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Actuator + Prometheus + Grafana搭建微服务监控平台
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[TOC] 前言关于Actuator： 对Spring Boot监控能力有过了解的小伙伴都应该知道Spring Boot Actuator这个子项目，它为应用提供了强大的监控能力。从Spring Boot 2.x开始，Actuator将底层改为Micrometer，提供了更强、更灵活的监控能力。Micrometer是一个监控门面，可以类比成监控界的 Slf4j 。借助Micrometer，应用能够对接各种监控系统，例如本文所要介绍的：Prometheus 关于Prometheus ： Prometheus是一个由SoundCloud开发的开源系统监控+告警+时序列数据库(TSDB)，Prometheus大部分组件使用Go语言编写，是Google BorgMon监控系统的开源版本。目前在CNCF基金会托管，并已成功孵化。在开源社区Prometheus目前也是相当活跃，在性能上Prometheus也足够支撑上万台规模的集群。 Prometheus的功能： 用度量名和键值对识别时间序列数据的多维数据模型拥有灵活的查询语言：PromQL不依赖分布式存储，单个服务器节点是自治的通过基于HTTP的pull方式采集时序数据可以通过中间网关进行时序列数据的推送支持通过服务发现或者静态配置来发现目标服务对象支持多种多样的图表和界面展示，比如Grafana等更多内容参考：官方文档，GitHub仓库 关于Grafana： Grafana 是一款采用 GO 语言编写的开源应用，支持跨平台度量分析和可视化 + 告警。可以通过将采集的数据查询然后可视化地展示，并及时通知。Grafana 支持多种数据源和展示方式，总而言之是一款强大酷炫的监控指标可视化工具。 更多内容参考：官方文档，GitHub仓库 创建项目本文的主要目的是实现微服务的监控，简单了解了上述工具的概念后，我们就来动手实践一下。首先创建一个简单的Spring Boot项目，其主要依赖如下： 代码语言：javascript复制 org.springframework.boot spring-boot-starter-web org.springframework.boot spring-boot-starter-actuator io.micrometer micrometer-registry-prometheus Tips：这里如果想要对接其他的监控系统，只需要更改依赖的包名。例如想对接 Influx ，则将依赖改为 micrometer-registry-influx 即可。编辑项目配置： 代码语言：javascript复制server: port: 9562 spring: application: # 指定应用名 name: prometheus-demo management: endpoints: web: exposure: # 将 Actuator 的 /actuator/prometheus 端点暴露出来 include: 'prometheus' metrics: tags: # 为指标设置一个Tag，这里设置为应用名，Tag是Prometheus提供的一种能力，从而实现更加灵活的筛选 application: ${spring.application.name}完成以上步骤后，进行一个简单的测试，看看端点是否能正常返回监控数据。启动项目，访问/actuator/prometheus端点。正常情况下会返回如下内容： 代码语言：javascript复制# HELP process_start_time_seconds Start time of the process since unix epoch. # TYPE process_start_time_seconds gauge process_start_time_seconds{application="prometheus-demo",} 1.577697308142E9 # HELP jvm_buffer_memory_used_bytes An estimate of the memory that the Java virtual machine is using for this buffer pool # TYPE jvm_buffer_memory_used_bytes gauge jvm_buffer_memory_used_bytes{application="prometheus-demo",id="mapped",} 0.0 jvm_buffer_memory_used_bytes{application="prometheus-demo",id="direct",} 16384.0 # HELP tomcat_sessions_expired_sessions_total # TYPE tomcat_sessions_expired_sessions_total counter tomcat_sessions_expired_sessions_total{application="prometheus-demo",} 0.0 # HELP jvm_gc_pause_seconds Time spent in GC pause # TYPE jvm_gc_pause_seconds summary jvm_gc_pause_seconds_count{action="end of minor GC",application="prometheus-demo",cause="Metadata GC Threshold",} 1.0 jvm_gc_pause_seconds_sum{action="end of minor GC",application="prometheus-demo",cause="Metadata GC Threshold",} 0.006 jvm_gc_pause_seconds_count{action="end of major GC",application="prometheus-demo",cause="Metadata GC Threshold",} 1.0 jvm_gc_pause_seconds_sum{action="end of major GC",application="prometheus-demo",cause="Metadata GC Threshold",} 0.032 jvm_gc_pause_seconds_count{action="end of minor GC",application="prometheus-demo",cause="Allocation Failure",} 1.0 jvm_gc_pause_seconds_sum{action="end of minor GC",application="prometheus-demo",cause="Allocation Failure",} 0.008 # HELP jvm_gc_pause_seconds_max Time spent in GC pause # TYPE jvm_gc_pause_seconds_max gauge jvm_gc_pause_seconds_max{action="end of minor GC",application="prometheus-demo",cause="Metadata GC Threshold",} 0.006 jvm_gc_pause_seconds_max{action="end of major GC",application="prometheus-demo",cause="Metadata GC Threshold",} 0.032 jvm_gc_pause_seconds_max{action="end of minor GC",application="prometheus-demo",cause="Allocation Failure",} 0.008 # HELP jvm_memory_used_bytes The amount of used memory # TYPE jvm_memory_used_bytes gauge jvm_memory_used_bytes{application="prometheus-demo",area="heap",id="PS Survivor Space",} 0.0 jvm_memory_used_bytes{application="prometheus-demo",area="heap",id="PS Old Gen",} 1.3801776E7 jvm_memory_used_bytes{application="prometheus-demo",area="nonheap",id="Metaspace",} 3.522832E7 jvm_memory_used_bytes{application="prometheus-demo",area="nonheap",id="Code Cache",} 6860800.0 jvm_memory_used_bytes{application="prometheus-demo",area="heap",id="PS Eden Space",} 1.9782928E7 jvm_memory_used_bytes{application="prometheus-demo",area="nonheap",id="Compressed Class Space",} 4825568.0 # HELP logback_events_total Number of error level events that made it to the logs # TYPE logback_events_total counter logback_events_total{application="prometheus-demo",level="info",} 7.0 logback_events_total{application="prometheus-demo",level="trace",} 0.0 logback_events_total{application="prometheus-demo",level="warn",} 0.0 logback_events_total{application="prometheus-demo",level="debug",} 0.0 logback_events_total{application="prometheus-demo",level="error",} 0.0 # HELP process_uptime_seconds The uptime of the Java virtual machine # TYPE process_uptime_seconds gauge process_uptime_seconds{application="prometheus-demo",} 30.499 # 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{application="prometheus-demo",id="mapped",} 0.0 jvm_buffer_count_buffers{application="prometheus-demo",id="direct",} 2.0 # HELP system_cpu_count The number of processors available to the Java virtual machine # TYPE system_cpu_count gauge system_cpu_count{application="prometheus-demo",} 6.0 # HELP jvm_threads_peak_threads The peak live thread count since the Java virtual machine started or peak was reset # TYPE jvm_threads_peak_threads gauge jvm_threads_peak_threads{application="prometheus-demo",} 22.0 # HELP tomcat_sessions_alive_max_seconds # TYPE tomcat_sessions_alive_max_seconds gauge tomcat_sessions_alive_max_seconds{application="prometheus-demo",} 0.0 # HELP jvm_memory_committed_bytes The amount of memory in bytes that is committed for the Java virtual machine to use # TYPE jvm_memory_committed_bytes gauge jvm_memory_committed_bytes{application="prometheus-demo",area="heap",id="PS Survivor Space",} 1.5204352E7 jvm_memory_committed_bytes{application="prometheus-demo",area="heap",id="PS Old Gen",} 1.31596288E8 jvm_memory_committed_bytes{application="prometheus-demo",area="nonheap",id="Metaspace",} 3.7879808E7 jvm_memory_committed_bytes{application="prometheus-demo",area="nonheap",id="Code Cache",} 6881280.0 jvm_memory_committed_bytes{application="prometheus-demo",area="heap",id="PS Eden Space",} 1.76685056E8 jvm_memory_committed_bytes{application="prometheus-demo",area="nonheap",id="Compressed Class Space",} 5373952.0 # 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{application="prometheus-demo",id="mapped",} 0.0 jvm_buffer_total_capacity_bytes{application="prometheus-demo",id="direct",} 16384.0 # HELP jvm_gc_live_data_size_bytes Size of old generation memory pool after a full GC # TYPE jvm_gc_live_data_size_bytes gauge jvm_gc_live_data_size_bytes{application="prometheus-demo",} 1.3801776E7 # HELP jvm_memory_max_bytes The maximum amount of memory in bytes that can be used for memory management # TYPE jvm_memory_max_bytes gauge jvm_memory_max_bytes{application="prometheus-demo",area="heap",id="PS Survivor Space",} 1.5204352E7 jvm_memory_max_bytes{application="prometheus-demo",area="heap",id="PS Old Gen",} 2.841116672E9 jvm_memory_max_bytes{application="prometheus-demo",area="nonheap",id="Metaspace",} -1.0 jvm_memory_max_bytes{application="prometheus-demo",area="nonheap",id="Code Cache",} 2.5165824E8 jvm_memory_max_bytes{application="prometheus-demo",area="heap",id="PS Eden Space",} 1.390411776E9 jvm_memory_max_bytes{application="prometheus-demo",area="nonheap",id="Compressed Class Space",} 1.073741824E9 # HELP jvm_threads_daemon_threads The current number of live daemon threads # TYPE jvm_threads_daemon_threads gauge jvm_threads_daemon_threads{application="prometheus-demo",} 18.0 # HELP jvm_threads_states_threads The current number of threads having NEW state # TYPE jvm_threads_states_threads gauge jvm_threads_states_threads{application="prometheus-demo",state="runnable",} 8.0 jvm_threads_states_threads{application="prometheus-demo",state="new",} 0.0 jvm_threads_states_threads{application="prometheus-demo",state="timed-waiting",} 2.0 jvm_threads_states_threads{application="prometheus-demo",state="blocked",} 0.0 jvm_threads_states_threads{application="prometheus-demo",state="waiting",} 12.0 jvm_threads_states_threads{application="prometheus-demo",state="terminated",} 0.0 # HELP jvm_gc_memory_promoted_bytes_total Count of positive increases in the size of the old generation memory pool before GC to after GC # TYPE jvm_gc_memory_promoted_bytes_total counter jvm_gc_memory_promoted_bytes_total{application="prometheus-demo",} 8296848.0 # HELP tomcat_sessions_active_max_sessions # TYPE tomcat_sessions_active_max_sessions gauge tomcat_sessions_active_max_sessions{application="prometheus-demo",} 0.0 # HELP tomcat_sessions_created_sessions_total # TYPE tomcat_sessions_created_sessions_total counter tomcat_sessions_created_sessions_total{application="prometheus-demo",} 0.0 # HELP jvm_gc_memory_allocated_bytes_total Incremented for an increase in the size of the young generation memory pool after one GC to before the next # TYPE jvm_gc_memory_allocated_bytes_total counter jvm_gc_memory_allocated_bytes_total{application="prometheus-demo",} 1.36924824E8 # HELP process_cpu_usage The "recent cpu usage" for the Java Virtual Machine process # TYPE process_cpu_usage gauge process_cpu_usage{application="prometheus-demo",} 0.10024585094452443 # HELP system_cpu_usage The "recent cpu usage" for the whole system # TYPE system_cpu_usage gauge system_cpu_usage{application="prometheus-demo",} 0.38661791030714154 # HELP tomcat_sessions_active_current_sessions # TYPE tomcat_sessions_active_current_sessions gauge tomcat_sessions_active_current_sessions{application="prometheus-demo",} 0.0 # HELP jvm_classes_loaded_classes The number of classes that are currently loaded in the Java virtual machine # TYPE jvm_classes_loaded_classes gauge jvm_classes_loaded_classes{application="prometheus-demo",} 7195.0 # HELP http_server_requests_seconds # TYPE http_server_requests_seconds summary http_server_requests_seconds_count{application="prometheus-demo",exception="None",method="GET",outcome="CLIENT_ERROR",status="404",uri="/**",} 1.0 http_server_requests_seconds_sum{application="prometheus-demo",exception="None",method="GET",outcome="CLIENT_ERROR",status="404",uri="/**",} 0.012429856 # HELP http_server_requests_seconds_max # TYPE http_server_requests_seconds_max gauge http_server_requests_seconds_max{application="prometheus-demo",exception="None",method="GET",outcome="CLIENT_ERROR",status="404",uri="/**",} 0.012429856 # 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{application="prometheus-demo",} 2.841116672E9 # HELP jvm_threads_live_threads The current number of live threads including both daemon and non-daemon threads # TYPE jvm_threads_live_threads gauge jvm_threads_live_threads{application="prometheus-demo",} 22.0 # 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{application="prometheus-demo",} 1.0 # HELP tomcat_sessions_rejected_sessions_total # TYPE tomcat_sessions_rejected_sessions_total counter tomcat_sessions_rejected_sessions_total{application="prometheus-demo",} 0.0该端点返回的数据是Prometheus需要使用的。每一项都有相应的注释解释其含义，相信不难看懂。例如： 代码语言：javascript复制# HELP jvm_memory_used_bytes The amount of used memory # TYPE jvm_memory_used_bytes gauge jvm_memory_used_bytes{application="prometheus-demo",area="heap",id="PS Survivor Space",} 0.0表示：prometheus-demo 应用堆内存中的 PS Survivor Space 区域占用的空间是 0.0 个字节。 安装Prometheus服务接下来就是需要在服务器上安装Prometheus服务，用于从微服务暴露的监控端点中采集监控数据。为了简单起见，我这里采用docker的安装方式，其他安装方式可以参考 官方安装文档。 首先为Prometheus准备一个配置文件： 代码语言：javascript复制[root@localhost ~]# mkdir /etc/prometheus [root@localhost ~]# vim /etc/prometheus/prometheus.yml scrape_configs: # 任意写，建议英文，不要包含特殊字符 - job_name: 'spring' # 多久采集一次数据 scrape_interval: 15s # 采集时的超时时间 scrape_timeout: 10s # 采集的端点 metrics_path: '/actuator/prometheus' # 被采集的服务地址，即微服务的ip及端口 static_configs: - targets: ['192.168.1.252:9562']该配置文件的目的是让Prometheus服务自动每隔15秒请求 http://192.168.1.252:9562/actuator/prometheus 。更多配置项参考：Prometheus Configuration官方文档 最后通过docker启动Prometheus服务，命令如下： 代码语言：javascript复制[root@localhost ~]# docker run -d -p 9090:9090 -v /etc/prometheus/prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheus --config.file=/etc/prometheus/prometheus.yml启动成功后，正常情况下访问http://{ip}:9090，就可以看到Prometheus的首页：  Actuator + Prometheus + Grafana搭建微服务监控平台点击 Insert metric at cursor ，即可选择监控指标；点击 Graph ，即可让指标以图表方式展示；点击Execute 按钮，即可看到类似下图的结果：  Actuator + Prometheus + Grafana搭建微服务监控平台功能说明： Insert metric at cursor：选择展示的指标Graph：让指标以图形展示Execute：绘制指标图表信息Add Graph：绘制更多指标图表Grafana可视化上一小节我们已经成功搭建了Prometheus服务，并简单介绍了Prometheus自带的监控数据可视化界面，然而使用体验并不好，功能也比较少。下面我们来集成Grafana实现更友好、更贴近生产的监控数据可视化平台。 同样需要在服务器上安装Grafana服务，为了简单起见，我这里依旧采用docker的安装方式。其他安装方式可以参考 官方安装文档。 使用docker只需要一行命令就可以启动Grafana，如下： 代码语言：javascript复制[root@localhost ~]# docker run -d -p 3000:3000 grafana/grafana配置监控数据源Grafana启动成功后，访问http://{ip}:3000/login进行登录，默认账户密码均为admin：  Actuator + Prometheus + Grafana搭建微服务监控平台登录成功后，首页如下：  Actuator + Prometheus + Grafana搭建微服务监控平台首先需要添加监控数据的来源，点击首页中的Add data source ，即可看到类似如下的界面：  Actuator + Prometheus + Grafana搭建微服务监控平台这里点击Prometheus，即可看到类似如下界面，在这里配置Prometheus服务相关的信息：  Actuator + Prometheus + Grafana搭建微服务监控平台保存成功后会有如下提示：  Actuator + Prometheus + Grafana搭建微服务监控平台创建监控Dashboard点击导航栏上的 + 按钮，并点击Dashboard，将会看到类似如下的界面：  Actuator + Prometheus + Grafana搭建微服务监控平台点击 Add Query ，即可看到类似如下的界面：  Actuator + Prometheus + Grafana搭建微服务监控平台在红框标记的位置添加指标查询，指标的取值详见Spring Boot应用的 /actuator/prometheus 端点，例如jvm_memory_used_bytes 、jvm_threads_states_threads 、jvm_threads_live_threads 等。 Grafana会给你较好的提示，并且支持较为复杂的计算，例如聚合、求和、平均等。如果想要绘制多个线条，可点击Add Query 按钮。如上图所示，笔者为图表绘制了两条线，分别代表daemon以及peak线程。 点击下图的按钮，并填入Title，即可设置图表标题：  Actuator + Prometheus + Grafana搭建微服务监控平台若需要为Dashboard添加新的图表则点击上图中的左上角按钮：  Actuator + Prometheus + Grafana搭建微服务监控平台并按下图步骤操作即可：  Actuator + Prometheus + Grafana搭建微服务监控平台如果需要保存该Dashboard，则点击右上角的保存按钮即可：  Actuator + Prometheus + Grafana搭建微服务监控平台 Actuator + Prometheus + Grafana搭建微服务监控平台Dashboard市场至此，我们已经成功将Grafana与Prometheus集成，实现了较为丰富的图表展示——将关心的监控指标放置到Dashboard上，并且非常灵活！然而，这个配置的操作虽然不难，但还是挺费时间的。 那么是否有配置好的又强大、又通用、拿来即用的Dashboard呢？答案是肯定的！前往 Grafana Lab - Dashboards ，输入关键词即可搜索指定Dashboard：  Actuator + Prometheus + Grafana搭建微服务监控平台如上图所示，可以找到若干款以 Prometheus 作为数据源，支持Micrometer的Dashboard。下面，简单演示一下如何使用 JVM(Micrometer) 这个Dashboard。点击 JVM(Micrometer) 进入Dashboard详情介绍页，如下图所示：  Actuator + Prometheus + Grafana搭建微服务监控平台如图已详细描述了该Dashboard的特性、配置。其中的managementrics.tags.application ，前面安装Prometheus服务时已经配置过了。该页的右上角用红框标注的 4701 是一个非常重要的数字，因为这是该Dashboard的id。 回到Grafana的首页，我们来导入这个Dashboard，按下图步骤操作：  Actuator + Prometheus + Grafana搭建微服务监控平台输入后即可看到类似如下的界面，选择数据源，并点击Import：  Actuator + Prometheus + Grafana搭建微服务监控平台此时，即可看到类似如下的界面，我们常关心的指标该Dashboard均已支持：  Actuator + Prometheus + Grafana搭建微服务监控平台在上方的选项栏中可以选择查看不同的服务/应用：  Actuator + Prometheus + Grafana搭建微服务监控平台此外，还有一些比较好用的Dashboard，可以自行了解一下这里就不赘述了： JVM (Actuator)Spring Boot Statistics |
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