Deploy a Multi-Cloud Application

Architecture Overview

This architecture deploys identical application instances on AWS and Azure, placing them behind a global load balancer that directs users to the nearest healthy endpoint. The application runs as a containerized service on both clouds: ECS Fargate on AWS and Container Instances on Azure. Each cloud also hosts its own managed PostgreSQL database, with application-level synchronization keeping data consistent across providers.

The global load balancer is the key component. It monitors health check endpoints on both deployments and routes traffic based on geographic proximity. If one cloud provider experiences an outage, the load balancer detects the failed health checks and shifts all traffic to the remaining healthy deployment. This failover is automatic and requires no manual intervention.

The primary challenge in multi-cloud architectures is data consistency. Each cloud has its own managed database service with different replication capabilities. Rather than relying on provider-specific replication features that do not cross cloud boundaries, this architecture uses application-level synchronization to keep both databases in sync. This approach gives you control over conflict resolution and lets you choose eventual or strong consistency based on your application’s requirements.

Container Services

The application runs on ECS Fargate in AWS and Azure Container Instances in Azure. Both services provide serverless container execution, so you deploy the same Docker image to each cloud without managing virtual machines. Each deployment has its own scaling configuration tuned to the traffic patterns in that region.

Global Load Balancing

A global load balancer (such as Azure Traffic Manager or AWS Global Accelerator) distributes traffic based on endpoint health and geographic proximity. It continuously monitors health check endpoints and maintains a routing table that directs users to the closest healthy deployment. Failover typically completes within seconds of detecting an unhealthy endpoint.

Database Layer

Each cloud runs a managed PostgreSQL instance. AWS uses Amazon RDS for PostgreSQL, and Azure uses Azure Database for PostgreSQL. Application-level synchronization handles data replication between the two databases. This is more complex than single-cloud replication but gives you the flexibility to choose which data is replicated, how conflicts are resolved, and whether synchronization is real-time or batched.

Common Customizations

• Add a third region: Extend the prompt to include a GCP deployment for true tri-cloud redundancy with Cloud Run as the container platform.
• Use a specific workload: Replace the generic API with your actual application workload, such as a payment processing service or customer-facing portal, to get infrastructure tailored to your use case.
• Add CDN caching: Ask for CloudFront and Azure CDN in front of the application endpoints to cache static responses and reduce origin load.
• Implement active-passive: Simplify the data layer by using one cloud as the primary with synchronous writes and the other as a standby with asynchronous replication.