1 prometheus下载安装
1.1 虚机部署
https://prometheus.io/download/
wget https://github.com/prometheus/prometheus/releases/download/v2.53.0/prometheus-2.53.0.linux-amd64.tar.gz
tar -xvf prometheus-2.53.0.linux-amd64.tar.gz
cd /home/prometheus-2.53.0.linux-amd64
./prometheus
1.2 容器部署
# 1下载
docker pull prom/prometheus
# 2创建prometheus配置文件
mkdir /opt/prometheus
cd /opt/prometheus/
vim prometheus.yml
# 3启动
docker run -d --name prometheus --restart=always -p 9090:9090 -v /opt/prometheus/prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheus
1.3 prometheus.yml配置
scrape_configs:
# The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
- job_name: "prometheus"
static_configs:
- targets: ["9.135.95.39:9090"]
访问地址:http://127.0.0.1:9090/targets?search=
2 grafana下载安装
2.1 虚机部署
Download Grafana | Grafana Labs
wget https://dl.grafana.com/enterprise/release/grafana-enterprise-11.1.3.linux-amd64.tar.gz
tar -zxvf grafana-enterprise-11.1.0.linux-amd64.tar.gz
cd /home/grafana-11.1.0
bin/grafana-server web
2.2 容器部署
docker run -d --name=grafana -p 3000:3000 grafana/grafana-enterprise-dev:11.1.0-70874
2.3 数据源配置
http://127.0.0.1:3000
默认账号密码:admin/admin
3 node监控
3.1 node_exporter下载
wget https://github.com/prometheus/node_exporter/releases/download/v1.8.1/node_exporter-1.8.1.linux-amd64.tar.gz
tar -xvf node_exporter-1.8.1.linux-amd64.tar.gz
cd /home/ode_exporter-1.8.1.linux-amd64
./node_exporter
3.2 prometheus-job配置
scrape_configs:
- job_name: "node"
static_configs:
- targets: ["9.135.95.39:9100"]
3.3 grafana监控面板
https://grafana.com/grafana/dashboards/12633-linux/
4 mysql监控
4.1 mysqld_exporter下载
wget https://github.com/prometheus/mysqld_exporter/releases/download/v0.15.1/mysqld_exporter-0.15.1.linux-amd64.tar.gz
tar -xvf mysqld_exporter-0.15.1.linux-amd64.tar.gz
cd /home/mysqld_exporter-0.15.1.linux-amd64
# 2修改配置
# cat mysql.cnf
[client]
user=root
password=admin123456
host=192.168.1.139
port=13306
# 3启动
nohup ./mysqld_exporter --web.listen-address=192.168.1.199:9104 --config.my-cnf=mysql.cnf &
4.2 prometheus-job配置
scrape_configs:
- job_name: "mysql"
static_configs:
- targets: ["9.135.95.39:9104"]
4.3 grafana监控面板
https://grafana.com/grafana/dashboards/15211-mysql/
5 springboot应用监控
5.1 springboot应用配置
5.1.1 prometheus pom依赖配置
<!-- Spring Boot Actuator -->
<dependency>
<groupId>org.springframework.boot</groupId>
<artifactId>spring-boot-starter-actuator</artifactId>
<version>2.7.15</version>
</dependency>
<!-- Micrometer Prometheus Registry -->
<dependency>
<groupId>io.micrometer</groupId>
<artifactId>micrometer-registry-prometheus</artifactId>
<version>1.6.4</version>
</dependency>
5.1.2 application.yaml配置
spring:
application:
name: metrics-demo
server:
port: 8084
#Prometheus springboot监控配置
management:
endpoints:
web:
exposure:
include: '*'
metrics:
export:
prometheus:
enabled: true
tags:
application: ${spring.application.name} # 暴露的数据中添加application l
5.1.3 MeterRegistryCustomizer bean
@Bean
MeterRegistryCustomizer<MeterRegistry> configurer(
@Value("${spring.application.name}") String applicationName) {
return (registry) -> registry.config().commonTags("application", applicationName);
}
访问 http://9.139.95.39:8084/actuator/prometheus
5.2 prometheus-job配置
scrape_configs:
- job_name: "metrics-demo"
metrics_path: '/actuator/prometheus'
static_configs:
- targets: ["9.135.95.39:8084"]
5.3 grafana监控面板
https://grafana.com/grafana/dashboards/4701-jvm-micrometer/
5.4 PromQL 内置函数
# QPS统计
sum(rate(http_server_requests_seconds_count{application="metrics-demo"}[10s]))
# 每个接口QPS统计
rate(http_server_requests_seconds_count{application="metrics-demo"}[10s])
# 耗时统计
sum(rate(http_server_requests_seconds_sum{application="metrics-demo"}[10s])) / sum(rate(http_server_requests_seconds_count{application="metrics-demo"}[10s]))
# 每个接口的耗时
rate(http_server_requests_seconds_sum{application="metrics-demo"}[10s])
5.5 自定义指标
通过拦截器实现 MetricInterceptor.java
package com.demo.interceptor;
import io.micrometer.core.instrument.MeterRegistry;
import io.micrometer.core.instrument.Tags;
import io.micrometer.core.instrument.Timer;
import org.springframework.web.servlet.ModelAndView;
import org.springframework.web.servlet.handler.HandlerInterceptorAdapter;
import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;
import java.time.Duration;
/**
* 自定义指标上报
* @author xfgeng
* @date 2024-08-14 15:16
*/
public class MetricInterceptor extends HandlerInterceptorAdapter {
private MeterRegistry meterRegistry;
private ThreadLocal<Timer.Sample> threadLocal = new ThreadLocal<>();
public MetricInterceptor(MeterRegistry meterRegistry){
this.meterRegistry = meterRegistry;
}
@Override
public boolean preHandle(HttpServletRequest request, HttpServletResponse response, Object handler) throws Exception {
// 总计数 + 1
meterRegistry.counter("api_request_count", Tags.of("url", request.getRequestURI(), "method", request.getMethod())).increment();
// 处理中计数 +1
meterRegistry.gauge("api_process_count", Tags.of("url", request.getRequestURI(), "method", request.getMethod()), 1);
Timer.Sample sample = Timer.start();
threadLocal.set(sample);
return super.preHandle(request, response, handler);
}
@Override
public void postHandle(HttpServletRequest request, HttpServletResponse response, Object handler, ModelAndView modelAndView) throws Exception {
try {
super.postHandle(request, response, handler, modelAndView);
} finally {
meterRegistry.gauge("api_process_count", Tags.of("url", request.getRequestURI(), "method", request.getMethod()), -1);
// Timer timer = meterRegistry.timer("micro_req_histogram", Tags.of("url", request.getRequestURI(), "method", request.getMethod(), "code", String.valueOf(response.getStatus())));
Timer timer = Timer.builder("api_request_histogram").minimumExpectedValue(Duration.ofMillis(1)).maximumExpectedValue(Duration.ofMinutes(3))
.sla(Duration.ofMillis(10), Duration.ofMillis(50), Duration.ofMillis(100), Duration.ofMillis(300), Duration.ofMillis(1000))
.tags(Tags.of("url", request.getRequestURI(), "method", request.getMethod(), "code", String.valueOf(response.getStatus())))
.register(meterRegistry);
threadLocal.get().stop(timer);
threadLocal.remove();
}
}
}
WebMvcConfig.java
package com.demo.config;
import com.demo.interceptor.MetricInterceptor;
import io.micrometer.core.instrument.MeterRegistry;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.boot.actuate.autoconfigure.metrics.MeterRegistryCustomizer;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.web.servlet.config.annotation.InterceptorRegistry;
import org.springframework.web.servlet.config.annotation.WebMvcConfigurer;
@Configuration
public class WebMvcConfig implements WebMvcConfigurer {
@Autowired
private MeterRegistry meterRegistry;
@Override
public void addInterceptors(InterceptorRegistry registry) {
registry.addInterceptor(new MetricInterceptor(meterRegistry))
.addPathPatterns("/api/**") //拦截路径
.excludePathPatterns("/*.png","/*.gif"); //排除路径
}
@Bean
MeterRegistryCustomizer<MeterRegistry> configurer(
@Value("${spring.application.name}") String applicationName) {
return (registry) -> registry.config().commonTags("application", applicationName);
}
}
标签:exporter,request,grafana,application,prometheus,import,企业级
From: https://blog.csdn.net/drea_mer/article/details/141197587