扩展自定义spring boot prometheus metrics

实现原理很简单，主要是基于micrometer包装提供的MeterRegistry bean 进行扩展

项目结构

• maven pom.xml

<?xml version="1.0" encoding="UTF-8"?>

<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"

  xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 https://maven.apache.org/xsd/maven-4.0.0.xsd">

  <modelVersion>4.0.0</modelVersion>

  <parent>

    <groupId>org.springframework.boot</groupId>

    <artifactId>spring-boot-starter-parent</artifactId>

    <version>2.2.10.RELEASE</version>

    <relativePath/> <!-- lookup parent from repository -->

  </parent>

  <groupId>com.dalong</groupId>

  <artifactId>prome</artifactId>

  <version>0.0.1-SNAPSHOT</version>

  <name>prome</name>

  <description>Demo project for Spring Boot</description>

​

  <properties>

    <java.version>1.8</java.version>

  </properties>

​

  <dependencies>

    <dependency>

      <groupId>org.springframework.boot</groupId>

      <artifactId>spring-boot-starter-actuator</artifactId>

    </dependency>

    <dependency>

      <groupId>org.springframework.boot</groupId>

      <artifactId>spring-boot-starter-web</artifactId>

    </dependency>

    <dependency>

      <groupId>io.micrometer</groupId>

      <artifactId>micrometer-registry-prometheus</artifactId>

      <scope>runtime</scope>

    </dependency>

    <dependency>

      <groupId>org.aspectj</groupId>

      <artifactId>aspectjweaver</artifactId>

      <version>1.8.6</version>

    </dependency>

    <dependency>

      <groupId>org.springframework.boot</groupId>

      <artifactId>spring-boot-starter-test</artifactId>

      <scope>test</scope>

      <exclusions>

        <exclusion>

          <groupId>org.junit.vintage</groupId>

          <artifactId>junit-vintage-engine</artifactId>

        </exclusion>

      </exclusions>

    </dependency>

  </dependencies>

​

  <build>

    <plugins>

      <plugin>

        <groupId>org.springframework.boot</groupId>

        <artifactId>spring-boot-maven-plugin</artifactId>

      </plugin>

    </plugins>

  </build>

​

</project>

• 项目结构
  基于spring 的starter 官网生成

 

├── pom.xml

└── src

    ├── main

    │   ├── java

    │   │   └── com

    │   │       └── dalong

    │   │           └── prome

    │   │               ├── Login.java

    │   │               ├── MyService.java

    │   │               └── PromeApplication.java

    │   └── resources

    │       ├── application.properties

    │       ├── static

    │       └── templates

​

 

 

• 代码说明
  application.properties,开启prometheus 配置的

 

management.endpoints.web.exposure.include=prometheus,health,info

management.endpoints.web.base-path=/

MyService.java 一个模拟延迟处理的bean

package com.dalong.prome;

​

import io.micrometer.core.annotation.Timed;

import org.springframework.stereotype.Service;

​

import java.util.HashMap;

​

/**

 @author dalong

*/

​

​

@Service

public class MyService {

​

    // 注册timed 可以查看服务请求时间的处理，我们可以查看比较慢的请求情况，尤其是异步，而且是长时间运行的调度任务

    @Timed(description = "fetch userservice")

    public Object fetchUserinfo() throws InterruptedException {

        HashMap<String,String> userinfo  =new HashMap<>();

        userinfo.put("name","demoapp");

        userinfo.put("version","v1");

        Thread.sleep((long) (1000*Math.random()));

        return userinfo;

    }

}

 

PromeApplication.java：入口，注册了一个time的aop bean

package com.dalong.prome;

​

import io.micrometer.core.aop.TimedAspect;

import io.micrometer.core.instrument.MeterRegistry;

import org.springframework.boot.SpringApplication;

import org.springframework.boot.autoconfigure.SpringBootApplication;

import org.springframework.context.annotation.Bean;

​

@SpringBootApplication

public class PromeApplication {

    @Bean

    public TimedAspect timedAspect(MeterRegistry registry) {

        return new TimedAspect(registry);

    }

    public static void main(String[] args) {

        SpringApplication.run(PromeApplication.class, args);

    }

​

}

Login.java 一个service

package com.dalong.prome;

​

import io.micrometer.core.annotation.Timed;

import io.micrometer.core.instrument.Counter;

import io.micrometer.core.instrument.Meter;

import io.micrometer.core.instrument.MeterRegistry;

import org.springframework.beans.factory.annotation.Autowired;

import org.springframework.web.bind.annotation.RequestMapping;

import org.springframework.web.bind.annotation.RestController;

​

import java.util.HashMap;

​

/**

 @author dalong

*/

​

@RestController

public class Login {

    MeterRegistry meterRegistry;

    Counter okCounter;

    Counter failCounter;

    MyService myService;

    public  Login(MeterRegistry meterRegistry,MyService myService){

        this.meterRegistry=meterRegistry;

        this.myService=myService;

        okCounter = meterRegistry.counter("platform_userlogin_ok", "type", "ok"); // 1 - create a counter

        failCounter = Counter.builder("platform_userlogin_fail")    // 2 - create a counter using the fluent API

                .tag("type", "fail")

                .description("The number of fail logins")

                .register(meterRegistry);

​

    }

    @RequestMapping(value = {"/demoapp"})

    @Timed(description = "deoapp")

    public Object info() throws InterruptedException {

        if (Math.random()*10>1){

            // ok

            okCounter.increment();

            return myService.fetchUserinfo();

        }else{

            // fail

            failCounter.increment();

            return myService.fetchUserinfo();

        }

    }

}

• 运行效果

接口请求

 

 

metrics

 

 

 

 

说明

不太好的地方是默认对于prometheus 包装的MeterRegistry并不如golang 或者其他语言prometheus metrics 定义的那么方便（尤其是label 的处理上）
但是总的来说还都是比较简单的，基于prometheus 灵活的能力，我们可以比较方便的分析业务指标,如果真的需要自定义扩展的metrics 推荐使用
MeterBinder 接口以及Meter进行扩展，以下包含了一个参考例子

参考资料

https://docs.spring.io/spring-metrics/docs/current/public/prometheus
https://blog.autsoft.hu/defining-custom-metrics-in-a-spring-boot-application-using-micrometer/
https://www.atlantbh.com/custom_metrics_micrometer_prometheus_spring_boot_actuator/