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System Design

System design interviews test your ability to trade off between correctness, performance, scalability, and maintainability at the architecture level. For senior Java/Spring Boot engineers, this means understanding microservices trade-offs, database selection, caching strategies, API design, and reliability patterns (circuit breaker, retry, bulkhead, rate limiting).

What You'll Find Here​

NoteDescription
SOLID PrinciplesFive OOP design principles — SRP, OCP, LSP, ISP, DIP — that reduce coupling and improve testability.
MicroservicesService decomposition, database-per-service, service discovery, and async communication patterns.
API DesignREST resource modeling, versioning, pagination, structured error responses, REST vs gRPC vs GraphQL.
Caching StrategiesCache-aside, write-through, write-behind; eviction policies; TTL design; cache stampede prevention.
Reliability PatternsCircuit Breaker, Retry, Bulkhead, Timeout, and Rate Limiter with Resilience4j in Spring Boot.
Distributed SystemsCAP theorem, consistency models, idempotency, and distributed transactions via the Saga pattern.
Scalability PatternsHorizontal vs vertical scaling, stateless services, read replicas, sharding, async offloading.

Learning Path​

A suggested reading order for a returning Java developer preparing for senior backend interviews:

  1. SOLID Principles — the "grammar" of good OOP design; expected at every level of interview.
  2. API Design — REST semantics, versioning, and error contracts are foundational before discussing services.
  3. Caching Strategies — cache-aside with Redis is the most common pattern; understand eviction and consistency trade-offs.
  4. Reliability Patterns — Circuit Breaker and Retry with Resilience4j appear in almost every microservices setup.
  5. Microservices — service decomposition trade-offs and inter-service communication choices are standard senior questions.
  6. Distributed Systems — CAP theorem, eventual consistency, and Saga are advanced topics; build on the microservices foundation.
  7. Scalability Patterns — horizontal scaling, stateless session, and read replicas complete the picture for large-scale system design.
  • Spring Boot — most distributed system patterns have Spring Boot implementation examples.
  • Messaging — Saga and event-driven architectures rely on Kafka or RabbitMQ.
  • Databases — database selection, sharding, and replication are system design concerns.

Demos​

Hands-on, runnable demos for common System Design scenarios:

DemoWhat It Shows
SOLID Principles — Practical DemoSRP, OCP, LSP, ISP, and DIP applied to a notification system with refactors and Spring wiring.
Microservices — Practical DemoE‑commerce order flow: Kafka events, persist-before-publish, idempotent consumers, and compensation handling.
API Design — Practical DemoVersioned APIs, cursor pagination examples, OpenAPI integration, and RFC 7807 error handling.
Caching Strategies — Practical DemoCache-aside vs write-through examples, TTL jitter, mutex protection, and common pitfalls.
Reliability Patterns — Practical DemoResilience4j: circuit breaker, retry, bulkhead, timeouts, and testing patterns.
Distributed Systems — Practical DemoChoreography-based Saga, idempotency keys, compensating transactions, and event design.
Scalability Patterns — Practical DemoRedis session migration, HikariCP tuning, read-replica routing, and async offloading with metrics.