Resilience4j and Reactor RetryWhen: Why They’re Not Working Together to Distribute 100 Requests at 10 Requests per Second

Are you trying to use Resilience4j and Reactor RetryWhen to distribute 100 requests at 10 requests per second, but they’re just not playing nice together? You’re not alone! Many developers have tried to combine these two powerful libraries, only to find that they’re not working as expected. In this article, we’ll dive into the reasons why and provide you with a solution to overcome this hurdle.

What is Resilience4j?

Resilience4j is a popular open-source library that provides a set of components to build resilient applications. One of its core features is the ability to rate limit, circuit break, and retry requests to ensure that your application can withstand high traffic and failures. It’s a great tool for building robust and scalable systems.

What is Reactor RetryWhen?

Reactor RetryWhen, on the other hand, is a part of the Reactor framework, which provides a set of libraries for building reactive systems. RetryWhen is a utility that allows you to retry failed requests with a customizable retry strategy. It’s often used in conjunction with Resilience4j to provide an additional layer of resilience in your application.

The Problem: Why Resilience4j and Reactor RetryWhen Aren’t Working Together

So, why aren’t Resilience4j and Reactor RetryWhen working together as expected? The reason is that they’re trying to achieve the same goal, but in different ways. Resilience4j is designed to rate limit and retry requests at a high level, while Reactor RetryWhen is trying to retry failed requests at a lower level. This leads to conflicts and unexpected behavior.

When you combine Resilience4j and Reactor RetryWhen, you might experience issues like:

• Inconsistent retry behavior: Resilience4j might retry a request, but Reactor RetryWhen might also retry the same request, leading to duplicate retries.
• Rate limiting issues: Resilience4j might rate limit requests, but Reactor RetryWhen might not respect those limits, causing the rate limiter to malfunction.
• Unwanted retries: Reactor RetryWhen might retry failed requests, even if Resilience4j has already retried them.

The Solution: How to Make Resilience4j and Reactor RetryWhen Work Together

So, how can we make Resilience4j and Reactor RetryWhen work together seamlessly? The answer lies in configuring them to complement each other’s strengths. Here’s a step-by-step guide to get you started:

Step 1: Configure Resilience4j

First, configure Resilience4j to rate limit and retry requests as needed. For example, you can create a rate limiter that allows 10 requests per second:

 RateLimiter rateLimiter = RateLimiter.of("myRateLimiter", RateLimiterConfig.custom()
    .limitForPeriod(10)
    .limitRefreshPeriod(Duration.ofSeconds(1))
    .timeoutDuration(Duration.ofSeconds(10))
    .build());

Step 2: Configure Reactor RetryWhen

Next, configure Reactor RetryWhen to retry failed requests with a custom retry strategy. For example, you can create a retry strategy that retries up to 3 times with an exponential backoff:

Retry retry = Retry.anyOf(Retry.anyOf(Retry.maxAttempts(3), Retry.exponentialBackoff(Duration.ofMillis(100), 3)));

Step 3: Combine Resilience4j and Reactor RetryWhen

Now, combine Resilience4j and Reactor RetryWhen to create a resilient request flow. You can use the ` retryWhen` method to wrap your request in a retryable block:

 Mono<HttpResponse> request = WebClient.builder()
    .baseUrl("https://example.com")
    .build()
    .get()
    .uri("/")
    .retrieve()
    .bodyToMono(HttpResponse.class)
    .retryWhen(retry);

request.rateLimiter(rateLimiter)
    .block(Duration.ofSeconds(10));

Step 4: Test and Refine

Finally, test your resilient request flow with a high volume of requests (e.g., 100 requests at 10 requests per second) to ensure that it’s working as expected. Refine your configuration as needed to achieve the desired level of resilience and performance.

Best Practices for Combining Resilience4j and Reactor RetryWhen

When combining Resilience4j and Reactor RetryWhen, keep the following best practices in mind:

• Use Resilience4j for high-level rate limiting and retrying, and Reactor RetryWhen for low-level retrying of failed requests.
• Configure Resilience4j to respect the rate limits and retry policies set by Reactor RetryWhen.
• Use a single retry strategy across both libraries to avoid conflicting retry behaviors.
• Test your resilient request flow with a high volume of requests to ensure it’s working as expected.

Library	Purpose	Configuration
Resilience4j	Rate limiting and retrying	RateLimiterConfig, RetryConfig
Reactor RetryWhen	Retying failed requests	Retry, RetryStrategy

Conclusion

In conclusion, combining Resilience4j and Reactor RetryWhen can be a powerful way to build resilient applications that can withstand high traffic and failures. However, it’s essential to configure them correctly to avoid conflicts and unexpected behavior. By following the steps outlined in this article, you can create a resilient request flow that distributes 100 requests at 10 requests per second.

Remember to keep an eye on your application’s performance and adjust your configuration as needed to achieve the desired level of resilience and performance.

Additional Resources

For more information on Resilience4j and Reactor RetryWhen, check out the following resources:

1. Resilience4j Documentation
2. Reactor RetryWhen Documentation
3. Resilience4j GitHub Repository
4. Reactor Core GitHub Repository

Happy coding!

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