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
Notes are being added. Planned topics:
| Topic | Description |
|---|---|
| SOLID Principles | Single Responsibility, Open/Closed, Liskov, Interface Segregation, Dependency Inversion. |
| Microservices | Service decomposition, inter-service communication (REST vs. messaging), eventual consistency. |
| API Design | REST vs. gRPC vs. GraphQL; versioning; pagination; rate limiting. |
| Caching Strategies | Cache-aside, write-through, write-behind; eviction policies; cache stampede. |
| Reliability Patterns | Circuit Breaker (Resilience4j), Retry, Bulkhead, Timeout, Rate Limiter. |
| Distributed Systems | CAP theorem, consistency models, idempotency, distributed transactions (Saga pattern). |
| Scalability Patterns | Horizontal vs. vertical scaling, stateless services, read replicas, sharding. |
Learning Path
- SOLID Principles — these are the “grammar” of good OOP design; expected at every level.
- Caching Strategies — cache-aside with Redis is the most common pattern; understand eviction and consistency trade-offs.
- Reliability Patterns — Circuit Breaker and Retry with Resilience4j appear in almost every microservices setup.
- Microservices — service decomposition trade-offs and inter-service communication choices are standard interview questions.
- Distributed Systems — CAP theorem, eventual consistency, and Saga are senior-level topics.
Related Domains
- 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.