Prometheus笔记（二）监控go项目实时给grafana展现
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Prometheus笔记（二）监控go项目实时给grafana展现
Prometheus笔记（一）metric typegithub
文章目录
1、prometheus和grafana安装
一、promethues安装
先写好配置文件，保存为prometheus.yml，golang
global: scrape_interval: 15s # By default, scrape targets every 15 seconds. # Attach these labels to any time series or alerts when communicating with # external systems (federation, remote storage, Alertmanager). external_labels: monitor: 'codelab-monitor' # 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' //服务的名称，后续要监控咱们本身的服务时只须要按照这个格式再添加上 # Override the global default and scrape targets from this job every 5 seconds. scrape_interval: 5s static_configs: - targets: ['localhost:9090'] //这个为服务的ip和port
更多配置文件写法请参考：https://prometheus.io/docs/operating/configuration/web
官方给出供参考的配置文件：https://github.com/prometheus/prometheus/blob/release-2.3/config/testdata/conf.good.ymldocker
而后利用docker启动。shell
docker run -p 9090:9090 --network=host -v /root/prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheusjson
启动以后，能够先测试一下是否能够用。api
[root@localhost ~]# curl http://localhost:9090/api/v1/label/job/values { "status":"success", "data":["prometheus"] }
若是是用上面我给出来的默认配置，返回值应该是和这里给出来的同样。说明promethues服务端启动好了。浏览器
二、grafana安装
这篇文章只是演示基本用法，因此用到的grafana的配置都是默认的。直接使用下面的命令启动就能够了。curl
$ docker run -d -p 3000:3000 grafana/grafana
若是须要更多功能则须要更复杂的配置了，更多配置方法请参考：http://docs.grafana.org/installation/docker/
docker镜像起来后，用浏览器登入 127.0.0.0:3000 ，会弹出来登入界面，用户名和密码为admin/admin，第一次会提示修改密码，按照提示操做便可。这样就完成了安装。
2、获取监控数据
这一步我主要写一个简单的go项目，用来获取内存的实时使用率数据，而后在grafana展现。
代码下载地址：https://github.com/Zhanben/goproject/tree/master/gomemory
package main import ( "net/http" "log" "time" "os" "github.com/prometheus/client_golang/prometheus/promhttp" "github.com/prometheus/client_golang/prometheus" "github.com/shirou/gopsutil/mem" ) func main (){ //初始化日志服务 logger := log.New(os.Stdout, "[Memory]", log.Lshortfile | log.Ldate | log.Ltime) //初始一个http handler http.Handle("/metrics", promhttp.Handler()) //初始化一个容器 diskPercent := prometheus.NewGaugeVec(prometheus.GaugeOpts{ Name: "memeory_percent", Help: "memeory use percent", }, []string {"percent"}, ) prometheus.MustRegister(diskPercent) // 启动web服务，监听1010端口 go func() { logger.Println("ListenAndServe at:localhost:1010") err := http.ListenAndServe("localhost:1010", nil) if err != nil { logger.Fatal("ListenAndServe: ", err) } }() //收集内存使用的百分比 for { logger.Println("start collect memory used percent!") v, err := mem.VirtualMemory() if err != nil { logger.Println("get memeory use percent error:%s", err) } usedPercent := v.UsedPercent logger.Println("get memeory use percent:", usedPercent) diskPercent.WithLabelValues("usedMemory").Set(usedPercent) time.Sleep(time.Second*2) } }
程序跑起来的输出以下：
[root@localhost demoproject]# go run memory.go [Memory]2018/07/14 11:43:12 memory.go:42: start collect memory used percent! [Memory]2018/07/14 11:43:12 memory.go:48: get memeory use percent: 41.22097449562238 [Memory]2018/07/14 11:43:12 memory.go:33: ListenAndServe at:locahost:1010 [Memory]2018/07/14 11:43:14 memory.go:42: start collect memory used percent! [Memory]2018/07/14 11:43:14 memory.go:48: get memeory use percent: 41.219733205342514 [Memory]2018/07/14 11:43:16 memory.go:42: start collect memory used percent! [Memory]2018/07/14 11:43:16 memory.go:48: get memeory use percent: 41.219733205342514 ^Csignal: interrupt
此时能够查询的到promethues监控到的数据。
[root@localhost ~]# curl http://localhost:1010/metrics ... # HELP go_memstats_sys_bytes Number of bytes obtained by system. Sum of all system allocations. # TYPE go_memstats_sys_bytes gauge go_memstats_sys_bytes 3.346432e+06 //这个为代码添加的字段，其他为promethues默认监控字段 # HELP memeory_percent memeory use percent # TYPE memeory_percent gauge memeory_percent{percent="usedMemory"} 41.16718525016137 # HELP process_cpu_seconds_total Total user and system CPU time spent in seconds. # TYPE process_cpu_seconds_total counter process_cpu_seconds_total 0.01 ....
3、配置grafana展现数据
一、修改配置重启promethues和grafana
先将监控服务注册到promethues服务端，修改配置文件：promethues.yml
... //和前面的配置文件同样 scrape_configs: # The job name is added as a label `job=<job_name>` to any timeseries scraped from this config. - job_name: 'memory' //给你的服务取的名字 # Override the global default and scrape targets from this job every 5 seconds. scrape_interval: 5s static_configs: - targets: ['localhost:1010'] //改为你本身代码里面使用的端口号
暂停掉以前启动的promethues和grafana
[root@localhost ~]# docker ps CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES 650cb5891e56 grafana/grafana "/run.sh" 19 hours ago Up 19 hours 0.0.0.0:3000->3000/tcp brave_ride 850a44d18dfe prom/prometheus "/bin/prometheus -..." 21 hours ago Up 21 hours 0.0.0.0:9090->9090/tcp zen_keller [root@localhost ~]# docker stop 850a44d18dfe 850a44d18dfe [root@localhost ~]# docker stop 650cb5891e56 650cb5891e56
修改好配置文件以后从新启动promethues和grafana
[root@localhost ~]# docker run -d -p 9090:9090 --network=host -v /root/prometheus.yml:/etc/prometheus/prometheus.yml prom/prometheus [root@localhost ~]# docker run -d -p 3000:3000 grafana/grafana
检验promethues服务端是否注册到了咱们本身的服务。
[root@localhost demoproject]# curl http://localhost:9090/api/v1/targets { "status": "success", "data": { "activeTargets": [{ "discoveredLabels": { "__address__": "localhost:1010", "__metrics_path__": "/metrics", "__scheme__": "http", "job": "memory" }, "labels": { "instance": "localhost:1010", "job": "memory" //这个memory即咱们在promethues的配置文件填写的名字 }, "scrapeUrl": "http://localhost:1010/metrics", "lastError": "", "lastScrape": "2018-07-14T07:39:26.127284982Z", "health": "up" //注意上面这个字段要为up,要否则后续grafana查询不到数据 } ], "droppedTargets": [] } }
二、建立数据源
- 打开grafana界面,登入后以下图所示:
- 建立数据源
按照图片里面的填写的填好。其中memory为数据源名字，能够本身随便取一个。类型须要选择promethues。下面的URL须要填写promethues的服务端的URL，access选择不使用代理的Browser。填好以后点击下面的保存，完成建立数据源。
三、建立dashboard
第一步如图所示，按照图中的三步操做。
操做完成以后会进入下图所示的界面，而后再次按照图中提示操做便可。
完成以后会弹出来一个panle，单击下拉框，点击Edit。
点击Edit以后会pane下方会获得下图展现的界面：
在查询字段的地方填入，代码缩写的字段prometheus.NewGaugeVec建立时填写的name字段，本示例代码为memory_percent。填好以后点击下option旁边的query inspector，就能够在上面的表中查看到数据了。
最后查询到的数据以下图所示：
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参考资料
一、 https://godoc.org/github.com/prometheus/client_golang/prometheus
二、 https://prometheus.io/docs/introduction/overview/