ so teammates get the skill with the repo.
3. Restart the agent session after copying files so it re-scans the skills directory, then ask for the task in words that match the skill description.

Full install guide for Claude, Cursor, and Codex

What this skill does

# 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

Intended uses

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