0x00 前言
Prometheus 主要用于应用服务的监控,尤其是基于 Docker/Kubernetes 部署的应用服务,这里的监控是服务层面的(细粒度),以 Golang 开发的服务为例,如 runtime
信息,接口延迟,某个操作的延迟及接口调用成功率等等,只要是能够收集的信息,都可以作为 Prometheus 的监控指标。
0x01 应用接入
Prometheus 的应用接入其实并不复杂,通常按照如下几个步骤来完成:
- 实现定好需要采集哪些指标,如成功率,延迟,分布数据等
- 将指标转换为 Prometheus 的 Metrics 类型
- 在代码逻辑中加入 Metrics 的 “打点” 调用
- 启动 PrometheusHttp 服务,暴露自己的采集的指标
以上几步即可完成在项目应用中将指标暴露给 Prometheus。
0x02 Exporter 简介
Exporter 是一个采集监控数据并通过 Prometheus 监控规范对外提供数据的组件,它负责从目标处(Your 服务)搜集数据,并将其转化为 Prometheus 支持的格式。Prometheus 会周期性地调用 Exporter 提供的 metrics 数据接口来获取数据。那么使用 Exporter 的好处是什么?
举例来说,如果要监控 Mysql/Redis 等数据库,我们必须要调用它们的接口来获取信息(前提要有),这样每家都有一套接口,这样非常不通用。所以 Prometheus 做法是每个软件做一个 Exporter,Prometheus 的 Http 读取 Exporter 的信息(将监控指标进行统一的格式化并暴露出来)。简单类比,Exporter 就是个翻译,把各种语言翻译成一种统一的语言。
0x03 Build Your Own Exportor
官方文档 WRITING EXPORTERS 介绍了编写 Exportor 的一些注意点。Prometheus 的 client 库提供了实现自定义 Exportor 的 接口,Collector 接口定义了两个方法 Describe
和 Collect
,实现这两个方法就可以暴露自定义的数据:
Describe 接口
实现 Describe
接口,传递指标描述符到 channel
// Describe simply sends the two Descs in the struct to the channel.
func (c *ClusterManager) Describe(ch chan<- *prometheus.Desc) {
ch <- c.OOMCountDesc
ch <- c.RAMUsageDesc
}
Collect 接口
Collect 函数将执行抓取函数并返回数据,返回的数据传递到 channel 中,并且传递的同时绑定原先的指标描述符。实现指标采集的工作需要在这里完成(针对开发者)
type Collector interface {
// Describe sends the super-set of all possible descriptors of metrics
// collected by this Collector to the provided channel and returns once
// the last descriptor has been sent. The sent descriptors fulfill the
// consistency and uniqueness requirements described in the Desc
// documentation.
//
// It is valid if one and the same Collector sends duplicate
// descriptors. Those duplicates are simply ignored. However, two
// different Collectors must not send duplicate descriptors.
//
// Sending no descriptor at all marks the Collector as “unchecked”,
// i.e. no checks will be performed at registration time, and the
// Collector may yield any Metric it sees fit in its Collect method.
//
// This method idempotently sends the same descriptors throughout the
// lifetime of the Collector. It may be called concurrently and
// therefore must be implemented in a concurrency safe way.
//
// If a Collector encounters an error while executing this method, it
// must send an invalid descriptor (created with NewInvalidDesc) to
// signal the error to the registry.
Describe(chan<- *Desc)
// Collect is called by the Prometheus registry when collecting
// metrics. The implementation sends each collected metric via the
// provided channel and returns once the last metric has been sent. The
// descriptor of each sent metric is one of those returned by Describe
// (unless the Collector is unchecked, see above). Returned metrics that
// share the same descriptor must differ in their variable label
// values.
//
// This method may be called concurrently and must therefore be
// implemented in a concurrency safe way. Blocking occurs at the expense
// of total performance of rendering all registered metrics. Ideally,
// Collector implementations support concurrent readers.
Collect(chan<- Metric)
}
暴露 Exportor 及 Promhttp 启动
使用下面的代码将自定义的 Metrics 暴露出去,这也是 promhttp 的通用做法了:
import (
"log"
"net/http"
"github.com/prometheus/client_golang/prometheus/promhttp"
)
func main() {
http.Handle("/metrics", promhttp.Handler())
log.Fatal(http.ListenAndServe(":8080", nil))
}
0x04 一个完整的例子
本小节给出一个完整的 Exportor 例子,结构和接口的使用方法可以参考 GODOC。 需要引入的 package:
import (
"net/http"
"github.com/prometheus/client_golang/prometheus/promhttp"
"github.com/prometheus/common/log"
"github.com/prometheus/client_golang/prometheus"
)
封装了 fooCollector
,采集两个指标 fooMetric
和 barMetric
:
type fooCollector struct {
fooMetric *prometheus.Desc
barMetric *prometheus.Desc
}
初始化 newFooCollector
,注意 prometheus.NewDesc
的参数,推荐还是传入 help
及 label
信息:
func newFooCollector() *fooCollector {
m1 := make(map[string]string)
m1["env"] = "prod"
v := []string{"hostname"}
return &fooCollector{
fooMetric: prometheus.NewDesc("fff_metrics","Show metrics a for mysql",nil,nil),
barMetric:prometheus.NewDesc("bbb_metrics","Show metrics a bar occu",v,m1),
}
}
实现 Describe
及 Collect
方法:
func (collect *fooCollector) Describe(ch chan <- *prometheus.Desc) {
ch <- collect.barMetric
ch <- collect.fooMetric
}
func (collect *fooCollector) Collect(ch chan<- prometheus.Metric) {
var metricValue float64
if 1 == 1 {
metricValue = 1
}
ch <- prometheus.MustNewConstMetric(collect.fooMetric,prometheus.GaugeValue, metricValue)
ch <- prometheus.MustNewConstMetric(collect.barMetric,prometheus.CounterValue, metricValue,"kk")
}
最后一个步骤,注册 fooCollector
及启动 promhttp
服务,以上几步就实现了一个简单的 Exportor
func main() {
foo := newFooCollector()
prometheus.MustRegister(foo)
log.Info("beging to server on Port: 18080")
http.Handle("/metrics",promhttp.Handler())
log.Fatal(http.ListenAndServe(":18080",nil))
}
0x05 抽象 Exportor 的实现步骤
1、定义指标及初始化方法
定义指标就是创建指标的描述符,通常把要采集的指标描述符放在一个结构体里,如下我们定义了一个指标 fooCollector
,其中包含了两种类型的数据 fooMetric
和 barMetric
:
//Define a struct for you collector that contains pointers
//to prometheus descriptors for each metric you wish to expose.
//Note you can also include fields of other types if they provide utility
//but we just won't be exposing them as metrics.
type fooCollector struct {
fooMetric *prometheus.Desc
barMetric *prometheus.Desc
}
初始化方法 newFooCollector
用于初始化 fooCollector
,包含对每个成员 prometheus.Desc
类型的初始化,prometheus.NewDesc
方法创建一个 prometheus.Desc
对象:
//You must create a constructor for you collector that
//initializes every descriptor and returns a pointer to the collector
// 调用工厂方法即可创建一个结构体的实例
func newFooCollector() *fooCollector {
return &fooCollector{
fooMetric: prometheus.NewDesc("foo_metric",
"Shows whether a foo has occurred in our cluster",
nil, nil,
),
barMetric: prometheus.NewDesc("bar_metric",
"Shows whether a bar has occurred in our cluster",
nil, nil,
),
}
}
2、实现数据采集(核心) 数据采集需要实现 Collector 的两个接口:
Describe
:告诉prometheus
我们定义了哪些prometheus.Desc
结构,通过channel
传递给上层Collect
:真正实现数据采集的功能,将采集数据结果通过 channel 传递给上层
注意:Collect
中完成的就是每个指标的采集,必须保证这里的数据是动态更新的,每一次调用 curl http://127.0.0.1:8080/metrics
都会触发对 Collect
方法的调用
//Each and every collector must implement the Describe function.
//It essentially writes all descriptors to the prometheus desc channel.
func (collector *fooCollector) Describe(ch chan<- *prometheus.Desc) {
//Update this section with the each metric you create for a given collector
ch <- collector.fooMetric
ch <- collector.barMetric
}
//Collect implements required collect function for all promehteus collectors
func (collector *fooCollector) Collect(ch chan<- prometheus.Metric) {
//Implement logic here to determine proper metric value to return to prometheus
//for each descriptor or call other functions that do so.
var metricValue float64
if 1 == 1 {
metricValue = 1
}
//Write latest value for each metric in the prometheus metric channel.
//Note that you can pass CounterValue, GaugeValue, or UntypedValue types here.
ch <- prometheus.MustNewConstMetric(collector.fooMetric, prometheus.CounterValue, metricValue)
ch <- prometheus.MustNewConstMetric(collector.barMetric, prometheus.CounterValue, metricValue)
}
3、注册指标及启动 promHTTP
服务
这里在主函数中注册上面自定义的指标,注册成功之后,启动 HTTP 服务器,这样就完成了自定义的 Exportor 服务。
func main() {
//Create a new instance of the foocollector and
//register it with the prometheus client.
foo := newFooCollector()
prometheus.MustRegister(foo)
//This section will start the HTTP server and expose
//any metrics on the /metrics endpoint.
http.Handle("/metrics", promhttp.Handler())
log.Info("Beginning to serve on port :8080")
log.Fatal(http.ListenAndServe(":8080", nil))
}
0x06 总结
本篇文章分析了 Prometheus 在应用中的接入方法及实现的步骤。