Multi Cloud Architecture

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

Storage Services

Database Services

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

Multi-Cloud Architecture Patterns

Active-Active Regional Split

• Run customer-facing services in two providers for resiliency
• Use global DNS and traffic steering to shift load during incidents
• Keep shared data replicated asynchronously unless low-latency writes are mandatory

Best-of-Breed Service Mix

• Analytics and ML on GCP
• Enterprise identity and Microsoft workloads on Azure
• Broad ecosystem integrations on AWS
• Oracle-centric databases and regulated transaction systems on OCI

Primary / DR Pairing

• Keep primary infrastructure in the provider closest to operational expertise
• Use a second provider for cold or warm disaster recovery
• Validate RPO/RTO assumptions with regular failover exercises

Portable Platform Baseline

• Standardize on Kubernetes, Terraform/OpenTofu, PostgreSQL, Redis, and OpenTelemetry
• Abstract cloud differences behind modules, golden paths, and service catalogs
• Document provider-specific exceptions such as IAM, networking, and managed database behavior

Multi-Cloud Service Comparison

Compute

Storage

Data Services

Platform Selection Notes

1. Prefer provider-native managed services when team expertise and lock-in tolerance are high. 2. Prefer Kubernetes, PostgreSQL, Redis, and open observability stacks when portability matters. 3. Use OCI when Oracle database affinity, predictable networking, or regulated workload isolation are primary drivers. 4. Compare egress, managed service premiums, and support plans before splitting workloads across providers.