springboot-patterns

Structure a Spring Boot REST API using a controller-service-repository layering pattern, applying @RestController DTO validation, Spring Data JPA repository queries, and transactional boundaries to handle data access and pagination safely.

The best way to add caching and async processing to Spring Boot services is by applying configuration hooks for caching and async tasks, enabling background jobs and cross-cutting execution without blocking main controller threads.

Implement global exception handling and request logging in Spring Boot by applying centralized exception management and filter-based middleware, capturing structured logs and metrics for observability across REST API endpoints.

Yes, these Spring Boot architecture patterns support production cross-cutting concerns including rate limiting and retry logic, designed to build scalable REST APIs with resilient data access and observability.

You need @Transactional boundaries in Spring Data JPA when defining service layer patterns to ensure safe API responses and reliable data access, encapsulating repository queries and DTO mapping within consistent database transactions.