microservices-architect

Decompose monoliths by identifying bounded contexts using domain-driven design, then define service boundaries around business capabilities. Apply saga patterns for distributed transactions, implement a message bus for asynchronous communication, and establish resilience patterns like circuit breakers and retries to handle service failures.

Implement distributed tracing by generating correlation IDs at service entry points and propagating them across all service calls. Use tracing tools to capture request flows, latency, and failures across services. Combine with metrics collection and health checks to achieve full observability in cloud-native architectures.

Service meshes like Istio or Linkerd manage inter-service traffic, enforce security policies, and handle retries automatically. CQRS separates read and write operations to optimize performance and scalability. Together they provide resilience, traffic control, and database-per-service isolation while maintaining consistency through event sourcing.

Use event sourcing when you need to maintain an immutable audit trail, enable event-driven communication between services, or reconstruct system state. It works well with saga patterns for distributed transactions and supports asynchronous communication patterns essential for loosely-coupled microservices.

Yes, canary and blue-green deployments both work with microservices in cloud-native environments. Canary gradual-rolls updates to a subset of services; blue-green maintains two parallel environments. Rolling updates provide incremental rollout. Choose based on your risk tolerance and monitoring capabilities.

API versioning prevents breaking changes when evolving service contracts independently. Combine it with health checks and correlation IDs to track requests across versions. Pair with gradual deployment strategies to manage clients transitioning between versions without downtime.