Reliability strategies in Java microservice architecture

In the Java microservice architecture, common reliability strategies include: timeout and circuit breaker: set a timeout for the request and circuit breaker the request when the service fails. Retry: Automatically retry requests in the event of a temporary service failure. Redundancy and load balancing: Deploy multiple replica service instances and use load balancing technology to distribute requests.

Reliability Strategy in Java Microservice Architecture

In a distributed system, reliability is crucial. In a microservice architecture, reliability assurance is particularly complex due to the large number of services and their dependence on each other. This article will introduce common reliability strategies in Java microservice architecture and demonstrate them through practical cases.

Timeout and circuit breaker

Timeout and circuit breaker mechanism can prevent a single service slowness or failure from affecting the entire system.

• Timeout: Set a timeout for each service request, and interrupt the request after timeout.
• Circuit: When the service failure rate reaches a certain threshold, requests to the service will be automatically cut off until it returns to normal.

Code example:

// 设置超时
@HystrixCommand(commandProperties = {
    @HystrixProperty(name = "execution.isolation.thread.timeoutInMilliseconds", value = "5000")
})
public void doSomething() { ... }

// 配置熔断
@HystrixCommand(fallbackMethod = "fallback")
public void doSomethingElse() { ... }

Retry

The retry mechanism can automatically restart when the service fails temporarily. Try request. The number of retries and time interval can be customized.

Code example:

@FeignClient(name = "my-service", fallback = MyServiceFallback.class)
public interface MyServiceClient {
    @Retryable(value = MyServiceUnavailableException.class, maxAttempts = 3)
    MyResponse doSomething();
}

Redundancy and load balancing

Redundancy and load balancing mechanisms can be served through multiple replicas Examples to improve system availability.

• Redundancy: Deploy multiple instances of the same service.
• Load balancing: Distribute requests to different service instances to improve system throughput and availability.

Code example:

# Kubernetes Deployment YAML
apiVersion: apps/v1
kind: Deployment
...
spec:
  replicas: 3
...

Practical case: e-commerce system

Question: The service responsible for placing orders in the e-commerce system frequently times out due to traffic peaks.

Solution:

• Implement timeout and circuit breaker in the order service: prevent timeout requests from affecting the system, and automatically fuse.
Implement
• Retry on the product query service: Automatically retry the request when the product query service is temporarily unavailable to improve the success rate of the order process.
Deploy
• multiple copies of the ordering service and product query service, and use the load balancing mechanism to distribute requests.

Through these reliability strategies, e-commerce systems can maintain high availability and performance during traffic peaks.

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