Spring Boot Resilience4j logo

Spring Boot Resilience4j

Community
giuseppe-trisciuoglio
spring-boot-resilience4j

Provides fault tolerance patterns for Spring Boot 3.x using Resilience4j. Use when implementing circuit breakers, handling service failures, adding retry logic with exponential backoff, configuring rate limiters, or protecting services from cascading failures. Generates circuit breaker, retry, rate limiter, bulkhead, time limiter, and fallback implementations. Validates resilience configurations through Actuator endpoints.

Overview

Publishergiuseppe-trisciuoglio
Repositorydeveloper-kit
Skill namespring-boot-resilience4j
Stars
345
Forks
41
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by giuseppe-trisciuoglio on GitHub. Read the source before you install it.

Installation

Install the Spring Boot Resilience4j AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/giuseppe-trisciuoglio/developer-kit.git /tmp/developer-kit
mkdir -p .claude/skills
cp -r /tmp/developer-kit/plugins/developer-kit-java/skills/spring-boot-resilience4j .claude/skills/spring-boot-resilience4j
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Spring Boot Resilience4j in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Spring Boot Resilience4j on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Spring Boot Resilience4j is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

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:

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:

java
@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:

yaml
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:

java
@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:

yaml
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:

java
@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:

yaml
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:

java
@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:

java
@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:

yaml
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:

java
@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:

yaml
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:

java
@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:

java
@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:

yaml
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

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

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

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

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

  5. 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

java
// 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

java
// 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

java
// 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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Spring Boot Resilience4j AI skill do?

Provides fault tolerance patterns for Spring Boot 3.x using Resilience4j. Use when implementing circuit breakers, handling service failures, adding retry logic with exponential backoff, configuring rate limiters, or protecting services from cascading failures. Generates circuit breaker, retry, rate limiter, bulkhead, time limiter, and fallback implementations. Validates resilience configurations through Actuator endpoints.

Why use Spring Boot Resilience4j on TypingMind?

Because you install it once and use it with any model. Spring Boot Resilience4j is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Spring Boot Resilience4j in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/giuseppe-trisciuoglio/developer-kit/tree/main/plugins/developer-kit-java/skills/spring-boot-resilience4j. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Spring Boot Resilience4j?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Spring Boot Resilience4j?

As many as you like. As long as a model supports skills, you can use Spring Boot Resilience4j with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Spring Boot Resilience4j AI skill free?

Yes. It is published on GitHub by giuseppe-trisciuoglio under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇