add simple exporter

main.go

@@ -93,5 +93,5 @@ func main() {
 	reg.MustRegister(workerCA)
 	//当promhttp.Handler()被执行时，所有metric被序列化输出。题外话，其实输出的格式既可以是plain text，也可以是protocol Buffers。
 	http.Handle("/metrics", promhttp.HandlerFor(reg, promhttp.HandlerOpts{}))
-	http.ListenAndServe("9100", nil)
+	http.ListenAndServe(":9100", nil)
 }

main.go.new.txt

@@ -0,0 +1,97 @@
+package main
+
+import (
+	"github.com/prometheus/client_golang/prometheus"
+	"github.com/prometheus/client_golang/prometheus/promhttp"
+	"net/http"
+	"sync"
+)
+
+type ClusterManager struct {
+	sync.Mutex
+	Zone              string
+	metricMapCounters map[string]string
+	metricMapGauges   map[string]string
+}
+
+// Simulate prepare the data
+func (c *ClusterManager) ReallyExpensiveAssessmentOfTheSystemState() (
+	metrics map[string]float64,
+) {
+	metrics = map[string]float64{
+		"oom_crashes_total": 42.00,
+		"ram_usage":         6.023e23,
+	}
+	return
+}
+
+// 通过NewClusterManager方法创建结构体及对应的指标信息，代码如下所示。
+// NewClusterManager creates the two Descs OOMCountDesc and RAMUsageDesc. Note
+// that the zone is set as a ConstLabel. (It's different in each instance of the
+// ClusterManager, but constant over the lifetime of an instance.) Then there is
+// a variable label "host", since we want to partition the collected metrics by
+// host. Since all Descs created in this way are consistent across instances,
+// with a guaranteed distinction by the "zone" label, we can register different
+// ClusterManager instances with the same registry.
+func NewClusterManager(zone string) *ClusterManager {
+	return &ClusterManager{
+		Zone: zone,
+		metricMapGauges: map[string]string{
+			"ram_usage": "ram_usage_bytes",
+		},
+		metricMapCounters: map[string]string{
+			"oom_crashes": "oom_crashes_total",
+		},
+	}
+}
+
+//首先，采集器必须实现prometheus.Collector接口，也必须实现Describe和Collect方法。实现接口的代码如下所示。
+// Describe simply sends the two Descs in the struct to the channel.
+// Prometheus的注册器调用Collect来抓取参数
+// 将收集的数据传递到Channel中并返回
+// 收集的指标信息来自Describe，可以并发地执行抓取工作，但是必须要保证线程的安全
+
+func (c *ClusterManager) Describe(ch chan<- *prometheus.Desc) {
+	//	prometheus.NewDesc(prometheus.BuildFQName(namespace, "", metricName), docString, labels, nil)
+	for _, v := range c.metricMapGauges {
+		ch <- prometheus.NewDesc(prometheus.BuildFQName(c.Zone, "", v), v, nil, nil)
+	}
+
+	for _, v := range c.metricMapCounters {
+		ch <- prometheus.NewDesc(prometheus.BuildFQName(c.Zone, "", v), v, nil, nil)
+	}
+}
+
+// Collect方法是核心，它会抓取你需要的所有数据，根据需求对其进行分析，然后将指标发送回客户端库。
+// 用于传递所有可能指标的定义描述符
+// 可以在程序运行期间添加新的描述，收集新的指标信息
+// 重复的描述符将被忽略。两个不同的Collector不要设置相同的描述符
+func (c *ClusterManager) Collect(ch chan<- prometheus.Metric) {
+	c.Lock()
+	defer c.Unlock()
+	m := c.ReallyExpensiveAssessmentOfTheSystemState()
+	for k, v := range m {
+		t := prometheus.GaugeValue
+		if c.metricMapCounters[k] != "" {
+			t = prometheus.CounterValue
+		}
+		c.registerConstMetric(ch, k, v, t)
+	}
+}
+
+// 用于传递所有可能指标的定义描述符给指标
+func (c *ClusterManager) registerConstMetric(ch chan<- prometheus.Metric, metric string, val float64, valType prometheus.ValueType, labelValues ...string) {
+	descr := prometheus.NewDesc(prometheus.BuildFQName(c.Zone, "", metric), metric, nil, nil)
+	if m, err := prometheus.NewConstMetric(descr, valType, val, labelValues...); err == nil {
+		ch <- m
+	}
+}
+
+func main() {
+	workerCA := NewClusterManager("xiaodian")
+	reg := prometheus.NewPedanticRegistry()
+	reg.MustRegister(workerCA)
+	//当promhttp.Handler()被执行时，所有metric被序列化输出。题外话，其实输出的格式既可以是plain text，也可以是protocol Buffers。
+	http.Handle("/metrics", promhttp.HandlerFor(reg, promhttp.HandlerOpts{}))
+	http.ListenAndServe(":9100", nil)
+}

main.simple.txt

@@ -0,0 +1,47 @@
+package main
+
+//自己动手编写一个Exporter
+//一般来说，绝大多数Exporter都是基于Go语言编写的，一小部分是基于Python语言编写的，还有很小一部分是使用Java语言编写的。比如官方提供的Consul Metrics自定义采集器Exporter，如果是在Go语言的运行环境下，需要按照如下所示代码运行这个Exporter。
+
+import (
+	"log"
+	"net/http"
+
+	"github.com/prometheus/client_golang/prometheus"
+	"github.com/prometheus/client_golang/prometheus/promhttp"
+)
+
+var (
+	cpuTemp = prometheus.NewGauge(prometheus.GaugeOpts{
+		Namespace: "our_idc",
+		Subsystem: "k8s",
+		Name:      "cpu_temperature_celsius",
+		Help:      "Current temperature of the CPU.",
+	})
+	hdFailures = prometheus.NewCounterVec(
+		prometheus.CounterOpts{
+			Namespace: "our_idc",
+			Subsystem: "k8s",
+			Name:      "hd_errors_total",
+			Help:      "Number of hard-disk errors.",
+		},
+		[]string{"device"},
+	)
+)
+
+func init() {
+	// Metrics have to be registered to be exposed:
+	prometheus.MustRegister(cpuTemp)
+	prometheus.MustRegister(hdFailures)
+}
+
+func main() {
+	cpuTemp.Set(65.3)
+	hdFailures.With(prometheus.Labels{"device": "/dev/sda"}).Inc()
+
+	// 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(":9105", nil))
+
+}