通过在应用中埋点来暴露应用数据，使用Prometheus Client监控抓取数据，即可实现利用Prometheus监控应用的目的。本文以阿里云容器服务Kubernetes集群和阿里云容器镜像服务为例，介绍如何通过Prometheus Client监控应用。
前提条件
- 已创建Kubernetes集群。具体操作，请参见创建Kubernetes托管版集群。
- 已接入阿里云Prometheus监控。具体操作，请参见开启阿里云Prometheus监控。
- 已创建阿里云容器镜像服务镜像仓库。具体操作，请参见创建镜像仓库。
步骤一：对应用埋点
Prometheus Client目前支持大部分编程语言，更多信息，请参见CLIENT LIBRARIES。以下示例通过对应用埋点以暴露Go应用的监控数据：
package main
import (
"flag"
"fmt"
"log"
"math"
"math/rand"
"net/http"
"time"
"github.com/prometheus/client_golang/prometheus"
"github.com/prometheus/client_golang/prometheus/promhttp"
)
var (
addr = flag.String("listen-address", ":8080", "The address to listen on for HTTP requests.")
uniformDomain = flag.Float64("uniform.domain", 0.0002, "The domain for the uniform distribution.")
normDomain = flag.Float64("normal.domain", 0.0002, "The domain for the normal distribution.")
normMean = flag.Float64("normal.mean", 0.00001, "The mean for the normal distribution.")
oscillationPeriod = flag.Duration("oscillation-period", 10*time.Minute, "The duration of the rate oscillation period.")
)
var (
// Create a summary to track fictional interservice RPC latencies for three distinct services with different latency distributions.
// These services are differentiated via a "service" label.
rpcDurations = prometheus.NewSummaryVec(
prometheus.SummaryOpts{
Name: "rpc_durations_seconds",
Help: "RPC latency distributions.",
Objectives: map[float64]float64{0.5: 0.05, 0.9: 0.01, 0.99: 0.001},
},
[]string{"service"},
)
// The same as above, but now as a histogram, and only for the normal
// distribution. The buckets are targeted to the parameters of the
// normal distribution, with 20 buckets centered on the mean, each
// half-sigma wide.
rpcDurationsHistogram = prometheus.NewHistogram(prometheus.HistogramOpts{
Name: "rpc_durations_histogram_seconds",
Help: "RPC latency distributions.",
Buckets: prometheus.LinearBuckets(*normMean-5**normDomain, .5**normDomain, 20),
})
)
func init() {
// Register the summary and the histogram with Prometheus's default registry.
prometheus.MustRegister(rpcDurations)
prometheus.MustRegister(rpcDurationsHistogram)
// Add Go module build info.
prometheus.MustRegister(prometheus.NewBuildInfoCollector())
}
func main() {
flag.Parse()
start := time.Now()
oscillationFactor := func() float64 {
return 2 + math.Sin(math.Sin(2*math.Pi*float64(time.Since(start))/float64(*oscillationPeriod)))
}
// Periodically record some sample latencies for the three services.
go func() {
for {
v := rand.Float64() * *uniformDomain
rpcDurations.WithLabelValues("uniform").Observe(v)
time.Sleep(time.Duration(100*oscillationFactor()) * time.Millisecond)
}
}()
go func() {
for {
v := (rand.NormFloat64() * *normDomain) + *normMean
rpcDurations.WithLabelValues("normal").Observe(v)
// Demonstrate exemplar support with a dummy ID. This
// would be something like a trace ID in a real
// application. Note the necessary type assertion. We
// already know that rpcDurationsHistogram implements
// the ExemplarObserver interface and thus don't need to
// check the outcome of the type assertion.
rpcDurationsHistogram.(prometheus.ExemplarObserver).ObserveWithExemplar(
v, prometheus.Labels{"dummyID": fmt.Sprint(rand.Intn(100000))},
)
time.Sleep(time.Duration(75*oscillationFactor()) * time.Millisecond)
}
}()
go func() {
for {
v := rand.ExpFloat64() / 1e6
rpcDurations.WithLabelValues("exponential").Observe(v)
time.Sleep(time.Duration(50*oscillationFactor()) * time.Millisecond)
}
}()
// Expose the registered metrics via HTTP.
http.Handle("/metrics", promhttp.HandlerFor(
prometheus.DefaultGatherer,
promhttp.HandlerOpts{
// Opt into OpenMetrics to support exemplars.
EnableOpenMetrics: true,
},
))
log.Fatal(http.ListenAndServe(*addr, nil))
}在本示例中，相关参数说明如下：
- 在注册rpc_durations_seconds指标前需要注册一个监控指标prometheus.MustRegister。本示例中rpc_durations_seconds为prometheus.NewSummaryVec类型，更多其他类型，请参见Prometheus。
- rpcDurations是一个全局的单例，在更新监控数据时通过调用rpcDurations.WithLabelValues("uniform").Observe(v)增加监控数据。
步骤二：将应用制作为镜像并上传到镜像仓库
将完成埋点的应用制作成镜像并上传至阿里云容器镜像服务的镜像仓库。
步骤三：将应用部署至容器服务Kubernetes集群
步骤四：配置服务发现
配置阿里云Prometheus监控的服务发现以抓取Go应用数据。本示例以ARMS控制台操作为例：
步骤五：验证Prometheus Client是否支持通过指标监控应用数据
- 在文本框输入步骤一：对应用埋点注册的指标rpc_durations_seconds，单击
。若查询到指标rpc_durations_seconds，表示Prometheus Client已通过该指标监控应用数据。