Prometheus开发中间件Exporter过程详解

Prometheus 为开发这提供了客户端工具，用于为自己的中间件开发Exporter，对接Prometheus 。

目前支持的客户端

Go
Java
Python
Ruby

以go为例开发自己的Exporter

依赖包的引入

工程结构

[root@node1 data]# tree exporter/
exporter/
├── collector
│ └── node.go
├── go.mod
└── main.go

引入依赖包

require (
  github.com/modern-go/concurrent v0.0.0-20180306012644-bacd9c7ef1dd // indirect
  github.com/modern-go/reflect2 v1.0.1 // indirect
  github.com/prometheus/client_golang v1.1.0
    //借助gopsutil 采集主机指标
  github.com/shirou/gopsutil v0.0.0-20190731134726-d80c43f9c984
)

main.go

package main

import (
  \"cloud.io/exporter/collector\"
  \"fmt\"
  \"github.com/prometheus/client_golang/prometheus\"
  \"github.com/prometheus/client_golang/prometheus/promhttp\"
  \"net/http\"
)

func init() {
   //注册自身采集器
  prometheus.MustRegister(collector.NewNodeCollector())
}
func main() {
  http.Handle(\"/metrics\", promhttp.Handler())
  if err := http.ListenAndServe(\":8080\", nil); err != nil {
    fmt.Printf(\"Error occur when start server %v\", err)
  }
}

为了能看清结果我将默认采集器注释,位置registry.go

func init() {
  //MustRegister(NewProcessCollector(ProcessCollectorOpts{}))
  //MustRegister(NewGoCollector())
}

/collector/node.go

代码中涵盖了Counter、Gauge、Histogram、Summary四种情况，一起混合使用的情况，具体的说明见一下代码中。

package collector

import (
  \"github.com/prometheus/client_golang/prometheus\"
  \"github.com/shirou/gopsutil/host\"
  \"github.com/shirou/gopsutil/mem\"
  \"runtime\"
  \"sync\"
)

var reqCount int32
var hostname string
type NodeCollector struct {
  requestDesc  *prometheus.Desc  //Counter
  nodeMetrics   nodeStatsMetrics //混合方式 
  goroutinesDesc *prometheus.Desc  //Gauge
  threadsDesc  *prometheus.Desc //Gauge
  summaryDesc  *prometheus.Desc //summary
  histogramDesc *prometheus.Desc  //histogram
  mutex     sync.Mutex
}
//混合方式数据结构
type nodeStatsMetrics []struct {
  desc  *prometheus.Desc
  eval  func(*mem.VirtualMemoryStat) float64
  valType prometheus.ValueType
}

//初始化采集器
func NewNodeCollector() prometheus.Collector {
  host,_:= host.Info()
  hostname = host.Hostname
  return &NodeCollector{
    requestDesc: prometheus.NewDesc(
      \"total_request_count\",
      \"请求数\",
      []string{\"DYNAMIC_HOST_NAME\"}, //动态标签名称
      prometheus.Labels{\"STATIC_LABEL1\":\"静态值可以放在这里\",\"HOST_NAME\":hostname}),
    nodeMetrics: nodeStatsMetrics{
      {
        desc: prometheus.NewDesc(
          \"total_mem\",
          \"内存总量\",
          nil, nil),
        valType: prometheus.GaugeValue,
        eval: func(ms *mem.VirtualMemoryStat) float64 { return float64(ms.Total) / 1e9 },
      },
      {
        desc: prometheus.NewDesc(
          \"free_mem\",
          \"内存空闲\",
          nil, nil),
        valType: prometheus.GaugeValue,
        eval: func(ms *mem.VirtualMemoryStat) float64 { return float64(ms.Free) / 1e9 },
      },

    },
    goroutinesDesc:prometheus.NewDesc(
      \"goroutines_num\",
      \"协程数.\",
      nil, nil),
    threadsDesc: prometheus.NewDesc(
      \"threads_num\",
      \"线程数\",
      nil, nil),
    summaryDesc: prometheus.NewDesc(
      \"summary_http_request_duration_seconds\",
      \"summary类型\",
      []string{\"code\", \"method\"},
      prometheus.Labels{\"owner\": \"example\"},
    ),
    histogramDesc: prometheus.NewDesc(
      \"histogram_http_request_duration_seconds\",
      \"histogram类型\",
      []string{\"code\", \"method\"},
      prometheus.Labels{\"owner\": \"example\"},
    ),
  }
}

// Describe returns all descriptions of the collector.
//实现采集器Describe接口
func (n *NodeCollector) Describe(ch chan<- *prometheus.Desc) {
  ch <- n.requestDesc
  for _, metric := range n.nodeMetrics {
    ch <- metric.desc
  }
  ch <- n.goroutinesDesc
  ch <- n.threadsDesc
  ch <- n.summaryDesc
  ch <- n.histogramDesc
}
// Collect returns the current state of all metrics of the collector.
//实现采集器Collect接口,真正采集动作
func (n *NodeCollector) Collect(ch chan<- prometheus.Metric) {
  n.mutex.Lock()
  ch <- prometheus.MustNewConstMetric(n.requestDesc,prometheus.CounterValue,0,hostname)
  vm, _ := mem.VirtualMemory()
  for _, metric := range n.nodeMetrics {
    ch <- prometheus.MustNewConstMetric(metric.desc, metric.valType, metric.eval(vm))
  }

  ch <- prometheus.MustNewConstMetric(n.goroutinesDesc, prometheus.GaugeValue, float64(runtime.NumGoroutine()))

  num, _ := runtime.ThreadCreateProfile(nil)
  ch <- prometheus.MustNewConstMetric(n.threadsDesc, prometheus.GaugeValue, float64(num))

  //模拟数据
  ch <- prometheus.MustNewConstSummary(
    n.summaryDesc,
    4711, 403.34,
    map[float64]float64{0.5: 42.3, 0.9: 323.3},
    \"200\", \"get\",
  )

  //模拟数据
  ch <- prometheus.MustNewConstHistogram(
      n.histogramDesc,
      4711, 403.34,
      map[float64]uint64{25: 121, 50: 2403, 100: 3221, 200: 4233},
      \"200\", \"get\",
    )
  n.mutex.Unlock()
}

执行的结果http://127.0.0.1:8080/metrics

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持。