Exporter/Client Libraries 开发介绍

Prometheus 提供各种语言的 Client Libraries 来开发 instrumentation metrics 的采集器。这些 lib 库，默认提供如 CPU 使用率、垃圾回收统计信息。

介绍

各种 client 库源代码

• https://github.com/prometheus?q=client
• https://github.com/prometheus/client_golang

实现方式：

• counter: Inc/Dec
• gauge: Set
• histogram(直方图)/summary(百分位): observe
• Collector，实现两个接口
  • Describe
  • Collect

指标采集方式：

• 周期/定时任务触发
• 业务请求时触发，http 请求、异步任务等
• metrics 请求时触发，适用于实时获取指标

认证需自行实现：

• HTTP 认证方式

示例

python prometheus_client

pip install prometheus-client

# https://stackoverflow.com/questions/59924566/export-prometheus-metrics-using-python-code
import prometheus_client as prom
import random
import time

req_summary = prom.Summary('python_my_req_example', 'Time spent processing a request')


@req_summary.time()
def process_request(t):
  time.sleep(t)


if __name__ == '__main__':
  counter = prom.Counter('python_my_counter', 'This is my counter')
  gauge = prom.Gauge('python_my_gauge', 'This is my gauge')
  histogram = prom.Histogram('python_my_histogram', 'This is my histogram')
  summary = prom.Summary('python_my_summary', 'This is my summary')
  prom.start_http_server(8080)

  while True:
    counter.inc(random.random())
    gauge.set(random.random() * 15 - 5)
    histogram.observe(random.random() * 10)
    summary.observe(random.random() * 10)
    process_request(random.random() * 5)
    time.sleep(1)
source repo / download raw

# https://prometheus.github.io/client_python/getting-started/three-step-demo/
from prometheus_client import start_http_server, Summary
import random
import time

# Create a metric to track time spent and requests made.
REQUEST_TIME = Summary('request_processing_seconds', 'Time spent processing request')

# Decorate function with metric.
@REQUEST_TIME.time()
def process_request(t):
    """A dummy function that takes some time."""
    time.sleep(t)

if __name__ == '__main__':
    # Start up the server to expose the metrics.
    start_http_server(8000)
    # Generate some requests.
    while True:
        process_request(random.random())
source repo / download raw

# https://prometheus.github.io/client_python/exporting/http/flask/
from flask import Flask
from werkzeug.middleware.dispatcher import DispatcherMiddleware
from prometheus_client import make_wsgi_app

# Create my app
app = Flask(__name__)

# Add prometheus wsgi middleware to route /metrics requests
app.wsgi_app = DispatcherMiddleware(app.wsgi_app, {
    '/metrics': make_wsgi_app()
})
source repo / download raw

基础使用

package main

import (
	"fmt"
	"log"
	"math/rand"
	"net/http"
	"time"

	"github.com/prometheus/client_golang/prometheus"
	"github.com/prometheus/client_golang/prometheus/promhttp"
)

var diskinfo = []string{"mount"}

var (
	// gauge
	cpuTemp = prometheus.NewGauge(prometheus.GaugeOpts{
		Name: "cpu_temperature_celsius",
		Help: "Current temperature of the CPU.",
	})
	cpuCount = prometheus.NewGauge(prometheus.GaugeOpts{
		Name: "cpu_count",
		Help: "cout count.",
		ConstLabels: prometheus.Labels{
			"key1": "val1",
		},
	})
	disk = prometheus.NewGaugeVec(prometheus.GaugeOpts{
		Name: "disk",
		Help: "disk size info.",
	}, diskinfo)

	// counter
	requestTotal = prometheus.NewCounter(prometheus.CounterOpts{
		Name: "request_total",
		Help: "http request total",
	})
	hdFailures = prometheus.NewCounterVec(
		prometheus.CounterOpts{
			Name: "hd_errors_total",
			Help: "Number of hard-disk errors.",
		},
		[]string{"device"},
	)

	// histogram
	urlRequestTime = prometheus.NewHistogramVec(
		prometheus.HistogramOpts{
			Name:    "url_request_time",
			Help:    "url request time.",
			Buckets: prometheus.LinearBuckets(0, 3, 5),
		}, []string{"url"})

	// summary
	requestSummary = prometheus.NewSummaryVec(
		prometheus.SummaryOpts{
			Name:       "request_time_summary",
			Help:       "request time summary",
			Objectives: map[float64]float64{0.2: 0.1, 0.5: 0.001, 0.99: 0.0001},
		}, []string{"url"})
)

func init() {
	// Metrics have to be registered to be exposed:
	prometheus.MustRegister(cpuCount)
	prometheus.MustRegister(disk)
	prometheus.MustRegister(cpuTemp)

	prometheus.MustRegister(requestTotal)
	prometheus.MustRegister(hdFailures)

	prometheus.MustRegister(urlRequestTime)

	prometheus.MustRegister(requestSummary)
}

func main() {
	cpuCount.Set(4)
	disk.WithLabelValues("/dev/sda").Set(10)
	disk.WithLabelValues("/dev/sdb").Set(10)
	cpuTemp.Set(65.3)

	//requestTotal.Inc()
	hdFailures.With(prometheus.Labels{"device": "/dev/sda"}).Inc()

	// histogram
	//urlRequestTime.WithLabelValues("/url").Observe(10)
	//urlRequestTime.WithLabelValues("/url").Observe(5)
	//requestSummary.WithLabelValues("/url").Observe(10)
	//requestSummary.WithLabelValues("/url").Observe(5)

	// 修改值
	//时间触发：磁盘使用、CPU使用、内存使用
	go func() {
		// for range time.Tick(time.Second) {}
		ticker := time.NewTicker(3 * time.Second)
		for {
			disk.WithLabelValues("/dev/sda").Set(rand.Float64())
			disk.WithLabelValues("/dev/sdb").Set(rand.Float64())
			<-ticker.C
		}
	}()

	// 事件触发，如 HTTP 请求
	http.HandleFunc("/url/", func(writer http.ResponseWriter, request *http.Request) {
		requestTotal.Inc()
		urlRequestTime.WithLabelValues("/url").Observe(rand.Float64())
		requestSummary.WithLabelValues("/url").Observe(rand.Float64())
		writer.Write([]byte("done."))
	})

	// 在访问metrics时触发，只有这两种
	//prometheus.NewGaugeFunc()
	//prometheus.NewCounterFunc()
	fcall := prometheus.NewCounterFunc(prometheus.CounterOpts{
		Name: "abc",
		Help: "abc",
	}, func() float64 {
		fmt.Println("call")
		return rand.Float64()
	})
	prometheus.MustRegister(fcall)

	// The Handler function provides a default handler to expose metrics
	// via an HTTP server. "/metrics" is the usual endpoint for that.
	http.Handle("/metrics", promhttp.Handler())
	log.Fatal(http.ListenAndServe(":8080", nil))
}
source repo / download raw

mysql-exporter 示例

https://github.com/xiexianbin/mysql-exporter

应用监控

beego 实现 web.handler("/metrics", promhttp.Handler())，参考