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