microservices-architect

To decompose a monolith into microservices, identify bounded contexts and aggregate boundaries from your business domains to define autonomous service candidates. Analyze key business workflows to ensure service boundaries align with domain logic and independent scaling requirements.

For distributed data consistency in microservices, implement the saga pattern or CQRS. Combine these with a database-per-service ownership model and event-driven flows to maintain data integrity without relying on distributed two-phase commits.

Handle partial failures in cloud-native microservices by implementing circuit breakers, retries, bulkheads, and health probes. Integrate a service mesh like Istio for traffic control to prevent cascading failures across your distributed system.

Yes, this microservices architecture approach applies directly to cloud-native systems and Kubernetes deployments. It supports service mesh integration, enabling advanced traffic control, automated retries, and secure inter-service communication.

Implement observability in microservices by instrumenting distributed tracing across inter-service communication patterns. Define health probes and leverage service mesh integration to monitor traffic, latency, and transaction flows in production environments.

Use event-driven architecture for decoupled, asynchronous workflows like order processing, and synchronous communication for immediate request-response needs. The choice depends on your specific inter-service communication patterns and consistency requirements.