Application and best practices of go-zero in microservice governance

As a lightweight Go language microservice framework, go-zero's application and best practices in microservice governance have become an important part that cannot be ignored in current development.

When developing distributed applications in Go language, the microservice architecture pattern is generally used. In a microservices architecture, communication between services is very important. To ensure the reliability and efficiency of communication between services, microservice governance needs to be optimized. This article will explore the application and best practices of go-zero in microservice governance, with a view to providing developers with practical guidance and inspiration.

1. Overview

go-zero is a high-performance, lightweight, microservice framework with the advantages of thread safety and high concurrency. Its application scenarios are very wide, including but not limited to: recommendation system, message queue, log management, API gateway, etc. At the same time, go-zero has very complete support for microservice governance, including service discovery, load balancing, circuit breaker degradation, current limiting, etc.

2. Service discovery

Service discovery is an important part of microservice governance. go-zero provides support for multiple service registration centers such as etcd and consul, and implements integration with other go-micro compatible service discovery tools through go-micro's service discovery interface.

We can achieve the integration of go-zero and etcd through the following code:

import (

    "github.com/go-zero/go-zero/core/discov"

    "github.com/go-zero/go-zero/core/stores/etcd"

    )

    //构建etcd连接
    client := etcd.NewClient([]string{"localhost:2379"})
    //创建Discovery服务
    d := discov.NewDiscovery(client, "hello")
    //获取服务列表
    services, err := d.GetServices()

Through the above code, we have successfully integrated etcd and go-zero and obtained the service list.

3. Load balancing

Load balancing is an important means to ensure high availability of services. go-zero supports multiple load balancing methods, including polling, random, weighted polling, weighted random, etc. Usually, we will deploy multiple service instances on different machines, which requires adding machine selection factors to the load balancing algorithm.

In the following code example, we use the RoundRobin algorithm to achieve load balancing and set the weight for each service instance.

import (
    "github.com/stretchr/testify/assert"
    "github.com/go-zero/go-zero/core/balance"
    )
    
    //定义服务列表
    nodes, _ := balance.NewRoundRobin("/",
        balance.WithNodes(
            &balance.WeightNode{
                Weight: 10,
                Node: balance.NewNode("127.0.0.1", 8000),
            },
            &balance.WeightNode{
                Weight: 20,
                Node: balance.NewNode("127.0.0.2", 8000),
            },
        ))
    // 从服务列表中选择下一个节点进行调用
    next, err := nodes.Next()

The above code shows how to use the balance component provided by go-zero, use the RoundRobin algorithm to achieve load balancing, and set different weight values ​​for each service instance.

4. Circuit breaker downgrade and current limiting

In high concurrency scenarios, service calls may be abnormal due to various reasons, which requires the use of circuit breaker downgrade and current limiting strategies. go-zero implements strategies such as circuit breaker degradation and current limiting through hystrix components.

In the following code example, we use the hystrix component to limit the speed and concurrency of service calls in high-concurrency scenarios.

import (
    "net/http"
    "github.com/go-zero/go-zero/core/hystrix"
    )
    
    //定义熔断降级回调函数
    fallbackFunc := func(err error) bool {
        //判断回调错误类型
        e := hystrix.ExtractHTTPError(err)
        if e == nil || e.Code != http.StatusNotFound {
            // 返回true触发熔断降级
            return true
        }
        //返回false
        return false
    }
    //实例化Hystrix方法
    hystrix.Do(ctx, "test", func(ctx context.Context) error {
        //执行服务
        resp, err := http.Get("https://example.com/")
        if err != nil {
            return err
        }
        defer resp.Body.Close()
        return nil
    }, hystrix.WithFallback(fallbackFunc))

In the above code, we use the Do method in the hystrix component to implement restrictions on service calls, circuit break and downgrade abnormal calls in high concurrency scenarios, and implement error type filtering through callback functions. . In this way, we can effectively reduce the impact of abnormal calls on the system.

5. Summary

This article discusses the application and best practices of go-zero in microservice governance. Through in-depth explanations of technologies such as service discovery, load balancing, circuit breaker degradation, and current limiting, it aims to provide developers with some practical ideas and guidance. I believe that in the next microservice development, we can better use the go-zero framework to improve system performance and reliability.

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