Resilience4j improves the flexibility of Java microservices through circuit breakers, current limiting, retry and other mechanisms. 1. Use circuit breakers to prevent cascade failures and prevent requests from being sent when services fail frequently; 2. Use current limiting to control concurrent access to avoid sudden traffic overwhelming downstream services; 3. Respond to temporary errors through retry mechanisms, but avoid invalid retry and resource waste; 4. Multiple strategies can be used in combination to enhance the overall resilience of the system, but attention should be paid to the mutual influence between policies. Properly configuring these functions can significantly improve the stability and fault tolerance of distributed systems.

Java microservices face many uncertainties in distributed systems, such as network latency and unavailability of third-party services. At this time, Resilience4j becomes a very practical tool. It is not as complex as Hystrix and is designed for Java 8 and functional programming, perfect for modern microservice architectures.

The following key points can help you better build more flexible Java microservices with Resilience4j.

Use circuit breakers to prevent cascade failure

Circuit Breaker is one of the most core functions of Resilience4j. It works like a fuse in a circuit - when a dependent service fails frequently, the circuit breaker will "on" to prevent subsequent requests from continuing to send to the service, thus preventing the entire system from crashing due to a problem with a point.

It's also very simple to use, you can define a circuit breaker like this:

 CircuitBreakerRegistry registry = CircuitBreakerRegistry.ofDefaults();
CircuitBreaker circuitBreaker = registry.circuitBreaker("myService");

Then wrap your remote call with it:

 Supplier<String> decoratedSupplier = CircuitBreaker.decorateSupplier(circuitBreaker, () -> myRemoteCall());
String result = Try.of(decoratedSupplier).recover(throwable -> "fallback").get();

The key is to configure the state transition rules of the circuit breaker, such as how many times it fails, how long it takes to try to open the state after opening, etc. These parameters must be adjusted according to the actual business scenario, and must not be too sensitive or too slow.

Use current limit control to concurrent access

Sometimes, the service is not slack, but is overwhelmed by too many requests. At this time, the Rate Limited function is required.

Resilience4j's current limiter can limit the number of requests per unit time to protect downstream services from sudden traffic breakdown. For example, limit up to 10 requests per second:

 RateLimiter rateLimiter = RateLimiter.ofDefaults("myRateLimiter");

Then use the decorator mode to wrap the method:

 Supplier<String> decorated = RateLimiter.decorateSupplier(rateLimiter, () -> myRemoteCall());

Note: The current limiting strategy needs to be used in conjunction with thread pools or semaphores, otherwise the problem of blocking the main thread may occur. In addition, the current limiting strategies of different interfaces are best configured separately to avoid one-size-fits-all impact on overall performance.

Retry mechanism improves fault tolerance

For some temporary errors (such as short network jitter), automatic retry is a good choice. Resilience4j provides a Retry module that automatically retry failed requests within a specified number of times.

For example:

 Retry retry = Retry.ofDefaults("myRetry");
Supplier<String> decorated = Retry.decorateSupplier(retry, () -> myRemoteCall());

But a few things to note:

• Not all failures are suitable for retry, such as 4xx errors are usually a client problem, and retry is useless.
• Set a reasonable retry interval and maximum number of times to avoid increasing downstream pressure.
• It can be used in conjunction with a circuit breaker to prevent infinite retry from causing an avalanche effect.

Combining multiple strategies to enhance resilience

The power of Resilience4j is that it can combine multiple policies together. For example, you can add a circuit breaker, current limit and try again:

 Supplier<String> chain = Decorators.ofSupplier(() -> myRemoteCall())
    .withRateLimiter(rateLimiter)
    .withCircuitBreaker(circuitBreaker)
    .withRetry(retry)
    .decorate();

This combination can make your microservices more resilient when facing various abnormal situations. However, you should also pay attention to the mutual influence between strategies. For example, retry may cause the current limit to be triggered faster, and the circuit breaker may enter the open state earlier due to multiple retrys.

Overall, Resilience4j is a lightweight but fully functional library suitable for building robust Java microservices. As long as the key strategies such as circuit breaker, current limiting, and retry are reasonably configured, the stability and fault tolerance of the system can be effectively improved. Basically all is it, not complicated but it is easy to ignore details.

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