spring-boot-resilience4j

SKILL.md

Spring Boot Resilience4j Patterns

Overview

Provides Resilience4j patterns (circuit breaker, retry, rate limiter, bulkhead, time limiter, fallback) for Spring Boot 3.x fault tolerance with configuration and testing workflows.

When to Use

Implementing fault tolerance and preventing cascading failures

Adding circuit breakers, retry logic, or rate limiting to service calls

Handling transient failures with exponential backoff

Protecting services from overload and resource exhaustion

Combining multiple patterns for comprehensive resilience

Instructions

1. Setup and Dependencies

Add Resilience4j dependencies to your project. For Maven, add to pom.xml:
<dependency>
    <groupId>io.github.resilience4j</groupId>
    <artifactId>resilience4j-spring-boot3</artifactId>
    <version>2.2.0</version> // Use latest stable version
</dependency>
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-aop</artifactId>
</dependency>
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-actuator</artifactId>
</dependency>

For Gradle, add to build.gradle:

implementation "io.github.resilience4j:resilience4j-spring-boot3:2.2.0"
implementation "org.springframework.boot:spring-boot-starter-aop"
implementation "org.springframework.boot:spring-boot-starter-actuator"

Enable AOP annotation processing with @EnableAspectJAutoProxy (auto-configured by Spring Boot).

2. Circuit Breaker Pattern

Apply @CircuitBreaker annotation to methods calling external services:

@Service
public class PaymentService {
    private final RestTemplate restTemplate;

    public PaymentService(RestTemplate restTemplate) {
        this.restTemplate = restTemplate;
    }

    @CircuitBreaker(name = "paymentService", fallbackMethod = "paymentFallback")
    public PaymentResponse processPayment(PaymentRequest request) {
        return restTemplate.postForObject("http://payment-api/process",
            request, PaymentResponse.class);
    }

    private PaymentResponse paymentFallback(PaymentRequest request, Exception ex) {
        return PaymentResponse.builder()
            .status("PENDING")
            .message("Service temporarily unavailable")
            .build();
    }
}

Configure in application.yml:

resilience4j:
  circuitbreaker:
    configs:
      default:
        registerHealthIndicator: true
        slidingWindowSize: 10
        minimumNumberOfCalls: 5
        failureRateThreshold: 50
        waitDurationInOpenState: 10s
    instances:
      paymentService:
        baseConfig: default

See @references/configuration-reference.md for complete circuit breaker configuration options.

3. Retry Pattern

Apply @Retry annotation for transient failure recovery:

@Service
public class ProductService {
    private final RestTemplate restTemplate;

    public ProductService(RestTemplate restTemplate) {
        this.restTemplate = restTemplate;
    }

    @Retry(name = "productService", fallbackMethod = "getProductFallback")
    public Product getProduct(Long productId) {
        return restTemplate.getForObject(
            "http://product-api/products/" + productId,
            Product.class);
    }

    private Product getProductFallback(Long productId, Exception ex) {
        return Product.builder()
            .id(productId)
            .name("Unavailable")
            .available(false)
            .build();
    }
}

Configure retry in application.yml:

resilience4j:
  retry:
    configs:
      default:
        maxAttempts: 3
        waitDuration: 500ms
        enableExponentialBackoff: true
        exponentialBackoffMultiplier: 2
    instances:
      productService:
        baseConfig: default
        maxAttempts: 5

See @references/configuration-reference.md for retry exception configuration.

4. Rate Limiter Pattern

Apply @RateLimiter to control request rates:

@Service
public class NotificationService {
    private final EmailClient emailClient;

    public NotificationService(EmailClient emailClient) {
        this.emailClient = emailClient;
    }

    @RateLimiter(name = "notificationService",
        fallbackMethod = "rateLimitFallback")
    public void sendEmail(EmailRequest request) {
        emailClient.send(request);
    }

    private void rateLimitFallback(EmailRequest request, Exception ex) {
        throw new RateLimitExceededException(
            "Too many requests. Please try again later.");
    }
}

Configure in application.yml:

resilience4j:
  ratelimiter:
    configs:
      default:
        registerHealthIndicator: true
        limitForPeriod: 10
        limitRefreshPeriod: 1s
        timeoutDuration: 500ms
    instances:
      notificationService:
        baseConfig: default
        limitForPeriod: 5

5. Bulkhead Pattern

Apply @Bulkhead to isolate resources. Use type = SEMAPHORE for synchronous methods:

@Service
public class ReportService {
    private final ReportGenerator reportGenerator;

    public ReportService(ReportGenerator reportGenerator) {
        this.reportGenerator = reportGenerator;
    }

    @Bulkhead(name = "reportService", type = Bulkhead.Type.SEMAPHORE)
    public Report generateReport(ReportRequest request) {
        return reportGenerator.generate(request);
    }
}

Use type = THREADPOOL for async/CompletableFuture methods:

@Service
public class AnalyticsService {
    @Bulkhead(name = "analyticsService", type = Bulkhead.Type.THREADPOOL)
    public CompletableFuture<AnalyticsResult> runAnalytics(
            AnalyticsRequest request) {
        return CompletableFuture.supplyAsync(() ->
            analyticsEngine.analyze(request));
    }
}

Configure in application.yml:

resilience4j:
  bulkhead:
    configs:
      default:
        maxConcurrentCalls: 10
        maxWaitDuration: 100ms
    instances:
      reportService:
        baseConfig: default
        maxConcurrentCalls: 5

  thread-pool-bulkhead:
    instances:
      analyticsService:
        maxThreadPoolSize: 8

6. Time Limiter Pattern

Apply @TimeLimiter to async methods to enforce timeout boundaries:

@Service
public class SearchService {
    @TimeLimiter(name = "searchService", fallbackMethod = "searchFallback")
    public CompletableFuture<SearchResults> search(SearchQuery query) {
        return CompletableFuture.supplyAsync(() ->
            searchEngine.executeSearch(query));
    }

    private CompletableFuture<SearchResults> searchFallback(
            SearchQuery query, Exception ex) {
        return CompletableFuture.completedFuture(
            SearchResults.empty("Search timed out"));
    }
}

Configure in application.yml:

resilience4j:
  timelimiter:
    configs:
      default:
        timeoutDuration: 2s
        cancelRunningFuture: true
    instances:
      searchService:
        baseConfig: default
        timeoutDuration: 3s

7. Combining Multiple Patterns

Stack multiple patterns on a single method for comprehensive fault tolerance:

@Service
public class OrderService {
    @CircuitBreaker(name = "orderService")
    @Retry(name = "orderService")
    @RateLimiter(name = "orderService")
    @Bulkhead(name = "orderService")
    public Order createOrder(OrderRequest request) {
        return orderClient.createOrder(request);
    }
}

Execution order: Retry → CircuitBreaker → RateLimiter → Bulkhead → Method

All patterns should reference the same named configuration instance for consistency.

8. Exception Handling and Monitoring

Create a global exception handler using @RestControllerAdvice:

@RestControllerAdvice
public class ResilienceExceptionHandler {

    @ExceptionHandler(CallNotPermittedException.class)
    @ResponseStatus(HttpStatus.SERVICE_UNAVAILABLE)
    public ErrorResponse handleCircuitOpen(CallNotPermittedException ex) {
        return new ErrorResponse("SERVICE_UNAVAILABLE",
            "Service currently unavailable");
    }

    @ExceptionHandler(RequestNotPermitted.class)
    @ResponseStatus(HttpStatus.TOO_MANY_REQUESTS)
    public ErrorResponse handleRateLimited(RequestNotPermitted ex) {
        return new ErrorResponse("TOO_MANY_REQUESTS",
            "Rate limit exceeded");
    }

    @ExceptionHandler(BulkheadFullException.class)
    @ResponseStatus(HttpStatus.SERVICE_UNAVAILABLE)
    public ErrorResponse handleBulkheadFull(BulkheadFullException ex) {
        return new ErrorResponse("CAPACITY_EXCEEDED",
            "Service at capacity");
    }
}

Enable Actuator endpoints for monitoring resilience patterns in application.yml:

management:
  endpoints:
    web:
      exposure:
        include: health,metrics,circuitbreakers,retries,ratelimiters
  endpoint:
    health:
      show-details: always
  health:
    circuitbreakers:
      enabled: true
    ratelimiters:
      enabled: true

Access monitoring endpoints:

GET /actuator/health - Overall health including resilience patterns

GET /actuator/circuitbreakers - Circuit breaker states

GET /actuator/metrics - Custom resilience metrics

Testing & Verification Workflow

Circuit Breaker: Call endpoint with failures → check GET /actuator/circuitbreakers shows OPEN → wait waitDurationInOpenState → verify state transitions to HALF_OPEN → CLOSED

Retry: Enable resilience4j.retry.metrics.enabled: true → invoke endpoint → verify retry.{instance}.successful-calls-with-retry-attempts metric increases

Rate Limiter: Send requests exceeding limitForPeriod → verify 429 status → check GET /actuator/ratelimiters shows LIMITED

Bulkhead: Load test with concurrent requests exceeding maxConcurrentCalls → verify excess requests fail immediately with BulkheadFullException

Time Limiter: Mock async delay beyond timeoutDuration → verify fallback triggers after timeout

See @references/testing-patterns.md for unit and integration testing strategies.

Best Practices

Provide fallback methods: Ensure graceful degradation with meaningful responses

Use exponential backoff: Prevent overwhelming recovering services (exponentialBackoffMultiplier: 2)

Set appropriate thresholds: failureRateThreshold between 50-70%

Use constructor injection: Never use field injection for Resilience4j dependencies

Enable health indicators: Set registerHealthIndicator: true for all patterns

Retry only transient errors: Network timeouts, 5xx; skip 4xx and business exceptions

Size bulkheads based on load: Calculate thread pool and semaphore sizes from expected concurrency

Document fallback behavior: Make fallback logic clear and predictable

Constraints and Warnings

Fallback methods must have the same signature plus an optional exception parameter

Circuit breaker state is per-instance; ensure proper bean scoping in multi-tenant scenarios

Retry operations must be idempotent (may execute multiple times)

Do not use circuit breakers for operations that must always complete; use timeouts instead

Rate limiters can cause thread blocking; configure appropriate wait durations

Be cautious with @Retry on non-idempotent operations like POST requests

Monitor memory when using thread pool bulkheads with high concurrency

Examples

Before → After: Circuit Breaker

// BEFORE: No protection
public PaymentResponse processPayment(PaymentRequest request) {
    return restTemplate.postForObject("http://payment-api/process", request, PaymentResponse.class);
}

// AFTER: Circuit breaker with fallback
@CircuitBreaker(name = "paymentService", fallbackMethod = "paymentFallback")
public PaymentResponse processPayment(PaymentRequest request) {
    return restTemplate.postForObject("http://payment-api/process", request, PaymentResponse.class);
}
private PaymentResponse paymentFallback(PaymentRequest request, Exception ex) {
    return PaymentResponse.builder().status("PENDING").message("Service temporarily unavailable").build();
}

Before → After: Retry with Backoff

// BEFORE: Single attempt
public Order getOrder(Long orderId) {
    return orderRepository.findById(orderId).orElseThrow(() -> new OrderNotFoundException(orderId));
}

// AFTER: Retry with exponential backoff
@Retry(name = "orderService", maxAttempts = 3, waitDuration = @WaitDuration(500L), fallbackMethod = "getOrderFallback")
public Order getOrder(Long orderId) {
    return orderRepository.findById(orderId).orElseThrow(() -> new OrderNotFoundException(orderId));
}
private Order getOrderFallback(Long orderId, Exception ex) { return Order.cachedOrder(orderId); }

Before → After: Rate Limiting

// BEFORE: Unbounded requests
@GetMapping("/api/data") public Data fetchData() { return dataService.process(); }

// AFTER: Rate limited
@RateLimiter(name = "dataService", fallbackMethod = "rateLimitFallback")
@GetMapping("/api/data") public Data fetchData() { return dataService.process(); }
private ResponseEntity<ErrorResponse> rateLimitFallback(Exception ex) {
    return ResponseEntity.status(429).body(new ErrorResponse("TOO_MANY_REQUESTS", "Rate limit exceeded"));
}

See also: Configuration Reference · Testing Patterns · Examples · Resilience4j Docs · Actuator Skill