/multi-cloud-architecture

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