Practice service decomposition, API gateways, and distributed architecture patterns
Start Practicing NowMaster service boundaries, domain-driven design, and decomposition
Learn REST, gRPC, message brokers, and service mesh
Understand distributed transactions, monitoring, and debugging
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Service decomposition strategies
API gateway and service mesh
Inter-service communication (REST, gRPC)
Event-driven architecture and messaging
Distributed tracing and monitoring
Service discovery and configuration
A: Avoid if possible. Patterns: Saga pattern (choreography with events or orchestration with coordinator), eventual consistency, compensating transactions. Two-phase commit doesn't scale. Use idempotent operations, event sourcing, outbox pattern. Accept eventual consistency. Design for failure with retries and compensation logic.
A: Client-side discovery: client queries service registry (Consul, Eureka), calls service directly. Server-side discovery: load balancer queries registry, routes request. Kubernetes uses DNS-based discovery. Trade-offs: client-side more network hops awareness, server-side simpler clients. Health checks required for both.
A: Synchronous: REST (simple, HTTP), gRPC (efficient, protobuf, streaming). Asynchronous: message queues (RabbitMQ, Kafka), event-driven. Use sync for request-response, async for event notifications. Consider circuit breakers, retries, timeouts. gRPC for internal high-performance, REST for public APIs. Event-driven for decoupling.
A: API Gateway is single entry point for clients. Handles: routing, authentication, rate limiting, request/response transformation, protocol translation. Benefits: decouples clients from services, reduces round trips (aggregation), centralizes cross-cutting concerns. Examples: Kong, Ambassador, AWS API Gateway. Alternative: Backend for Frontend (BFF) pattern.
Understand the trade-offs between microservices and monoliths
Master distributed tracing tools like Jaeger or Zipkin
Know how to decompose services by business capability or subdomain (DDD)
Practice with circuit breaker pattern and resilience libraries
Understand eventual consistency and how to design for it
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