Monolith to Microservices Migration with Event-Driven Architecture
Decomposition strategy for a Node.js monolith into microservices with asynchronous message-based communication.
Plan and execute a gradual migration from monolith to microservices without service interruption, using asynchronous communication patterns with message queues.
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Prompt objective
Plan and execute a gradual migration from monolith to microservices without service interruption, using asynchronous communication patterns with message queues.
Real use case
A food delivery platform has a 280,000-line Express.js monolith processing 8,000 daily orders. Deploys take 45 minutes, a bug in the payment module brings down the entire system, and a 20-person team has constant merge conflicts.
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Prompt
Design the migration of [PROJECT NAME] monolith to microservices. The current system is built with [NODE.JS + EXPRESS/NESTJS] and [POSTGRESQL/MONGODB].\\\\\\\\n\\\\\\\\n**Current Monolith State:**\\\\\\\\n- Lines of code: [NUMBER]\\\\\\\\n- Main modules: [LIST: e.g., orders, payments, inventory, notifications, reports]\\\\\\\\n- Database: [SHARED/SEPARATE] with [NUMBER] tables\\\\\\\\n- Deploy: [FREQUENCY] with [DURATION] downtime\\\\\\\\n- Team: [NUMBER] developers in [NUMBER] squads\\\\\\\\n\\\\\\\\n**1) Domain Boundaries Analysis:**\\\\\\\\n- Bounded contexts mapping (DDD)\\\\\\\\n- Module coupling identification\\\\\\\\n- Domain dependency matrix\\\\\\\\n- Prioritization: which service to extract first (lowest risk, highest benefit)\\\\\\\\n\\\\\\\\n**2) Strangler Fig Pattern:**\\\\\\\\n- API Gateway as facade (Kong/AWS API Gateway/custom)\\\\\\\\n- Gradual routing: monolith → microservice by endpoint\\\\\\\\n- Feature flags for instant rollback\\\\\\\\n- Dual-write period (monolith + microservice)\\\\\\\\n- Cross-system consistency verification\\\\\\\\n\\\\\\\\n**3) Inter-Service Communication:**\\\\\\\\n- Synchronous: gRPC for internal queries (low latency)\\\\\\\\n- Asynchronous: RabbitMQ/SQS for domain events\\\\\\\\n- Event schema registry (event versioning)\\\\\\\\n- Saga pattern for distributed transactions (e.g., order → payment → inventory)\\\\\\\\n- Dead letter queue for failed events\\\\\\\\n- Consumer idempotency\\\\\\\\n\\\\\\\\n**4) Data Strategy:**\\\\\\\\n- Database per service (isolation)\\\\\\\\n- Shared database data migration\\\\\\\\n- Event sourcing for audit trail\\\\\\\\n- CQRS for read-intensive services (reports)\\\\\\\\n- Eventual consistency: handling in the frontend\\\\\\\\n\\\\\\\\n**5) Infrastructure:**\\\\\\\\n- Container per service (Docker)\\\\\\\\n- Orchestration: [KUBERNETES/ECS/DOCKER COMPOSE]\\\\\\\\n- Service discovery and load balancing\\\\\\\\n- Distributed tracing (Jaeger/Datadog)\\\\\\\\n- Centralized logging (ELK/Grafana Loki)\\\\\\\\n- Health checks and circuit breakers\\\\\\\\n\\\\\\\\n**6) Migration Timeline:**\\\\\\\\n- Phase 1 (months 1-2): Infrastructure + first service\\\\\\\\n- Phase 2 (months 3-4): [NUMBER] critical services\\\\\\\\n- Phase 3 (months 5-6): Remaining services + monolith decommission\\\\\\\\n- Risks and mitigations per phase
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