Introduction
Welcome back! Building on our previous discussion on the Circuit Breaker pattern, this article will explore one of the essential resilience patterns.
Implementing resilience in microservice with the Retry pattern in Java is crucial for enhancing reliability and delivering a seamless user experience. by providing mechanisms to handle transient failures and offer alternative responses when services are unavailable. Let’s delve into understanding the problem and the solution, and then figure out how to implement this pattern using Java and Spring.
The Problem
In a microservices architecture, services often communicate over a network. These communications can sometimes fail due to transient issues like network glitches, temporary service unavailability, timeouts, or overloaded services. The system’s reliability and user experience can degrade significantly without a mechanism to handle these transient failures. For example, a failed call to a downstream service can lead to a cascade of errors, negatively impacting the entire application’s functionality.
Solution: Retry Pattern
The Retry pattern addresses this problem by automatically retrying a failed operation, anticipating that the failure might be transient. Doing so improves the system’s resilience and reduces the need for manual intervention. The pattern typically involves:
- Detecting a failure or exception during an operation.
- Waiting for a specified duration (often with an exponential backoff strategy) before retrying the operation.
- Retrying the operation a configured number of times or until a timeout is reached.
- If all retries fail, execute a fallback action or propagate the failure to the caller.
When to Use The Retry Pattern
- Scenario: Imagine an e-commerce application where the order service needs to verify product availability with the inventory service. Network issues or temporary unavailability of the inventory service could cause failures.
- Use Case: If the inventory service is known to experience occasional issues, the Retry pattern can automatically retry the request a few times before giving up, thus reducing the chances of failure due to transient issues.
Benefits:
- Improves resilience by overcoming temporary glitches
- Reduces the need for manual intervention
- Enhances the overall user experience by minimizing failures caused by transient issues
Implementing Retry Pattern in Java and Spring
1. Add Required Dependency:
<dependency>
<groupId>org.springframework.cloud</groupId>
<artifactId>spring-cloud-starter-circuitbreaker-resilience4j</artifactId>
</dependency>
2. Customize Retry Configurations
- The Retry annotation is configured in the following application.yaml to attempt the inventory service call up to 3 times (maxAttempts=3) with a delay of 500 milliseconds (waitDuration=500ms) between each attempt.
resilience4j:
retry:
instances:
inventoryService:
maxAttempts: 3
waitDuration: 500ms
3. Use @Retry Annotation
now let’s see the Retry pattern in action as the following code:
@Service
@Slf4j
@RequiredArgsConstructor
public class OrderService {
private final InventoryClient inventoryClient;
private static int RETRY_COUNTER = 1;
@Retry(name = "inventoryService", fallbackMethod = "fallbackRetryCheckInventory")
public void processOrder(Long productId, long quantity) {
log.info("processOrder -- calling the inventoryService counter {} ", RETRY_COUNTER++);
Boolean isProductAvailable = inventoryClient.checkProductAvailability(productId);
if (!isProductAvailable) {
throw new ProductAvailabilityException("Product:"+ productId+" unavailable");
}
}
public void fallbackRetryCheckInventory(Long productId, long quantity, Throwable throwable) {
log.info("Fallback logic if Inventory Service retries for productId {} and quantity : {}. Error: {}", productId, quantity, throwable.getMessage());
}
}
Retry Logs
processOrder -- calling the inventoryService counter 1 processOrder -- calling the inventoryService counter 2 processOrder -- calling the inventoryService counter 3 Fallback logic if Inventory Service retries for productId 2922 and quantity : 2. Error: Connection refused executing GET http://localhost:8081/api/inventory/check/2922 Order processed successfully
Best Practices for Implementing the Retry Pattern
- Exponential Backoff and Jitter:
- Use exponential backoff combined with jitter to avoid retry storms and reduce the load on the failing service. This means increasing the wait time between retries exponentially and adding randomness to prevent synchronized retries from multiple clients.
- Circuit Breaker Integration:
- Combine the Retry pattern with a Circuit Breaker to prevent repeated attempts to call a failing service. This helps in temporarily blocking requests to an unstable service, giving it time to recover.
- Idempotency:
- Ensure the operations being retried are idempotent to prevent unintended side effects. Idempotent operations can be performed multiple times
Summary
The Retry pattern is a crucial resilience pattern in microservices architectures, enabling automatic retries of failed operations due to transient issues. By implementing this pattern, you can enhance the reliability and user experience of your application by overcoming temporary glitches and reducing the need for manual intervention.
When implementing the Retry pattern, it’s essential to follow best practices such as using exponential backoff and jitter, integrating with the Circuit Breaker pattern, ensuring idempotency, setting sensible retry limits, providing fallback mechanisms, and implementing robust monitoring and logging.
Combining the Retry pattern with other resilience patterns and resilient communication strategies can further strengthen the overall resilience and fault tolerance of your microservices architecture, resulting in a more robust and reliable system.
