Architecture
A multi-cloud serverless architecture diagram with DNS-based traffic routing between AWS and Azure regions, automatic failover on health check failures, and bi-directional data replication with conflict resolution across cloud providers. This template models the multi-cloud strategy for maximum availability and vendor independence, using serverless services from both AWS (Lambda, DynamoDB) and Azure (Functions, Cosmos DB). Critical for enterprises requiring cloud provider redundancy.
Full FlowZap Code
TrafficManager { # Global Traffic Manager
n1: circle label:"User Request"
n2: rectangle label:"DNS-Based Routing"
n3: diamond label:"Primary Cloud Healthy?"
n4: rectangle label:"Route to Primary (AWS)"
n5: rectangle label:"Failover to Secondary (Azure)"
n1.handle(right) -> n2.handle(left)
n2.handle(right) -> n3.handle(left)
n3.handle(right) -> n4.handle(left) [label="Healthy"]
n3.handle(bottom) -> n5.handle(top) [label="Unhealthy"]
n4.handle(bottom) -> AWS.n6.handle(top) [label="Forward"]
n5.handle(bottom) -> Azure.n11.handle(top) [label="Forward"]
}
AWS { # AWS Region
n6: rectangle label:"API Gateway"
n7: rectangle label:"Lambda Functions"
n8: rectangle label:"DynamoDB"
n9: rectangle label:"S3 Storage"
n10: rectangle label:"CloudWatch Monitoring"
n6.handle(right) -> n7.handle(left) [label="Invoke"]
n7.handle(right) -> n8.handle(left) [label="Read/Write"]
n7.handle(bottom) -> n9.handle(top) [label="Store"]
n10.handle(top) -> TrafficManager.n3.handle(bottom) [label="Health Check"]
}
Azure { # Azure Region
n11: rectangle label:"Azure API Management"
n12: rectangle label:"Azure Functions"
n13: rectangle label:"Cosmos DB"
n14: rectangle label:"Blob Storage"
n15: rectangle label:"Azure Monitor"
n11.handle(right) -> n12.handle(left) [label="Invoke"]
n12.handle(right) -> n13.handle(left) [label="Read/Write"]
n12.handle(bottom) -> n14.handle(top) [label="Store"]
n15.handle(top) -> TrafficManager.n3.handle(bottom) [label="Health Check"]
}
DataSync { # Cross-Cloud Sync
n16: rectangle label:"Event Bridge"
n17: rectangle label:"Bi-Directional Replication"
n18: rectangle label:"Conflict Resolution"
n16.handle(right) -> n17.handle(left) [label="CDC Events"]
n17.handle(right) -> n18.handle(left) [label="Last-Write-Wins"]
n17.handle(top) -> AWS.n8.handle(bottom) [label="Sync"]
n17.handle(top) -> Azure.n13.handle(bottom) [label="Sync"]
}
Why This Workflow?
Relying on a single cloud provider creates vendor lock-in risk and single points of failure at the provider level. A multi-cloud serverless architecture distributes workloads across AWS and Azure, providing automatic failover, negotiating leverage, and compliance with data sovereignty requirements.
How It Works
- Step 1: A global traffic manager routes requests based on DNS health checks.
- Step 2: If the primary cloud (AWS) is healthy, traffic routes to AWS Lambda and DynamoDB.
- Step 3: If the primary fails health checks, traffic automatically fails over to Azure Functions and Cosmos DB.
- Step 4: Bi-directional data replication keeps both clouds synchronized.
- Step 5: Conflict resolution (last-write-wins) handles concurrent writes during split-brain scenarios.
- Step 6: Both clouds report health status back to the traffic manager for continuous monitoring.
Alternatives
Single-cloud with multi-region provides simpler redundancy within one provider. Kubernetes abstracts cloud differences but adds operational complexity. This template shows true multi-cloud failover with serverless services.
Key Facts
| Template Name | Serverless Multi-Cloud Architecture |
| Category | Architecture |
| Steps | 6 workflow steps |
| Format | FlowZap Code (.fz file) |
Related templates
Architecture
An AWS Step Functions orchestration architecture diagram with state machine workflows including choice states, parallel processing, wait-for-callback patterns, and compensation rollback for failed steps. This template models serverless workflow orchestration where complex multi-step processes are defined as state machines with built-in error handling and retry logic. Critical for teams building reliable serverless workflows that require human approval or long-running processes.
Architecture
A microservices API gateway architecture diagram showing request routing, JWT authentication, rate limiting, service discovery, and response aggregation across distributed backend services. This template models the entry point for all client traffic in a microservices ecosystem, enforcing security policies before requests reach internal services. Ideal for platform engineers designing scalable API infrastructure with centralized cross-cutting concerns.
Architecture
A service mesh architecture diagram with Istio or Linkerd sidecar proxies handling mTLS encryption, traffic policies, circuit breaking, and distributed tracing across microservices. This template visualizes how a service mesh abstracts networking concerns away from application code, enabling zero-trust communication between services. Essential for teams adopting service mesh infrastructure to improve observability and security.
Architecture
A database-per-service architecture diagram where each microservice owns its dedicated data store, with event-driven synchronization via Kafka for cross-service data consistency. This template demonstrates the core microservices data isolation principle, showing how PostgreSQL and MongoDB coexist in a polyglot persistence strategy. Critical for architects enforcing service autonomy while maintaining eventual consistency.
Architecture
A microservices decomposition architecture diagram organized by business capabilities: Identity, Product Catalog, Pricing, and Order Fulfillment, each with independent data stores and APIs. This template shows how to break a monolith into services aligned with business domains, using a Backend-for-Frontend (BFF) pattern for client-specific aggregation. Useful for architects planning domain-driven microservice boundaries.
Architecture
A strangler fig migration architecture diagram showing the incremental replacement of a legacy monolith with new microservices, using a routing layer to split traffic between old and new systems. This template models the proven migration strategy where new features are built as microservices while legacy endpoints are gradually retired. Essential for teams modernizing legacy systems without risky big-bang rewrites.