这篇文章主要介绍了Prometheus开发中间件Exporter过程详解,文中通过示例代码介绍的非常详细，对大家的学习或者工作具有一定的参考学习价值,需要的朋友可以参考下
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)<strong style="color:transparent">来源gao@daima#com搞(%代@#码@网</strong>) //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
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