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Go语言开发一个完整的exporter

zsx_yiyiyi 2024-06-17 10:19:58

简介Go语言开发一个完整的exporter

Go语言开发一个完整的exporter

Prometheus 官方和社区提供了非常多的 exporter，涵盖数据库、中间件、OS、存储、硬件设备等，具体可查

看：

https://github.com/prometheus/docs/blob/main/content/docs/instrumenting/exporters.md

https://exporterhub.io/

通过这些 exporter 基本可以覆盖80%的监控需求，然后很多场景下需要自己定义监控指标，那么我们就需要自己

开发 exporter ，本文我们将通过获取CPU和内存的监控细信息来编写一个完整的expoter。

1、项目结构

# tree
my_go_exporter/
├── collector
│   └── collector.go
├── data
│   ├── cpu_data.go
│   └── memory_data.go
├── global
│   └── global.go
├── go.mod
├── go.sum
├── handle
│   ├── cpu_handle.go
│   └── memory_handle.go
├── main.go
└── scraper
    ├── cpu_scraper.go
    ├── memory_scraper.go
    └── scrape.go

data：获取 CPU 和 Memory 信息。

global：主要是存放一些全局使用的公共属性。

handler：定义一个 httphandler 来处理http请求。

scrape：scrape 在 prometheus 里的功能是数据采集器，在这里主要是全局 scrape 的 interface 和其具体实现。

collector：collector 文件在本文这里类似数据注册器，所有的 scrape 需要被注册到 collector 里才能真正的被调

用，将数据暴露出去。

main.go：实现 web 接口，供外部访问。

1、global全局属性定义

global.go

package global

const (
	Namespace = "my_exporter"
	Subsystem = "sub_exporter"
)

2、cpu和memory数据获取

这里只是随机生成一些结果，并没有真正的去获取这些数据。

cpu_data.go

package data

import "math/rand"

// 这里模拟的是假数据
// CPU使用率
func GetCpuData(str string) float64 {
	cpuData := map[string]float64{
		"192.168.164.100:7547": rand.Float64() * 100,
		"192.168.164.101:7547": rand.Float64() * 100,
	}
	return cpuData[str]
}

memory_data.go

package data

import "math/rand"

// 这里模拟的是假数据
// Memory使用率
func GetMemoryData(str string) float64 {
	memoryData := map[string]float64{
		"192.168.164.100:8547": rand.Float64() * 100,
		"192.168.164.101:8547": rand.Float64() * 100,
	}
	return memoryData[str]
}

3、scrape定义指标信息

scrape.go

package scraper

import "github.com/prometheus/client_golang/prometheus"

// 所有指标收集需要满足Name和Scrape两个方法
// Name返回指标名字来用于用户开关指标
type Scraper interface {

	// Scraper的名字,必须是唯一的
	Name() string

	// Scraper的描述信息,该方法可选
	Help() string

	// Scrape从客户端收集数据,并将其作为prometheus metric通过通道发送
	Scrape(ch chan<- prometheus.Metric) error
}

Scrape 的参数没什么要说的，这里可以根据不同的监控目的添加不同的链接驱动

如果是 mysqld_exporter 的话需要换成

Scrape(db *sql.DB, ch chan<- prometheus.Metric) error

如果是 redis_exporter 的话换成

Scrape(c *redis.Conn, ch chan<- prometheus.Metric) error

cpu_scraper.go

package scraper

import (
	"exporter/data"
	"exporter/global"
	"fmt"
	"github.com/prometheus/client_golang/prometheus"
)

// 实现Scraper接口
type CpuScraper struct {
	CSName string
	CSHelp string
	Ip     string
	Port   string
}

func (cpuScraper *CpuScraper) Name() string {
	return cpuScraper.CSName
}

func (cpuScraper *CpuScraper) Help() string {
	return cpuScraper.CSHelp
}

func (cpuScraper *CpuScraper) Scrape(ch chan<- prometheus.Metric) error {
	ch <- prometheus.MustNewConstMetric(
		prometheus.NewDesc(
			prometheus.BuildFQName(global.Namespace, global.Subsystem, cpuScraper.CSName),
			// 动态标签的键,可以包含多个
			cpuScraper.CSHelp, []string{"user1", "user2"},
			prometheus.Labels{"ip": cpuScraper.Ip, "port": cpuScraper.Port},
		),
		prometheus.GaugeValue,
		// 指标值
		data.GetCpuData(fmt.Sprintf("%s:%s", cpuScraper.Ip, cpuScraper.Port)),
		// 动态标签的值,与上面动态标签的键相互对应,可以包含多个,多个用逗号分割
		"root1", "root2",
	)
	return nil
}

memory_scraper.go

package scraper

import (
	"exporter/data"
	"exporter/global"
	"fmt"
	"github.com/prometheus/client_golang/prometheus"
)

// 实现Scraper接口
type MemoryScraper struct {
	MSName string
	MSHelp string
	Ip     string
	Port   string
}

func (memoryScraper *MemoryScraper) Name() string {
	return memoryScraper.MSName
}

func (memoryScraper *MemoryScraper) Help() string {
	return memoryScraper.MSHelp
}

func (memoryScraper *MemoryScraper) Scrape(ch chan<- prometheus.Metric) error {
	ch <- prometheus.MustNewConstMetric(
		prometheus.NewDesc(
			prometheus.BuildFQName(global.Namespace, global.Subsystem, memoryScraper.MSName),
			// 动态标签的键,可以包含多个
			memoryScraper.MSHelp, []string{"user3", "user4"},
			prometheus.Labels{"ip": memoryScraper.Ip, "port": memoryScraper.Port},
		),
		prometheus.GaugeValue,
		// 指标值
		data.GetMemoryData(fmt.Sprintf("%s:%s", memoryScraper.Ip, memoryScraper.Port)),
		// 动态标签的值,与上面动态标签的键相互对应,可以包含多个,多个用逗号分割
		"root4", "root4",
	)
	return nil
}

NewDesc 参数第一个为指标的名称，第二个为帮助信息，显示在指标的上面作为注释，第三个是定义的 label 名

称，为数组，第四个是定义的 Labels。

4、collector抓取数据并返回数据

collector.go

package collector

import (
	"exporter/global"
	"exporter/scraper"
	"github.com/prometheus/client_golang/prometheus"
	log "github.com/sirupsen/logrus"
	"sync"
)

// 这里额外可以添加一些指标,用来监控exporter
type Metrics struct {
	// 收集指标的总次数
	TotalScrapes prometheus.Counter
	// 收集指标中发生错误的次数
	ScrapeErrors *prometheus.CounterVec
	// 最后一次是否发生了错误
	Error prometheus.Gauge
}

type Exporter struct {
	metrics  Metrics
	scrapers []scraper.Scraper
}

// 添加描述符
func (e *Exporter) Describe(ch chan<- *prometheus.Desc) {
	ch <- e.metrics.TotalScrapes.Desc()
	ch <- e.metrics.Error.Desc()
	e.metrics.ScrapeErrors.Describe(ch)
}

// 收集指标
func (e *Exporter) Collect(ch chan<- prometheus.Metric) {
	e.scrape(ch)
	ch <- e.metrics.TotalScrapes
	ch <- e.metrics.Error
	e.metrics.ScrapeErrors.Collect(ch)
}

//判断*exporter是否实现了collector这个接口的所有方法
var _ prometheus.Collector = (*Exporter)(nil)

// 开启线程收集指标
func (e *Exporter) scrape(ch chan<- prometheus.Metric) {
	var (
		wg  sync.WaitGroup
		err error
	)
	defer wg.Wait()
	for _, sc := range e.scrapers {
		wg.Add(1)
		// 使用匿名函数并且并发的收集指标
		go func(sc scraper.Scraper) {
			defer wg.Done()
			label := sc.Name()
			err = sc.Scrape(ch)
			if err != nil {
				log.WithField("scraper", sc.Name()).Error(err)
				e.metrics.ScrapeErrors.WithLabelValues(label).Inc()
				e.metrics.Error.Set(1)
			}
			// 请求次数加1次
			e.metrics.TotalScrapes.Inc()
		}(sc)
	}
}

// 返回一个collector
func NewCollector(metrics Metrics, scrapers []scraper.Scraper) *Exporter {
	return &Exporter{
		metrics:  metrics,
		scrapers: scrapers,
	}
}

// 返回一个Metrics
func NewMetrics() Metrics {
	return Metrics{
		TotalScrapes: prometheus.NewCounter(prometheus.CounterOpts{
			Namespace: global.Namespace,
			Subsystem: global.Subsystem,
			Name:      "scrapes_total",
			Help:      "Total number of times  was scraped for metrics.",
		}),
		ScrapeErrors: prometheus.NewCounterVec(prometheus.CounterOpts{
			Namespace: global.Namespace,
			Subsystem: global.Subsystem,
			Name:      "scrape_errors_total",
			Help:      "Total number of times an error occurred scraping .",
		}, []string{"collector"}),
		Error: prometheus.NewGauge(prometheus.GaugeOpts{
			Namespace: global.Namespace,
			Subsystem: global.Subsystem,
			Name:      "last_scrape_error",
			Help:      "Whether the last scrape of metrics  resulted in an error (1 for error, 0 for success).",
		}),
	}
}

5、handler注册collector

cpu_handle.go

package handle

import (
	"exporter/collector"
	"exporter/scraper"
	"github.com/prometheus/client_golang/prometheus"
	"github.com/prometheus/client_golang/prometheus/promhttp"
	"net/http"
)

// 这里可以添加多台机器
var cpuScrapers = []scraper.Scraper{
	&scraper.CpuScraper{CSName: "cpu_usage_100", CSHelp: "cpu_usage_100_help", Ip: "192.168.164.100", Port: "7547"},
	&scraper.CpuScraper{CSName: "cpu_usage_101", CSHelp: "cpu_usage_101_help", Ip: "192.168.164.101", Port: "7547"},
}

func NewCpuHandle() http.Handler {
	// 创建一个自定义的注册表
	registry := prometheus.NewRegistry()
	registry.MustRegister(collector.NewCollector(collector.NewMetrics(), cpuScrapers))
	return promhttp.HandlerFor(registry, promhttp.HandlerOpts{Registry: registry})
}

memory_handle.go

package handle

import (
	"exporter/collector"
	"exporter/scraper"
	"github.com/prometheus/client_golang/prometheus"
	"github.com/prometheus/client_golang/prometheus/promhttp"
	"net/http"
)

// 这里可以添加多台机器
var memoryScrapers = []scraper.Scraper{
	&scraper.MemoryScraper{MSName: "memory_usage_100", MSHelp: "memory_usage_100_help", Ip: "192.168.164.100", Port: "8547"},
	&scraper.MemoryScraper{MSName: "memory_usage_101", MSHelp: "memory_usage_101_help", Ip: "192.168.164.101", Port: "8547"},
}

func NewMemoryHandle() http.Handler {
	// 创建一个自定义的注册表
	registry := prometheus.NewRegistry()
	registry.MustRegister(collector.NewCollector(collector.NewMetrics(), memoryScrapers))
	return promhttp.HandlerFor(registry, promhttp.HandlerOpts{Registry: registry})
}

6、main

main.go

package main

import (
	"exporter/handle"
	log "github.com/sirupsen/logrus"
	"net/http"
	"os"
)

func main() {
	http.Handle("/metrics/cpu", handle.NewCpuHandle())
	http.Handle("/metrics/memory", handle.NewMemoryHandle())
	log.Infoln("Start server at :9090")
	if err := http.ListenAndServe(":9090", nil); err != nil {
		log.Errorf("Error occur when start server %v", err)
		os.Exit(1)
	}
}

7、启动访问

http://localhost:9090/metrics/cpu

# HELP my_exporter_sub_exporter_cpu_usage_100 cpu_usage_100_help
# TYPE my_exporter_sub_exporter_cpu_usage_100 gauge
my_exporter_sub_exporter_cpu_usage_100{ip="192.168.164.100",port="7547",user1="root1",user2="root2"} 51.52126285020654
# HELP my_exporter_sub_exporter_cpu_usage_101 cpu_usage_101_help
# TYPE my_exporter_sub_exporter_cpu_usage_101 gauge
my_exporter_sub_exporter_cpu_usage_101{ip="192.168.164.101",port="7547",user1="root1",user2="root2"} 30.091186058528706
# HELP my_exporter_sub_exporter_last_scrape_error Whether the last scrape of metrics  resulted in an error (1 for error, 0 for success).
# TYPE my_exporter_sub_exporter_last_scrape_error gauge
my_exporter_sub_exporter_last_scrape_error 0
# HELP my_exporter_sub_exporter_scrapes_total Total number of times  was scraped for metrics.
# TYPE my_exporter_sub_exporter_scrapes_total counter
my_exporter_sub_exporter_scrapes_total 6
# HELP promhttp_metric_handler_errors_total Total number of internal errors encountered by the promhttp metric handler.
# TYPE promhttp_metric_handler_errors_total counter
promhttp_metric_handler_errors_total{cause="encoding"} 0
promhttp_metric_handler_errors_total{cause="gathering"} 0

http://localhost:9090/metrics/memory

# HELP my_exporter_sub_exporter_last_scrape_error Whether the last scrape of metrics  resulted in an error (1 for error, 0 for success).
# TYPE my_exporter_sub_exporter_last_scrape_error gauge
my_exporter_sub_exporter_last_scrape_error 0
# HELP my_exporter_sub_exporter_memory_usage_100 memory_usage_100_help
# TYPE my_exporter_sub_exporter_memory_usage_100 gauge
my_exporter_sub_exporter_memory_usage_100{ip="192.168.164.100",port="8547",user3="root4",user4="root4"} 66.45600532184905
# HELP my_exporter_sub_exporter_memory_usage_101 memory_usage_101_help
# TYPE my_exporter_sub_exporter_memory_usage_101 gauge
my_exporter_sub_exporter_memory_usage_101{ip="192.168.164.101",port="8547",user3="root4",user4="root4"} 43.771418718698015
# HELP my_exporter_sub_exporter_scrapes_total Total number of times  was scraped for metrics.
# TYPE my_exporter_sub_exporter_scrapes_total counter
my_exporter_sub_exporter_scrapes_total 74
# HELP promhttp_metric_handler_errors_total Total number of internal errors encountered by the promhttp metric handler.
# TYPE promhttp_metric_handler_errors_total counter
promhttp_metric_handler_errors_total{cause="encoding"} 0
promhttp_metric_handler_errors_total{cause="gathering"} 0