[33] Deploy Prometheus + Grafana monitoring platform with Docker

1. Docker deploys Prometheus

1.1 Download prom/prometheus image

docker pull prom/prometheus

1.2 Start the prometheus container

docker run -itd --name=prometheus -p 9090:9090 prom/prometheus

Open the local http://localhost:9090/  to indicate that the startup is successful

1.3 Copy the configuration file of the container

docker cp prometheus:/etc/prometheus/prometheus.yml /Users/chenpeng/share/prometheus/config

1.4 Delete the old container and rebuild the container with the configuration file mounted

docker rm prometheus
docker run -itd --name=prometheus -v /Users/chenpeng/share/prometheus/config/prometheus.yml:/etc/prometheus/prometheus.yml -p 9090:9090 prom/prometheus

2. Docker deploys Grafana

2.1 Download grafana/grafana image

docker pull grafana/grafana

2.2 Start the grafana container

docker run -itd --name=grafana -p 3000:3000 grafana/grafana

Open the webpage localhost:3000, the initial user password is admin, and the first login changes the password to 123456 

3. Example of adding monitoring to go code

3.1 Get the prometheus library

go get -u github.com/prometheus/client_golang/prometheus

3.2 go sample code

package main

import (
	"fmt"
	"github.com/gin-gonic/gin"
	"github.com/prometheus/client_golang/prometheus"
	"github.com/prometheus/client_golang/prometheus/promhttp"
	"math/rand"
	"net/http"
	"strconv"
	"time"
)

var (
	// 随机数
	ran = rand.New(rand.NewSource(time.Now().UnixMilli()))
	// 请求处理时间指标
	httpRequestDurationVec *prometheus.HistogramVec
	// 请求个数指标
	httpRequestCountVec *prometheus.CounterVec
	// DefaultBuckets prometheus buckets in seconds.
	DefaultBuckets = []float64{0.1, 0.3, 0.5, 1.0, 3.0, 5.0}
)

func main() {
	router := gin.Default()
	router.Use(Middleware)

	router.GET("/metrics", Metrics())

	apiGroup := router.Group("/api")
	{
		apiGroup.GET("/A", CommonControl)
		apiGroup.GET("/B", CommonControl)
		apiGroup.GET("/C", CommonControl)
		apiGroup.GET("/D", CommonControl)
		apiGroup.GET("/E", CommonControl)
	}

	_ = router.Run(":60000")
}

// 初始化prometheus
func init() {
	httpRequestDurationVec = prometheus.NewHistogramVec(prometheus.HistogramOpts{
		Name:    "http_server_requests_seconds",
		Help:    "How long it took to process the HTTP request, partitioned by status code, method and HTTP path.",
		Buckets: DefaultBuckets,
	}, []string{"code", "method", "uri"})

	httpRequestCountVec = prometheus.NewCounterVec(prometheus.CounterOpts{
		Name: "http_server_requests_count",
		Help: "How long it took to process the HTTP request, partitioned by status code, method and HTTP path.",
	}, []string{"code", "method"})

	prometheus.MustRegister(httpRequestDurationVec, httpRequestCountVec)
}

// 统一处理函数
func CommonControl(ctx *gin.Context) {
	time.Sleep(time.Duration(ran.Intn(100)) * time.Millisecond)

	ctx.JSON(http.StatusOK, gin.H{
		"message": "success",
	})
}

// 中间件记录请求指标
func Middleware(ctx *gin.Context) {
	start := time.Now()
	ctx.Next()

	// 返回状态码
	statusCode := strconv.Itoa(ctx.Writer.Status())
	// 标签
	labels := []string{statusCode, ctx.Request.Method, ctx.Request.URL.Path}
	// 请求处理时间
	duration := float64(time.Since(start).Nanoseconds()) / 1000000000
	
	// 添加指标
	httpRequestDurationVec.WithLabelValues(labels...).Observe(duration)
	httpRequestCountVec.WithLabelValues(statusCode, ctx.Request.Method).Inc()
	fmt.Printf("code: %d | method: %s | path: %s | duration: %f\n ", statusCode, ctx.Request.Method, ctx.Request.URL.Path, duration)
}

// http metrics 指标页面，配置给prometheus
func Metrics() gin.HandlerFunc {
	h := promhttp.Handler()

	return func(c *gin.Context) {
		h.ServeHTTP(c.Writer, c.Request)
	}
}

3.3 Visit the metrics page

http://localhost:60000/metrics

3.4 Modify the prometheus configuration file

Modify the configuration file just mounted by docker. My path here is /Users/chenpeng/share/prometheus/config/prometheus.yml

# A scrape configuration containing exactly one endpoint to scrape:
# Here it's Prometheus itself.
scrape_configs:
  # The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.
  - job_name: "prometheus"

    # metrics_path defaults to '/metrics'
    # scheme defaults to 'http'.

    static_configs:
      - targets: ["localhost:9090"]

  - job_name: "gopractice"

    static_configs:
      - targets: ["192.168.50.43:60000"] #这里要填本地ip，容器里localhost访问不到

Restart the prometheus docker container

docker restart prometheus

Visit  http://localhost:9090/targets?search=

 You can see that prometheus has included the metrics of the project

3.5 configure grafana

Enter grafana and select datasource

 Enter DATA SOURCES and select prometheus

Configure the prometheus address, also use the local intranet ip address, click save&test

 

Add a chart and set the corresponding function

 

 

4. Write docker-compose.yml to start

4.1 docker-compose.yml file

version: '3.5'
services:
  prometheus:
    image: prom/prometheus:latest
    container_name: prometheus-compose
    restart: no
    ports:
      - "9090:9090"
    volumes:
      - "/Users/chenpeng/software/dockercompose/prometheus/config/prometheus.yml:/etc/prometheus/prometheus.yml"
  grafana:
    image: grafana/grafana:latest
    container_name: grafana-compose
    restart: no
    ports:
      - "3000:3000"

4.2 Start docker-compose

docker-compose up -d