Start by defining microservices as independently deployable services organized around business capabilities, then walk through the architecture from client to services to data stores. Explain communication patterns (synchronous vs asynchronous) and coordination mechanisms (service discovery, API gateway, orchestration/choreography), and finish by discussing trade-offs like complexity, latency, and consistency.
Pro tip: Anchor your answer in a concrete example (e.g., an e-commerce order flow) and explicitly contrast microservices with a monolith to show you understand when the architecture is worth its operational cost.
Briefly define microservices as small, independently deployable services owning their own data, and state why organizations adopt them: independent scaling, team autonomy, and fault isolation.
Walk through the layers: clients, API gateway/BFF, service mesh or load balancer, individual services, and per-service databases. Mention infrastructure concerns like containers, orchestration (Kubernetes), and observability.
Cover synchronous communication (REST, gRPC) for request/response and asynchronous communication (message queues, event streaming like Kafka) for decoupling and resilience. Discuss when to use each.
Describe service discovery (client-side vs server-side), API gateway routing, and coordination patterns: orchestration (central controller) vs choreography (event-driven). Mention sagas for distributed transactions.
Highlight challenges: network latency, partial failures, data consistency (eventual consistency), debugging complexity, and operational overhead. Explain how patterns like circuit breakers, retries, and idempotency mitigate them.
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