microservice cheat sheet

Absolutely! Here’s a Microservices Interview One-Liners Cheat Sheet — built for real-world Java/Spring Boot microservices interviews (3–6 years experience), especially useful for last-minute revision.





⚡ Microservices Interview One-Liners (Spring Boot Focused)






🔹 Microservices Basics



  • Microservices = independent, small, loosely-coupled services focused on a single business capability.
  • Communication is via REST APIs, gRPC, messaging queues, etc.
  • They can be developed, deployed, and scaled independently.
  • Avoid shared DB — use database-per-service pattern.






🔹 Service Communication



  • Synchronous: REST, gRPC.
  • Asynchronous: Kafka, RabbitMQ, JMS.
  • DTOs (Data Transfer Objects) are used for API request/response.






🔹 API Gateway



  • Handles routing, authentication, rate limiting, and logging.
  • Common tools: Spring Cloud Gateway, Zuul, Kong, NGINX.
  • Reduces coupling between clients and services.






🔹 Service Discovery



  • Services register with Eureka or Consul.
  • Other services discover them using logical names, not hardcoded URLs.
  • @EnableEurekaClient and @LoadBalanced RestTemplate for Spring Cloud.






🔹 Load Balancing



  • Client-side: Ribbon (deprecated), Spring Cloud LoadBalancer (new).
  • Server-side: handled by API Gateway or Kubernetes services.






🔹 Configuration Management



  • Spring Cloud Config Server externalizes configuration.
  • Configs stored in Git, File System, or Vault.
  • Use @RefreshScope to refresh beans at runtime on config update.






🔹 Fault Tolerance



  • Resilience4j, Hystrix (deprecated) handle retries, circuit breaking.
  • Circuit Breaker avoids repeated failures by temporarily cutting the flow.
  • @CircuitBreaker, @Retry, @RateLimiter in Resilience4j.






🔹 Distributed Tracing



  • Tools: Zipkin, Sleuth, Jaeger.
  • TraceId and SpanId help track requests across services.
  • Use Sleuth with Zipkin in Spring Boot: spring-cloud-starter-sleuth.






🔹 Centralized Logging



  • Tools: ELK Stack (Elasticsearch, Logstash, Kibana), EFK, Graylog.
  • Helps in tracing errors and debugging across microservices.
  • Logs typically include service name, timestamp, trace ID.






🔹 Security in Microservices



  • Use OAuth2 + JWT for stateless authentication.
  • Gateway handles authentication, downstream services do authorization.
  • @PreAuthorize("hasRole('ADMIN')") for role-based access.






🔹 Data Management Patterns



  • Database per service — recommended for loose coupling.
  • Shared database — not recommended, breaks service independence.
  • SAGA Pattern handles distributed transactions via local transactions + event-based coordination.






🔹 Inter-Service Communication



  • RESTTemplate (deprecated) → replaced by WebClient.
  • FeignClient simplifies REST calls between services (declarative client).
  • Use @FeignClient(name="order-service") in Spring Cloud.






🔹 Event-Driven Architecture



  • Services publish/subscribe via Kafka, RabbitMQ, etc.
  • Promotes loose coupling and asynchronous behavior.
  • Best for high throughput, non-blocking, decoupled communication.






🔹 CI/CD & DevOps



  • Containerized via Docker, orchestrated using Kubernetes.
  • Pipelines (Jenkins, GitHub Actions, GitLab CI) automate build-deploy-test cycle.
  • Use Helm Charts for Kubernetes deployments.






🔹 Testing in Microservices



  • Unit Tests for components using JUnit/Mockito.
  • Integration Tests use @SpringBootTest.
  • Contract Testing: ensures API compatibility between services (Spring Cloud Contract).
  • End-to-End Testing simulates real user behavior across multiple services.






🔹 Versioning & Backward Compatibility



  • URL versioning (/api/v1/users) or header-based versioning.
  • Always maintain backward compatibility when updating APIs.






🔹 Observability & Metrics



  • Expose /actuator/metrics with Micrometer.
  • Integrate with Prometheus and Grafana for monitoring.
  • Health checks: /actuator/health






🔹 Best Practices



  • Each service should be autonomous, independently deployable, and resilient.
  • Avoid shared state — use stateless services where possible.
  • Handle failures gracefully with timeouts, retries, and circuit breakers.
  • Prefer API Gateway, centralized logging, and distributed tracing in production.





✅ You’re now covered for:


  • Microservices architecture
  • Spring Cloud components
  • Resilience and observability
  • Secure, scalable service-to-service interaction
  • DevOps and testing strategies




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