Cleverly use Spring Cloud to solve load balancing problems under microservice architecture

As the complexity of enterprise applications continues to increase, more and more enterprises are beginning to split applications into multiple microservices and complete the entire business process through collaboration between microservices. This architectural approach can make applications more stable and scalable, but it also brings some new problems, such as load balancing, service discovery, etc. This article will introduce how to use Spring Cloud to solve the load balancing problem under the microservice architecture.

What is load balancing?

Load Balancing refers to allocating load among multiple servers, network devices or applications to achieve optimal resource utilization, maximum capacity, fastest response speed, and highest reliability and maximum life, resulting in efficient and reliable service.

For example, when an application system has a large number of visits and a single server cannot satisfy all user requests, we can distribute the load through multiple servers to improve the stability and throughput of the system. volume, response time, etc. In the microservice architecture, since there are multiple microservices and multiple service instances, load balancing is also essential.

Common load balancing algorithms

Load balancing algorithms usually include the following:

Polling algorithm

Polling algorithm is the simplest One of the load balancing algorithms. Distribute requests to each service instance in sequence in the order of the service instance list. After all service instances have been assigned requests, redistribute them from scratch. The advantage of the polling algorithm is that it is simple and suitable for various load scenarios, but its disadvantages are also obvious, which may cause the load of some service instances to be too high.

Random algorithm

The random algorithm randomly allocates requests to service instances, which can effectively prevent load imbalance of service instances in most cases, but cannot guarantee that each service instance is assigned The requests are all the same.

Weighted polling algorithm

The weighted polling algorithm is an improvement based on the polling algorithm, that is, giving different weights (or proportions) to different service instances, so that each The number of requests assigned to a service instance is proportional to its weight. This algorithm can make the system more flexible and can allocate requests according to the actual capability level of the service instance.

Least connection algorithm

The least connection algorithm distributes requests to the service instance with the lightest load based on the actual load of the current service instance. This algorithm can ensure the load of each service instance. Balanced, but there are also some shortcomings, for example, it may cause certain requests to be executed repeatedly on different service instances.

Spring Cloud implements load balancing

Spring Cloud provides a complete solution for load balancing. Among them, one of the core components is Ribbon. Ribbon is a client-side load balancer that can be used with various HTTP and TCP service clients to provide clients with more stable and balanced load capabilities.

How to use Ribbon

Using Ribbon is very simple. You only need to add the following dependencies in the Spring Boot application:

<dependency>
  <groupId>org.springframework.cloud</groupId>
  <artifactId>spring-cloud-starter-netflix-ribbon</artifactId>
</dependency>

And where load balancing is required, pass @ Just modify it with LoadBalanced annotation:

@Autowired
@LoadBalanced
private RestTemplate restTemplate;

When we need to access a Rest service, we only need to use the service name as part of the URI in the request path of RestTemplate:

String result = restTemplate.getForObject("http://SERVICE-NAME/path", String.class);

where , SERVICE-NAME is the service name, and path is the service path. At this time, Ribbon will automatically select an available service instance based on the configured load balancing algorithm and distribute the request to the service instance. If the service instance is unavailable, Ribbon will automatically select the next available service instance.

Ribbon's load balancing strategy

By default, Ribbon uses a polling algorithm to achieve load balancing, which can also be specified through the configuration file. The following are some common load balancing strategies:

ribbon:
  LoadBalancerRuleClassName: com.netflix.loadbalancer.RandomRule # 随机负载均衡
  # LoadBalancerRuleClassName: com.netflix.loadbalancer.RoundRobinRule # 轮询负载均衡
  # LoadBalancerRuleClassName: com.netflix.loadbalancer.WeightedResponseTimeRule # 带权重的随机负载均衡
  # LoadBalancerRuleClassName: com.netflix.loadbalancer.RepeatableRandomRule # 重试随机负载均衡
  # LoadBalancerRuleClassName: com.netflix.loadbalancer.AvailabilityFilteringRule # 豁免机房、实例挂掉等异常情况负载均衡

Conclusion

This article introduces how to implement load balancing under the microservice architecture through the Ribbon in Spring Cloud. Using Ribbon is very simple. We only need to modify it with the @LoadBalanced annotation where load balancing is needed. When multiple service instances are available, Ribbon automatically selects an available service instance based on the configured load balancing policy and distributes requests to the service instance to achieve load balancing.

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