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随着云计算和容器化技术的不断发展#xff0c;微服务架构逐渐成为现代软件开发的主流趋势。微服务架构将大型应用程序拆分成多个小型、独立的服务#xff0c;每个服务都可以独立开发、部署和扩展。这种架构模式提高了系统的可伸缩性、灵活性和可靠性#xff0c;但同时…背景
随着云计算和容器化技术的不断发展微服务架构逐渐成为现代软件开发的主流趋势。微服务架构将大型应用程序拆分成多个小型、独立的服务每个服务都可以独立开发、部署和扩展。这种架构模式提高了系统的可伸缩性、灵活性和可靠性但同时也带来了服务监控和管理的挑战。
在微服务架构中服务之间的依赖关系变得复杂服务数量众多因此需要一种有效的监控和管理工具来确保系统的稳定性和可靠性。监控工具可以帮助开发人员实时了解服务的运行状态、性能指标和异常情况从而及时发现问题并进行处理。同时管理工具还可以提供自动化的部署、配置和扩展功能提高开发效率和运维质量。 Prometheus的优势 请求、数据库查询、消息队列等应用指标。 高效数据存储Prometheus采用时间序列数据库TSDB来存储监控数据具有高效的数据压缩和查询性能。 丰富查询语言Prometheus提供了强大的数据查询语言PromQL可以方便地对监控数据进行过滤、聚合和计算。 灵活告警机制Prometheus支持基于规则的告警机制可以根据监控数据的阈值触发告警通知支持多种告警方式如邮件、短信、Slack等。 springBoot集成Prometheus 导入Pom依赖
dependencygroupIdorg.mybatis.spring.boot/groupIdartifactIdspring-boot-starter-actuator/artifactIdversion2.2.1.RELEASE/version
/dependency
dependencygroupIdio.micrometer/groupIdartifactIdmicrometer-registry-prometheus/artifactIdversion1.3.1/version
/dependency
修改springBoot配置文件
开启prometheus监控配置
management:endpoint:prometheus:enabled: trueendpoints:web:exposure:include: prometheus
修改默认的Prometheus监控度量名称
prometheus默认指标中有个http.server.requests的度量名称记录了http请求调用情况现在以这个为例修改名称
新建一个Configuration 类 PrometheusConfig
import io.micrometer.core.instrument.Meter;
import io.micrometer.core.instrument.MeterRegistry;
import io.micrometer.core.instrument.config.NamingConvention;
import org.springframework.boot.actuate.autoconfigure.metrics.MeterRegistryCustomizer;
import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;import java.util.Arrays;
import java.util.Objects;
import java.util.stream.Collectors;Configuration
public class PrometheusConfig {/** 用于替换 Prometheus中 公共的 http.server.requests度量名替换* return*/BeanMeterRegistryCustomizerMeterRegistry metricsConfig() {return registry - registry.config().namingConvention(new NamingConvention() {Overridepublic String name(String name, Meter.Type type, String baseUnit) {String collect ;if(name.contains(http.server.requests)){collect Arrays.stream(name.replaceAll(http.server.requests, jiang.xiao.yu.http).split(\\.)).filter(Objects::nonNull).collect(Collectors.joining(_));}else {collect Arrays.stream(name.split(\\.)).filter(Objects::nonNull).collect(Collectors.joining(_));}return collect;}});}
}
自定义Prometheus监控指标
使用拦截器监控指标
利用拦截器实现所有HTTP接口的监控
利用HTTP的拦截器添加Prometheus的监控指标首先创建一个拦截器CustomInterceptor 实现HandlerInterceptor接口然后重写里面的 前置处理、后置处理
import io.micrometer.core.instrument.*;
import org.springframework.web.servlet.HandlerInterceptor;
import org.springframework.web.servlet.ModelAndView;
import javax.servlet.http.HttpServletRequest;
import javax.servlet.http.HttpServletResponse;
import java.util.*;
import java.util.concurrent.TimeUnit;
import java.util.function.ToDoubleFunction;public class CustomInterceptor implements HandlerInterceptor {private static final String CUSTOM_KPI_NAME_TIMER custom.kpi.timer; //耗时private static final String CUSTOM_KPI_NAME_COUNTER custom.kpi.counter; //api调用次数。private static final String CUSTOM_KPI_NAME_SUMMARY custom.kpi.summary; //汇总率private static MeterRegistry registry;private long startTime;private GaugeNumber gaugeNumber new GaugeNumber();void getRegistry(){if(registry null){//这里使用的时SpringUtil获取Bean没有用Autowired注解Autowired会因为加载时机问题导致拿不到SpringUtil.getBean网上实现有很多可以自行搜索registry SpringUtil.getBean(MeterRegistry.class);}}Overridepublic boolean preHandle(HttpServletRequest request, HttpServletResponse response, Object handler) throws Exception {getRegistry();//记录接口开始调用的时间startTime System.currentTimeMillis();return HandlerInterceptor.super.preHandle(request, response, handler);}Overridepublic void postHandle(HttpServletRequest request, HttpServletResponse response, Object handler, ModelAndView modelAndView) throws Exception {HandlerInterceptor.super.postHandle(request, response, handler, modelAndView);}Overridepublic void afterCompletion(HttpServletRequest request, HttpServletResponse response, Object handler, Exception ex) throws Exception {//统计调用次数registry.counter(CUSTOM_KPI_NAME_COUNTER,uri, request.getRequestURI(), method, request.getMethod(),status, response.getStatus() , exception, ex null ? : ex.getMessage(), outcome, response.getStatus() 200 ? SUCCESS : CLIENT_ERROR).increment();//统计单次耗时registry.timer(CUSTOM_KPI_NAME_TIMER,uri, request.getRequestURI(), method, request.getMethod(),status, response.getStatus() , exception, ex null ? : ex.getMessage(), outcome, response.getStatus() 200 ? SUCCESS : CLIENT_ERROR).record(System.currentTimeMillis() - startTime, TimeUnit.MILLISECONDS);//统计调用成功率根据过滤Counter对象获取计数CollectionMeter meters registry.get(CUSTOM_KPI_NAME_COUNTER).tag(uri, request.getRequestURI()).tag(method, request.getMethod()).meters();double total 0;double success 0;for (Meter meter : meters) {Counter counter (Counter) meter;total counter.count();String status meter.getId().getTag(status);if (status.equals(200)){success counter.count();}}//保存对应的成功率到Map中String key request.getMethod() request.getRequestURI();gaugeNumber.setPercent(key, Double.valueOf(success / total * 100L));registry.gauge(CUSTOM_KPI_NAME_SUMMARY, Tags.of(uri, request.getRequestURI(), method, request.getMethod()), gaugeNumber, new ToDoubleFunctionGaugeNumber() {Overridepublic double applyAsDouble(GaugeNumber value) {return value.getPercent(key);}});HandlerInterceptor.super.afterCompletion(request, response, handler, ex);}// gauge监控某个对象所以用内部类替代然后根据tag标签区分对应的成功率key 为 method uriclass GaugeNumber {MapString,Double map new HashMap();public Double getPercent(String key) {return map.get(key);}public void setPercent(String key, Double percent) {map.put(key, percent);}}
}
注册自定义拦截器给Spring
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 CustomInterceptors implements WebMvcConfigurer {Overridepublic void addInterceptors(InterceptorRegistry registry) {registry.addInterceptor(new CustomInterceptor()).addPathPatterns(/**);}
}
大功告成启动程序测试吧 使用AOP记录监控指标
自定义指标注解
Documented
Retention(RetentionPolicy.RUNTIME)
Target(ElementType.METHOD)
public interface MethodMetrics {String name() default ;String desc() default ;String[] tags() default {};//是否记录时间间隔boolean withoutDuration() default false;
}
切面实现
Aspect
public class PrometheusAnnotationAspect {Autowiredprivate MeterRegistry meterRegistry;Pointcut(annotation(com.smac.prometheus.annotation.MethodMetrics))public void pointcut() {}Around(value pointcut())public Object process(ProceedingJoinPoint joinPoint) throws Throwable {Method targetMethod ((MethodSignature) joinPoint.getSignature()).getMethod();Method currentMethod ClassUtils.getUserClass(joinPoint.getTarget().getClass()).getDeclaredMethod(targetMethod.getName(), targetMethod.getParameterTypes());if (currentMethod.isAnnotationPresent(MethodMetrics.class)) {MethodMetrics methodMetrics currentMethod.getAnnotation(MethodMetrics.class);return processMetric(joinPoint, currentMethod, methodMetrics);} else {return joinPoint.proceed();}}private Object processMetric(ProceedingJoinPoint joinPoint, Method currentMethod, MethodMetrics methodMetrics) {String name methodMetrics.name();if (!StringUtils.hasText(name)) {name currentMethod.getName();}String desc methodMetrics.desc();if (!StringUtils.hasText(desc)) {desc currentMethod.getName();}//不需要记录时间if (methodMetrics.withoutDuration()) {Counter counter Counter.builder(name).tags(methodMetrics.tags()).description(desc).register(meterRegistry);try {return joinPoint.proceed();} catch (Throwable e) {throw new IllegalStateException(e);} finally {counter.increment();}}//需要记录时间默认Timer timer Timer.builder(name).tags(methodMetrics.tags()).description(desc).register(meterRegistry);return timer.record(() - {try {return joinPoint.proceed();} catch (Throwable e) {throw new IllegalStateException(e);}});}
}
在需要记监控的地方加上这个注解
MethodMetrics(namesms_send,tags {vendor})
public void send(String mobile, SendMessage message) throws Exception {//do something
}
