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? 在最新SpringBoot2.0中，Micrometer門面已經(jīng)整合到了spring-boot-starter-actuator項(xiàng)目中，我們只需引入相應(yīng)的具體實(shí)現(xiàn)包即可對(duì)接到相應(yīng)的監(jiān)控系統(tǒng)，本次將使用promethues來監(jiān)控、采集SpringBoot的指標(biāo)數(shù)據(jù)。

引入promehtus依賴

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

配置指標(biāo)endpoint

默認(rèn)情況下指標(biāo)的endpoint可以與服務(wù)同一個(gè)端口，通常為了不對(duì)業(yè)務(wù)造成干擾，使用額外的端口向外暴露指標(biāo)endpoint，只需更改application.yml即可實(shí)現(xiàn)，如下：

management:
  endpoints:
    web:
      exposure:
        include: "*"
  server:
    port: 30000

瀏覽器訪問http://localhost:30000/actuator/metrics 可以查看到目前存在監(jiān)控指標(biāo)，這些指標(biāo)都是默認(rèn)開啟的。

image-20201210154752319

使用promethues采集指標(biāo)數(shù)據(jù)

目前dockerHub上未提供官方的鏡像，這里還使用二進(jìn)制文件的方式來進(jìn)行監(jiān)控?cái)?shù)據(jù)的采集，下載完二進(jìn)制包后，需修改promethues.yml文件，配置scrape_configs，詳細(xì)如下：

# 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'
    scrape_interval: 5s
    metrics_path: '/actuator/prometheus' #指標(biāo)路徑
    # metrics_path defaults to '/metrics'
    # scheme defaults to 'http'.

    static_configs:
    - targets: ['127.0.0.1:30000'] #指標(biāo)暴露地址端口

啟動(dòng)promethues

./prometheus --config.file=./prometheus.yml

使用Grafana可視化指標(biāo)

這里使用docker運(yùn)行g(shù)rafana，默認(rèn)賬號(hào)密碼：admin/admin

docker run -d -p 3000:3000 grafana/grafana

來到設(shè)置，準(zhǔn)備添加數(shù)據(jù)源。

image-20201210160946826

這里選擇promethues

image-20201210161114105

輸入 ip（ip不能填127.0.0.1 或者是localhost，局域網(wǎng)ip就行） 和 端口即可，點(diǎn)擊下面的save&Test完成數(shù)據(jù)源的添加。

添加Panel，這里選之前創(chuàng)建的數(shù)據(jù)源，選擇指標(biāo)即可實(shí)現(xiàn)可視化。

image-20201210161839159

監(jiān)控http響應(yīng)

默認(rèn)已經(jīng)開啟了http請(qǐng)求的監(jiān)控，但是未開啟histogram

management:
  endpoints:
    web:
      exposure:
        include: "*"
  server:
    port: 30000
  metrics:
    distribution:
      percentiles-histogram[http.server.requests]: true 
      maximum-expected-value[http.server.requests]: 10000 #預(yù)期最大值
      minimum-expected-value[http.server.requests]: 1 #預(yù)期最小值

編寫測(cè)試接口

@RestController
public class TestController {


    @GetMapping(value = "/hello")
    public String helloPromethues(){
        try {

            TimeUnit.MILLISECONDS.sleep(new Random().nextInt(1000));
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
        return  "helloPromethues";
    }
}

使用wrk壓測(cè)該接口

wrk -t4 -c2000 -d100s  http://127.0.0.1:8080/hello

在Grafana中創(chuàng)建Panel，指標(biāo)選擇http_server_requests_seconds_bucket，并修改Y軸單位為秒。

image-20201210165035652

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