1.Spring Boot 工程集成 Micrometer
1.1引入依赖
<dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-actuator</artifactId> </dependency> <dependency> <groupId>io.micrometer</groupId> <artifactId>micrometer-registry-prometheus</artifactId> </dependency>
1.2配置
management.server.port=9003 management.endpoints.web.exposure.include=* management.endpoint.metrics.enabled=true management.endpoint.health.show-details=always management.endpoint.health.probes.enabled=true management.endpoint.prometheus.enabled=true management.metrics.export.prometheus.enabled=true management.metrics.tags.application=voice-qc-backend
这里 management.endpoints.web.exposure.include=* 配置为开启 Actuator 服务，因为Spring Boot Actuator 会自动配置一个 URL 为 /actuator/Prometheus 的 HTTP 服务来供 Prometheus 抓取数据，不过默认该服务是关闭的，该配置将打开所有的 Actuator 服务。
management.metrics.tags.application 配置会将该工程应用名称添加到计量器注册表的 tag 中去，方便后边 Prometheus 根据应用名称来区分不同的服务。
1.3监控jvm信息
然后在工程启动主类中添加 Bean 如下来监控 JVM 性能指标信息：
@SpringBootApplication public class GatewayDatumApplication { public static void main(String[] args) { SpringApplication.run(GatewayDatumApplication.class, args); } @Bean MeterRegistryCustomizer<MeterRegistry> configurer( @Value("${spring.application.name}") String applicationName) { return (registry) -> registry.config().commonTags("application", applicationName); } }
1.4创建自定义监控
监控请求次数与响应时间
package com.lianxin.gobot.api.monitor; import io.micrometer.core.instrument.Counter; import io.micrometer.core.instrument.MeterRegistry; import io.micrometer.core.instrument.Timer; import lombok.Getter; import org.springframework.beans.factory.annotation.Autowired; import org.springframework.beans.factory.annotation.Value; import org.springframework.stereotype.Component; import javax.annotation.PostConstruct; /** * @Author: GZ * @CreateTime: 2022-08-30 10:50 * @Description: 自定义监控服务 * @Version: 1.0 */ @Component public class PrometheusCustomMonitor { /** * 上报拨打请求次数 */ @Getter private Counter reportDialRequestCount; /** * 上报拨打URL */ @Value("${lx.call-result-report.url}") private String callReportUrl; /** * 上报拨打响应时间 */ @Getter private Timer reportDialResponseTime; @Getter private final MeterRegistry registry; @Autowired public PrometheusCustomMonitor(MeterRegistry registry) { this.registry = registry; } @PostConstruct private void init() { reportDialRequestCount = registry.counter("go_api_report_dial_request_count", "url",callReportUrl); reportDialResponseTime= registry.timer("go_api_report_dial_response_time", "url",callReportUrl); } }
1.5添加具体业务代码监控
//统计请求次数 prometheusCustomMonitor.getReportDialRequestCount().increment(); long startTime = System.currentTimeMillis(); String company = HttpUtils.post(companyUrl,""); //统计响应时间 long endTime = System.currentTimeMillis(); prometheusCustomMonitor.getReportDialResponseTime().record(endTime-startTime, TimeUnit.MILLISECONDS);
在浏览器访问 http://127.0.0.1:9001/actuator/prometheus ，就可以看到服务的一系列不同类型 metrics 信息，例如jvm_memory_used_bytes gauge、jvm_gc_memory_promoted_bytes_total counter ，go_api_report_dial_request_count等
到此，Spring Boot 工程集成 Micrometer 就已经完成，接下里就要与 Prometheus 进行集成了。
基于 Spring Boot + MyBatis Plus + Vue & Element 实现的后台管理系统 + 用户小程序，支持 RBAC 动态权限、多租户、数据权限、工作流、三方登录、支付、短信、商城等功能
2.集成 Prometheus
2.1安装
docker pull prom/prometheus mdkir /usr/local/prometheus vi prometheus.yml > 基于 Spring Cloud Alibaba + Gateway + Nacos + RocketMQ + Vue & Element 实现的后台管理系统 + 用户小程序，支持 RBAC 动态权限、多租户、数据权限、工作流、三方登录、支付、短信、商城等功能 > > * 项目地址：<https://github.com/YunaiV/yudao-cloud> > * 视频教程：<https://doc.iocoder.cn/video/> # 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). # Alertmanager configuration alerting: alertmanagers: - static_configs: - targets: # - alertmanager:9093 # 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: ['192.168.136.129:9090'] docker run -d --name prometheus -p 9090:9090 -v/usr/local/prometheus/prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheus
2.2集成配置
global: scrape_interval: 15s scrape_configs: - job_name: "prometheus" static_configs: - targets: ["localhost:9090"] - job_name: "metricsLocalTest" metrics_path: "/actuator/prometheus" static_configs: - targets: ["localhost:9003"]
这里 localhost:9001 就是上边本地启动的服务地址，也就是 Prometheus 要监控的服务地址。同时可以添加一些与应用相关的标签，方便后期执行 PromSQL 查询语句区分。最后重启 Prometheus 服务
3.使用 Grafana Dashboard 展示监控项
3.1安装grafana
docker pull grafana/grafana docker run -d --name grafana -p 3000:3000 -v /usr/local/grafana:/var/lib/grafana grafana/grafana
默认用户名/密码 admin/admin
3.2配置prometheus数据源
3.3增加jvm面板
模板编号为4701
3.4配置业务接口监控面板
