springboot-patterns
affaan-m/ecc
Spring Boot architecture patterns, REST API design, layered services, and production-grade backend patterns.
What is springboot-patterns?
Reference patterns for building scalable Spring Boot REST APIs with layered architecture, data access, caching, async processing, and logging. Use when structuring controllers, services, repositories, and configuring Spring Data JPA, validation, exception handling, and environment profiles.
- REST API structure with controllers, pagination, and response mapping
- Repository pattern with Spring Data JPA and custom queries
- Service layer with transactional boundaries and business logic
- DTO validation using Jakarta Bean Validation annotations
- Global exception handling with ControllerAdvice
- Caching with @Cacheable and @CacheEvict decorators
How to install springboot-patterns
npx skills add null --skill springboot-patterns- Spring Boot 2.7+ or 3.0+ project
- Spring Data JPA dependency for repository pattern
- Spring Web (MVC or WebFlux) for REST controllers
- Jakarta Bean Validation (javax.validation) for DTO validation
- SLF4J and Logback (included by default in Spring Boot)
- Optional: bucket4j library for rate limiting
How to use springboot-patterns
- 1.Review the REST API structure example to understand controller → service → repository layering
- 2.Apply the DTO and validation patterns to your request/response classes
- 3.Implement a global exception handler using @ControllerAdvice for consistent error responses
- 4.Add @Transactional to service methods that modify data
- 5.Enable caching with @EnableCaching and decorate frequently-accessed methods with @Cacheable
- 6.Enable async processing with @EnableAsync for non-blocking operations
- 7.Add request logging filters extending OncePerRequestFilter for observability
- 8.Implement rate limiting filters with bucket4j, ensuring proper client IP detection behind proxies
Use cases
- Building paginated REST endpoints with proper HTTP status codes and response DTOs
- Implementing transactional service methods that coordinate repository operations
- Adding request/response logging and performance monitoring via filters
- Configuring caching strategies for frequently accessed entities
- Handling validation errors and authorization failures with consistent error responses
- Java backend engineers building Spring Boot microservices
- Teams standardizing REST API design and layered architecture
- Developers implementing caching, async processing, or rate limiting
- Engineers setting up production-grade logging and error handling
springboot-patterns FAQ
Use @Transactional on methods that modify data (create, update, delete) to ensure ACID properties. Spring will automatically commit on success or rollback on exceptions. Avoid on read-only queries unless you need a specific isolation level.
Configure server.forward-headers-strategy=NATIVE (cloud platforms) or FRAMEWORK in application.properties. If using FRAMEWORK, register ForwardedHeaderFilter as a bean. Ensure your proxy overwrites (not appends) X-Forwarded-For headers to prevent spoofing. Then request.getRemoteAddr() will return the correct client IP.
@Cacheable checks the cache before executing the method; if found, returns cached value. @CacheEvict removes entries from the cache after method execution. Use @Cacheable for read operations and @CacheEvict when data changes.
Accept page and size parameters in your controller, create a PageRequest.of(page, size), pass it to your service, and return a Page<DTO>. Spring Data JPA handles the offset/limit SQL automatically. Always provide defaults (e.g., page=0, size=20).
Use INFO for significant business events (user created, payment processed). Use DEBUG for detailed diagnostic info (method entry/exit, variable values). Use ERROR for exceptions with stack traces. This keeps production logs readable while preserving detail in development.
Full instructions (SKILL.md)
Source of truth, from affaan-m/ecc.
name: springboot-patterns description: Spring Boot architecture patterns, REST API design, layered services, data access, caching, async processing, and logging. Use for Java Spring Boot backend work. metadata: origin: ECC
Spring Boot Development Patterns
Spring Boot architecture and API patterns for scalable, production-grade services.
When to Activate
- Building REST APIs with Spring MVC or WebFlux
- Structuring controller → service → repository layers
- Configuring Spring Data JPA, caching, or async processing
- Adding validation, exception handling, or pagination
- Setting up profiles for dev/staging/production environments
- Implementing event-driven patterns with Spring Events or Kafka
REST API Structure
@RestController
@RequestMapping("/api/markets")
@Validated
class MarketController {
private final MarketService marketService;
MarketController(MarketService marketService) {
this.marketService = marketService;
}
@GetMapping
ResponseEntity<Page<MarketResponse>> list(
@RequestParam(defaultValue = "0") int page,
@RequestParam(defaultValue = "20") int size) {
Page<Market> markets = marketService.list(PageRequest.of(page, size));
return ResponseEntity.ok(markets.map(MarketResponse::from));
}
@PostMapping
ResponseEntity<MarketResponse> create(@Valid @RequestBody CreateMarketRequest request) {
Market market = marketService.create(request);
return ResponseEntity.status(HttpStatus.CREATED).body(MarketResponse.from(market));
}
}
Repository Pattern (Spring Data JPA)
public interface MarketRepository extends JpaRepository<MarketEntity, Long> {
@Query("select m from MarketEntity m where m.status = :status order by m.volume desc")
List<MarketEntity> findActive(@Param("status") MarketStatus status, Pageable pageable);
}
Service Layer with Transactions
@Service
public class MarketService {
private final MarketRepository repo;
public MarketService(MarketRepository repo) {
this.repo = repo;
}
@Transactional
public Market create(CreateMarketRequest request) {
MarketEntity entity = MarketEntity.from(request);
MarketEntity saved = repo.save(entity);
return Market.from(saved);
}
}
DTOs and Validation
public record CreateMarketRequest(
@NotBlank @Size(max = 200) String name,
@NotBlank @Size(max = 2000) String description,
@NotNull @FutureOrPresent Instant endDate,
@NotEmpty List<@NotBlank String> categories) {}
public record MarketResponse(Long id, String name, MarketStatus status) {
static MarketResponse from(Market market) {
return new MarketResponse(market.id(), market.name(), market.status());
}
}
Exception Handling
@ControllerAdvice
class GlobalExceptionHandler {
@ExceptionHandler(MethodArgumentNotValidException.class)
ResponseEntity<ApiError> handleValidation(MethodArgumentNotValidException ex) {
String message = ex.getBindingResult().getFieldErrors().stream()
.map(e -> e.getField() + ": " + e.getDefaultMessage())
.collect(Collectors.joining(", "));
return ResponseEntity.badRequest().body(ApiError.validation(message));
}
@ExceptionHandler(AccessDeniedException.class)
ResponseEntity<ApiError> handleAccessDenied() {
return ResponseEntity.status(HttpStatus.FORBIDDEN).body(ApiError.of("Forbidden"));
}
@ExceptionHandler(Exception.class)
ResponseEntity<ApiError> handleGeneric(Exception ex) {
// Log unexpected errors with stack traces
return ResponseEntity.status(HttpStatus.INTERNAL_SERVER_ERROR)
.body(ApiError.of("Internal server error"));
}
}
Caching
Requires @EnableCaching on a configuration class.
@Service
public class MarketCacheService {
private final MarketRepository repo;
public MarketCacheService(MarketRepository repo) {
this.repo = repo;
}
@Cacheable(value = "market", key = "#id")
public Market getById(Long id) {
return repo.findById(id)
.map(Market::from)
.orElseThrow(() -> new EntityNotFoundException("Market not found"));
}
@CacheEvict(value = "market", key = "#id")
public void evict(Long id) {}
}
Async Processing
Requires @EnableAsync on a configuration class.
@Service
public class NotificationService {
@Async
public CompletableFuture<Void> sendAsync(Notification notification) {
// send email/SMS
return CompletableFuture.completedFuture(null);
}
}
Logging (SLF4J)
@Service
public class ReportService {
private static final Logger log = LoggerFactory.getLogger(ReportService.class);
public Report generate(Long marketId) {
log.info("generate_report marketId={}", marketId);
try {
// logic
} catch (Exception ex) {
log.error("generate_report_failed marketId={}", marketId, ex);
throw ex;
}
return new Report();
}
}
Middleware / Filters
@Component
public class RequestLoggingFilter extends OncePerRequestFilter {
private static final Logger log = LoggerFactory.getLogger(RequestLoggingFilter.class);
@Override
protected void doFilterInternal(HttpServletRequest request, HttpServletResponse response,
FilterChain filterChain) throws ServletException, IOException {
long start = System.currentTimeMillis();
try {
filterChain.doFilter(request, response);
} finally {
long duration = System.currentTimeMillis() - start;
log.info("req method={} uri={} status={} durationMs={}",
request.getMethod(), request.getRequestURI(), response.getStatus(), duration);
}
}
}
Pagination and Sorting
PageRequest page = PageRequest.of(pageNumber, pageSize, Sort.by("createdAt").descending());
Page<Market> results = marketService.list(page);
Error-Resilient External Calls
public <T> T withRetry(Supplier<T> supplier, int maxRetries) {
int attempts = 0;
while (true) {
try {
return supplier.get();
} catch (Exception ex) {
attempts++;
if (attempts >= maxRetries) {
throw ex;
}
try {
Thread.sleep((long) Math.pow(2, attempts) * 100L);
} catch (InterruptedException ie) {
Thread.currentThread().interrupt();
throw ex;
}
}
}
}
Rate Limiting (Filter + Bucket4j)
Security Note: The X-Forwarded-For header is untrusted by default because clients can spoof it.
Only use forwarded headers when:
- Your app is behind a trusted reverse proxy (nginx, AWS ALB, etc.)
- You have registered
ForwardedHeaderFilteras a bean - You have configured
server.forward-headers-strategy=NATIVEorFRAMEWORKin application properties - Your proxy is configured to overwrite (not append to) the
X-Forwarded-Forheader
When ForwardedHeaderFilter is properly configured, request.getRemoteAddr() will automatically
return the correct client IP from the forwarded headers. Without this configuration, use
request.getRemoteAddr() directly—it returns the immediate connection IP, which is the only
trustworthy value.
@Component
public class RateLimitFilter extends OncePerRequestFilter {
private final Map<String, Bucket> buckets = new ConcurrentHashMap<>();
/*
* SECURITY: This filter uses request.getRemoteAddr() to identify clients for rate limiting.
*
* If your application is behind a reverse proxy (nginx, AWS ALB, etc.), you MUST configure
* Spring to handle forwarded headers properly for accurate client IP detection:
*
* 1. Set server.forward-headers-strategy=NATIVE (for cloud platforms) or FRAMEWORK in
* application.properties/yaml
* 2. If using FRAMEWORK strategy, register ForwardedHeaderFilter:
*
* @Bean
* ForwardedHeaderFilter forwardedHeaderFilter() {
* return new ForwardedHeaderFilter();
* }
*
* 3. Ensure your proxy overwrites (not appends) the X-Forwarded-For header to prevent spoofing
* 4. Configure server.tomcat.remoteip.trusted-proxies or equivalent for your container
*
* Without this configuration, request.getRemoteAddr() returns the proxy IP, not the client IP.
* Do NOT read X-Forwarded-For directly—it is trivially spoofable without trusted proxy handling.
*/
@Override
protected void doFilterInternal(HttpServletRequest request, HttpServletResponse response,
FilterChain filterChain) throws ServletException, IOException {
// Use getRemoteAddr() which returns the correct client IP when ForwardedHeaderFilter
// is configured, or the direct connection IP otherwise. Never trust X-Forwarded-For
// headers directly without proper proxy configuration.
String clientIp = request.getRemoteAddr();
Bucket bucket = buckets.computeIfAbsent(clientIp,
k -> Bucket.builder()
.addLimit(Bandwidth.classic(100, Refill.greedy(100, Duration.ofMinutes(1))))
.build());
if (bucket.tryConsume(1)) {
filterChain.doFilter(request, response);
} else {
response.setStatus(HttpStatus.TOO_MANY_REQUESTS.value());
}
}
}
Background Jobs
Use Spring’s @Scheduled or integrate with queues (e.g., Kafka, SQS, RabbitMQ). Keep handlers idempotent and observable.
Observability
- Structured logging (JSON) via Logback encoder
- Metrics: Micrometer + Prometheus/OTel
- Tracing: Micrometer Tracing with OpenTelemetry or Brave backend
Production Defaults
- Prefer constructor injection, avoid field injection
- Enable
spring.mvc.problemdetails.enabled=truefor RFC 7807 errors (Spring Boot 3+) - Configure HikariCP pool sizes for workload, set timeouts
- Use
@Transactional(readOnly = true)for queries - Enforce null-safety via
@NonNullandOptionalwhere appropriate
Remember: Keep controllers thin, services focused, repositories simple, and errors handled centrally. Optimize for maintainability and testability.
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