关于springboot:SpringBoot-集成-Prometheus

目录

• 一、增加依赖
• 二、Prometheus 装置与配置
• 三、Grafana 装置和配置
• 四、自定义监控指标

一、增加依赖

• Maven pom.xml

<!--  第一条必须加，否则会导致 Could not autowire. No beans of 'xxxx' type found 的谬误  -->
<dependency>
    <groupId>org.springframework.boot</groupId>
  <artifactId>spring-boot-starter-actuator</artifactId>
</dependency>
<dependency>
  <groupId>io.micrometer</groupId>
  <artifactId>micrometer-core</artifactId>
</dependency>
<dependency>
  <groupId>io.micrometer</groupId>
  <artifactId>micrometer-registry-prometheus</artifactId>
</dependency>

• Gradle build.gradle

implementation 'org.springframework.boot:spring-boot-starter-actuator'
compile 'io.micrometer:micrometer-registry-prometheus'
compile 'io.micrometer:micrometer-core'

• 关上 Prometheus 监控接口 application.properties

server.port=8088
spring.application.name=springboot2-prometheus
management.endpoints.web.exposure.include=*
management.metrics.tags.application=${spring.application.name}

能够间接运行程序，拜访 http://localhost:8088/actuator/prometheus 能够看到上面的内容：

# HELP jvm_buffer_total_capacity_bytes An estimate of the total capacity of the buffers in this pool
# TYPE jvm_buffer_total_capacity_bytes gauge
jvm_buffer_total_capacity_bytes{id="direct",} 90112.0
jvm_buffer_total_capacity_bytes{id="mapped",} 0.0
# HELP tomcat_sessions_expired_sessions_total  
# TYPE tomcat_sessions_expired_sessions_total counter
tomcat_sessions_expired_sessions_total 0.0
# HELP jvm_classes_unloaded_classes_total The total number of classes unloaded since the Java virtual machine has started execution
# TYPE jvm_classes_unloaded_classes_total counter
jvm_classes_unloaded_classes_total 1.0
# HELP jvm_buffer_count_buffers An estimate of the number of buffers in the pool
# TYPE jvm_buffer_count_buffers gauge
jvm_buffer_count_buffers{id="direct",} 11.0
jvm_buffer_count_buffers{id="mapped",} 0.0
# HELP system_cpu_usage The "recent cpu usage" for the whole system
# TYPE system_cpu_usage gauge
system_cpu_usage 0.0939447637893599
# HELP jvm_gc_max_data_size_bytes Max size of old generation memory pool
# TYPE jvm_gc_max_data_size_bytes gauge
jvm_gc_max_data_size_bytes 2.841116672E9

# 此处省略超多字...

二、Prometheus 装置与配置

应用 docker 运行 Prometheus（仅初始测试）

docker run --name prometheus -d -p 9090:9090 prom/prometheus:latest

写配置文件prometheus.yml

# my global config
global:
  scrape_interval:     15s # Set the scrape interval to every 15 seconds. Default is every 1 minute.
  evaluation_interval: 15s # Evaluate rules every 15 seconds. The default is every 1 minute.
  # scrape_timeout is set to the global default (10s).

# Load rules once and periodically evaluate them according to the global 'evaluation_interval'.
rule_files:
  # - "first_rules.yml"
  # - "second_rules.yml"

# A scrape configuration containing exactly one endpoint to scrape:
# Here it's Prometheus itself.
scrape_configs:
  # The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
  - job_name: 'prometheus'

    # metrics_path defaults to '/metrics'
    # scheme defaults to 'http'.

    static_configs:
    - targets: ['localhost:9090']
  # demo job
  -  job_name: 'springboot-actuator-prometheus-test' # job name
     metrics_path: '/actuator/prometheus' # 指标获取门路
     scrape_interval: 5s # 距离
     basic_auth: # Spring Security basic auth 
       username: 'actuator'
       password: 'actuator'
     static_configs:
     - targets: ['docker.for.mac.localhost:18080'] # 实例的地址，默认的协定是 http（这里开始有问题，间接写 localhost 是拜访容器内的地址，而不是宿主机的。可通过在网页上方 status -> targets 查看对应的服务状况

运行 docker

docker run -d -p 9090:9090 -v $(pwd)/prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheus --config.file=/etc/prometheus/prometheus.yml

拜访 http://localhost:9090，可看到如下界面

• 点击 Insert metric at cursor，即可抉择监控指标；点击 Graph，即可让指标以图表形式展现；点击Execute 按钮，即可看到指标图

三、Grafana 装置和配置

1、启动

$ docker run -d --name=grafana -p 3000:3000 grafana/grafana 

2、登录

拜访 http://localhost:3000/login，初始账号 / 明码为：admin/admin

3、配置数据源

• 点击左侧齿轮 Configuration 中Add Data Source，会看到如下界面：

• 这里咱们抉择 Prometheus 当做数据源，这里咱们就配置一下 Prometheus 的拜访地址，点击 Save & Test

4、创立监控 Dashboard

• 点击导航栏上的 + 按钮，并点击 Dashboard，将会看到相似如下的界面

• 点击+ Add new panel

四、自定义监控指标

1、创立 Prometheus 监控治理类PrometheusCustomMonitor

import io.micrometer.core.instrument.Counter;
import io.micrometer.core.instrument.DistributionSummary;
import io.micrometer.core.instrument.MeterRegistry;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Component;

import javax.annotation.PostConstruct;
import java.util.concurrent.atomic.AtomicInteger;

@Component
public class PrometheusCustomMonitor {

    private Counter requestErrorCount;
    private Counter orderCount;
    private DistributionSummary amountSum;
    private AtomicInteger failCaseNum;

    private final MeterRegistry registry;

    @Autowired
    public PrometheusCustomMonitor(MeterRegistry registry) {this.registry = registry;}

    @PostConstruct
    private void init() {requestErrorCount = registry.counter("requests_error_total", "status", "error");
        orderCount = registry.counter("order_request_count", "order", "test-svc");
        amountSum = registry.summary("order_amount_sum", "orderAmount", "test-svc");
        failCaseNum = registry.gauge("fail_case_num", new AtomicInteger(0));
    }

    public Counter getRequestErrorCount() {return requestErrorCount;}

    public Counter getOrderCount() {return orderCount;}

    public DistributionSummary getAmountSum() {return amountSum;}

    public AtomicInteger getFailCaseNum() {return failCaseNum;}
}

2、新增 /order 接口

当 flag="1"时，抛异样，模仿下单失败状况。在接口中统计 order_request_count 和order_amount_sum

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

import javax.annotation.Resource;
import java.util.Random;

@RestController
public class TestController {
    @Resource
    private PrometheusCustomMonitor monitor;

    @RequestMapping("/order")
    public String order(@RequestParam(defaultValue = "0") String flag) throws Exception {
        // 统计下单次数
        monitor.getOrderCount().increment();
        if ("1".equals(flag)) {throw new Exception("出错啦");
        }
        Random random = new Random();
        int amount = random.nextInt(100);
        // 统计金额
        monitor.getAmountSum().record(amount);

        monitor.getFailCaseNum().set(amount);
        return "下单胜利, 金额:" + amount;
    }
}

3、新增全局异样处理器GlobalExceptionHandler

统计下单失败次数requests_error_total

import org.springframework.web.bind.annotation.ControllerAdvice;
import org.springframework.web.bind.annotation.ExceptionHandler;
import org.springframework.web.bind.annotation.ResponseBody;

import javax.annotation.Resource;

@ControllerAdvice
public class GlobalExceptionHandler {
    @Resource
    private PrometheusCustomMonitor monitor;

    @ResponseBody
    @ExceptionHandler(value = Exception.class)
    public String handle(Exception e) {monitor.getRequestErrorCount().increment();
        return "error, message:" + e.getMessage();}
}

4、测试

启动我的项目，拜访 http://localhost:8080/order 和http://localhost:8080/order?flag=1模仿下单胜利和失败的状况，而后咱们拜访http://localhost:8080/actuator/prometheus，能够看到咱们自定义指标曾经被 /prometheus 端点裸露进去

# HELP requests_error_total  
# TYPE requests_error_total counter
requests_error_total{application="springboot-actuator-prometheus-test",status="error",} 41.0
# HELP order_request_count_total  
# TYPE order_request_count_total counter
order_request_count_total{application="springboot-actuator-prometheus-test",order="test-svc",} 94.0
# HELP order_amount_sum  
# TYPE order_amount_sum summary
order_amount_sum_count{application="springboot-actuator-prometheus-test",orderAmount="test-svc",} 53.0
order_amount_sum_sum{application="springboot-actuator-prometheus-test",orderAmount="test-svc",} 2701.0

5、应用 Prometheus 监控

从新运行 docker

docker run -d -p 9090:9090 -v $(pwd)/prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheus --config.file=/etc/prometheus/prometheus.yml

抉择对应指标后能够看到数据变动

6、应用 Grafana 展现

在 Dashboard 界面抉择对应的监控指标即可

参考资料：

Metric types | Prometheus

IntelliJ IDEA 创立第一个 Spring Boot 我的项目 \_Study Notes-CSDN 博客

Spring Boot 应用 Micrometer 集成 Prometheus 监控 Java 利用性能【springboot 2.0】

Micrometer Application Monitoring【官网文档】

Spring Boot 微服务利用集成 Prometheus + Grafana 实现监控告警 ★

Monitoring Java Spring Boot applications with Prometheus: Part 1 | by Arush Salil | Kubernauts【放弃这个教程？】client java 不反对 springboot 2.x，最高反对 1.5

Spring Boot 参考指南（端点）\_风持续吹 – SegmentFault 思否