【监控指标】监控系统-prometheus、grafana。容器化部署。go语言 gin框架、gRPC框架的集成

文章目录

一、监控有哪些指标
二、prometheus、grafana架构
- Prometheus 组件
- Grafana 组件
- 架构优点
三、安装prometheus和node-exporter
- 1. docker pull镜像
- 2. 启动node-exporter
- 3. 启动prometheus
四、promql基本语法
五、grafana的安装和使用
- 1. 新建空文件夹grafana-storage，用来存储数据
- 2. 启动grafana(如果和已有的端口冲突改一下端口)
- 3. 配置prometheus并使用
六、导入Grafana模板
七、guages、counter、histograms指标
- guages
- Counter
- Histograms
八、go语言集成prometheus
九、grpc框架集成prometheus
十、gin框架集成prometheus

一、监控有哪些指标

监控1. 业务监控(上层概念 - 领导层)：需求方：老板、运营开发方： 大数据库 ，都会访问业务库，大数据库会从同步库， 宽表QPS、DAU日活、访问状态(http code)、业务接口(登录、注册、聊天、上传、留言、搜索、投诉)、 产品转换率、充值额度2. 系统监控需求方： 运维开发方： 运维操作系统相关： cpu使用率、内存使用、磁盘使用率、磁盘空间（非常常见）、TCP(上W的链接)，流量组件： mysql、redis、kafka3. 日志监控需求方：运维、开发开发方：开发两种日志：业务日志（大数据， 普通日志）、 系统日志（操作系统日志、mysql组件日志、kakfa的日志）监控中的重头戏，一般我们都会对单独针对日志设计日志管理系统， ELK日志系统， loki4. 网络监控：需求方：机房管理开放方：服务器管理IDC 交换机、路由器、防火墙、负载均衡、服务器、机柜、电源、UPS、空调、网络设备、机房环境监控，网络：内部网络（物理内网，虚拟内网（VPN））监控5. 程序监控：需求方：开发开发方：开发比如产生了 500 ErrUserNotFound一般要运维和开发人员配合，开发人员在程序中提供监控接口，运维人员通过接口获取监控数据prometheus的数据格式： metricsmetrics是一种对采样数据的总称

二、prometheus、grafana架构

官网：https://prometheus.fuckcloudnative.io/di-yi-zhang-jie-shao/overview

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Prometheus 组件

Prometheus server：Prometheus 的核心组件，负责收集、存储和查询时间序列数据。
Exporters：Exporters 是 Prometheus 用来从目标系统收集数据的插件。Exporters 可以是主动拉取数据的，也可以是被动推送数据的。
Pushgateway：Pushgateway 是一个被动推送数据的 Exporter，用于收集短暂运行的任务或服务的数据。
Alertmanager：Alertmanager 负责处理 Prometheus 发出的告警，并将告警发送到指定的通知系统。
Prometheus web UI：Prometheus 自带的 Web 界面，用于查看 Prometheus 收集的数据。

Grafana 组件

Grafana：一个开源的图形化数据可视化工具，用于将 Prometheus 的数据进行可视化展示。
架构说明

Prometheus通过 Exporters 从目标系统收集数据，并将数据存储到 Prometheus server。Prometheus server 还可以通过 Pushgateway 收集短暂运行的任务或服务的数据。Alertmanager 负责处理 Prometheus 发出的告警，并将告警发送到指定的通知系统。Prometheus web UI 用于查看 Prometheus 收集的数据。

Grafana 与 Prometheus 的结合

Grafana 可以与 Prometheus 结合使用，将 Prometheus 的数据进行可视化展示。Grafana 可以创建各种类型的图表，用于展示 Prometheus 的数据，例如曲线图、柱状图、饼图等。

架构优点

Prometheus 和 Grafana 的结合具有以下优点：

可扩展性：Prometheus 和 Grafana 都是可扩展的系统，可以满足不同规模的监控需求。
灵活性：Prometheus 和 Grafana 提供了丰富的功能，可以满足不同的监控需求。
开源：Prometheus 和 Grafana 都是开源软件，可以免费使用。

三、安装prometheus和node-exporter

1. docker pull镜像

docker pull prom/node-exporter
docker pull prom/prometheus
docker pull grafana/grafana

2. 启动node-exporter

docker run -d -p 9100:9100 -v "/proc:/host/proc:ro" -v "/sys:/host/sys:ro" -v "/:/rootfs:ro" prom/node-exporter

访问url：
http://127.0.0.1:9100/metrics

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3. 启动prometheus

建立 /opt/prometheus/prometheus.yml

内容如下：

global:scrape_interval: 60sevaluation_interval:	60sscrape_configs:- job_name: prometheusstatic_configs:- targets: ['localhost:9090']labels:instance: prometheus- job_name: linuxstatic_configs:- targets: ['自己的ip:9100']labels:instance: localhost

启动：

docker run -d \
-p 9090:9090 \
-v /opt/prometheus/prometheus.yml:/etc/prometheus/prometheus.yml \
prom/prometheus

访问url：

127.0.0.1:9090/graph

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四、promql基本语法

不需要花过多的精力学习它用到的时候使用即可

Prometheus Query Language（PromQL）是用于查询和分析从 Prometheus 中收集的监控指标数据的查询语言。以下是 PromQL 的基本语法和一些常见的查询操作符：

选择时间范围：
- time(): 获取当前时间戳。
- timestamp(): 将时间戳转换为日期和时间。
- offset <duration>: 偏移查询的时间范围。
选择指标数据：
- <metric_name>: 选择具体的指标名称。
- {<label_name>=<label_value>}: 使用标签选择指标实例。
- up{job="api"}: 选择标签 job 等于 api 的指标数据。
基本查询操作符：
- =: 等于。
- !=: 不等于。
- =~: 正则表达式匹配。
- !~: 不匹配正则表达式。
聚合操作：
- sum(<vector>): 对指标数据进行求和。
- avg(<vector>): 对指标数据取平均值。
- min(<vector>): 获取指标数据的最小值。
- max(<vector>): 获取指标数据的最大值。
- count(<vector>): 计算指标数据的数量。
- rate(<vector>[<duration>]): 计算速率，通常用于计算速率指标，例如请求速率。
- increase(<vector>[<duration>]): 计算增长量，通常用于计算计数器类型的指标。
时间窗口：
- [<duration>]: 指定查询的时间范围。
- offset <duration>: 设置查询时间范围的偏移量。
聚合函数：
- by(<label>): 按标签对结果进行分组。
- topk(<k>, <vector>): 获取前 k 个结果。
- quantile(<q>, <vector>): 计算分位数。
布尔操作：
- and: 逻辑与。
- or: 逻辑或。
- unless: 逻辑非。
函数：PromQL 支持多种函数，用于对指标数据进行操作和处理，如 abs(), floor(), ceil(), round() 等。
括号：可以使用括号来控制操作符的优先级。

以下是一些示例 PromQL 查询：

up{job="api"}: 选择标签 job 等于 api 的 up 指标数据。
sum(rate(http_requests_total{job="web"}[5m])): 计算过去 5 分钟内 job 为 web 的 http_requests_total 指标的速率总和。
node_cpu{mode="idle"} / ignoring(cpu) group_left sum(node_cpu)：计算 node_cpu 中 mode 为 “idle” 的 CPU 使用率与所有 CPU 使用率的比例，同时按 node_cpu 的标签进行分组。

PromQL 具有丰富的功能和语法，允许您执行各种复杂的查询和分析操作，以满足您的监控需求。要深入了解 PromQL，请参考 Prometheus 官方文档或相关教程。

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五、grafana的安装和使用

1. 新建空文件夹grafana-storage，用来存储数据

mkdir /opt/grafana-storage
chmod 777 -R /opt/grafana-storage

2. 启动grafana(如果和已有的端口冲突改一下端口)

docker run -d -p 3000:3000 --name=grafana -v /opt/grafana-storage/:/var/lib/grafana grafana/grafana

访问：

127.0.0.1:3000

默认用户名密码：admin/admin

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3. 配置prometheus并使用

点进Data sources
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然后add一个

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输入自己的ip直接完成：

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这时候没有展示展示什么需要自己配置

重点了解一下panel或row就可以了

panel是仪表盘
row是很多panel

这里直接点蓝按钮了
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然后进行查询就可以看到数据了

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这里apply以后可以save保存

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保存完以后可以直接进来看你创建的指标 也就是一个row

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六、导入Grafana模板

官方模板：grafana.com/grafana/dashboards/?search=kafka

比如找一个redis的模板下载：

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下载完json之后导入到grafana：

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可以找其他的模板导入比如jaeger redis等等

七、guages、counter、histograms指标

guages

最简单的度量指标，只是一个简单的返回值，或者叫瞬时状态，我们想要知道一个队列中的个数
比如：当前的内存使用率、当前的CPU使用率、当前的磁盘使用率、当前的磁盘空间、当前的TCP连接数、当前的流量、当前的QPS、当前的DAU、当前的访问状态、当前的业务接口、当前的产品转换率、当前的充值额度、当前的业务日志、当前的系统日志、当前的网络设备、当前的服务器、当前的机柜、当前的电源、当前的UPS、当前的空调、当前的网络设备、当前的机房环境监控、当前的程序监控
随着时间的推移，这个值是不断变化的，这个值有可能增加，有可能减少

Counter

是计数器，这个值是从0开始累积，在理想状态下，这个值不可能减少
在理想状态下：如果我的服务器重启，同时这个数是放在内存中的

guages和counter是最主要的类型 70%

Histograms

http_res_time 表示http请求的响应时间
nginx
如果我要统计一天的所有访问的平均耗时
如果我们统计下来平均耗时是50ms 但是，现在中午有一段时间系统卡住了， 1W个请求平均耗时是在5s，
但是由于我们每天的访问量很大， 1000W访问量，这个5s耗时的请求就被平均掉了
越早发现越好，有可能是程序的bug，也有可能是系统的bug
50ms以内有多少请求， 50-200ms有多少请求 200ms-500ms有多少请求 500ms-1s有多少请求 1s-5s有多少请求 5s以上有多少请求
分布式图

八、go语言集成prometheus

直接上代码：

package mainimport ("github.com/gin-gonic/gin""github.com/prometheus/client_golang/prometheus""github.com/prometheus/client_golang/prometheus/promauto""github.com/prometheus/client_golang/prometheus/promhttp""time"
)// 声明一个counter
var (opt = promauto.NewCounter(prometheus.CounterOpts{Name: "jzin_test",Help: "just for test",})
)// 每秒自增
func recordMetrics() {for {opt.Inc()time.Sleep(2 * time.Second)}
}// 启动一个http服务，暴露metrics 让prometheus拉取
func main() {go recordMetrics()r := gin.Default()//promauto.NewCounter会把counter注册到defaultRegisterer中 gin.WrapH(promhttp.Handler())会把defaultRegisterer中的metrics暴露出来r.GET("/metrics", gin.WrapH(promhttp.Handler()))_ = r.Run(":8050")
}

启动后集成到/opt/prometheus里 添加你自己的ip:端口

比如：

global:scrape_interval: 60sevaluation_interval: 60sscrape_configs:- job_name: prometheusstatic_configs:- targets: ['localhost:9090']labels:instance: prometheus- job_name: linuxstatic_configs:- targets: ['172.26.28.143:9100', '你自己的ip:端口']labels:instance: localhost

然后重新运行prometheus

测试：
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也可以集成到Garfana中

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九、grpc框架集成prometheus

代码有点多有点复杂想要的私信吧

十、gin框架集成prometheus

使用现用的库：https://github.com/penglongli/gin-metrics.git

按照第三方实现即可：

package mainimport ("github.com/gin-gonic/gin""github.com/penglongli/gin-metrics/ginmetrics"
)func main() {r := gin.Default()// get global Monitor objectm := ginmetrics.GetMonitor()// +optional set metric path, default /debug/metricsm.SetMetricPath("/metrics")// +optional set slow time, default 5sm.SetSlowTime(10)// +optional set request duration, default {0.1, 0.3, 1.2, 5, 10}// used to p95, p99m.SetDuration([]float64{0.1, 0.3, 1.2, 5, 10})// set middleware for ginm.Use(r)r.GET("/product/:id", func(ctx *gin.Context) {"productId": ctx.Param("id"),})})_ = r.Run()
}

第三方还提供了garfana的直方图：

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看起来效果挺好

json导入：

{"annotations": {"list": [{"builtIn": 1,"datasource": "-- Grafana --","enable": true,"hide": true,"iconColor": "rgba(0, 211, 255, 1)","name": "Annotations & Alerts","type": "dashboard"}]},"editable": true,"gnetId": null,"graphTooltip": 0,"id": 1,"links": [],"panels": [{"datasource": null,"description": "Application request rate every 5 minutes.","fieldConfig": {"defaults": {"custom": {},"mappings": [],"thresholds": {"mode": "absolute","steps": [{"color": "green","value": null},{"color": "red","value": 80}]}},"overrides": []},"gridPos": {"h": 6,"w": 8,"x": 0,"y": 0},"id": 4,"options": {"reduceOptions": {"calcs": ["mean"],"fields": "","values": false},"showThresholdLabels": false,"showThresholdMarkers": true},"pluginVersion": "7.2.0","targets": [{"expr": "rate(gin_request_total[5m])","interval": "","legendFormat": "","refId": "A"}],"timeFrom": null,"timeShift": null,"title": "PV Rate","type": "gauge"},{"aliasColors": {},"bars": false,"dashLength": 10,"dashes": false,"datasource": "Prometheus","description": "","fieldConfig": {"defaults": {"custom": {}},"overrides": []},"fill": 1,"fillGradient": 0,"gridPos": {"h": 6,"w": 8,"x": 8,"y": 0},"hiddenSeries": false,"id": 2,"legend": {"avg": false,"current": false,"max": false,"min": false,"show": true,"total": false,"values": false},"lines": true,"linewidth": 1,"nullPointMode": "null","options": {"alertThreshold": true},"percentage": false,"pluginVersion": "7.2.0","pointradius": 2,"points": false,"renderer": "flot","seriesOverrides": [],"spaceLength": 10,"stack": false,"steppedLine": false,"targets": [{"expr": "gin_request_total","format": "time_series","instant": false,"interval": "","legendFormat": "{{instance}}","refId": "A"}],"thresholds": [],"timeFrom": null,"timeRegions": [],"timeShift": null,"title": "PV","tooltip": {"shared": true,"sort": 0,"value_type": "individual"},"type": "graph","xaxis": {"buckets": null,"mode": "time","name": null,"show": true,"values": []},"yaxes": [{"format": "short","label": 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"UV","tooltip": {"shared": true,"sort": 0,"value_type": "individual"},"type": "graph","xaxis": {"buckets": null,"mode": "time","name": null,"show": true,"values": []},"yaxes": [{"format": "short","label": null,"logBase": 1,"max": null,"min": null,"show": true},{"format": "short","label": null,"logBase": 1,"max": null,"min": null,"show": true}],"yaxis": {"align": false,"alignLevel": null}},{"aliasColors": {},"bars": false,"dashLength": 10,"dashes": false,"datasource": null,"fieldConfig": {"defaults": {"custom": {},"unit": "Bps"},"overrides": []},"fill": 1,"fillGradient": 0,"gridPos": {"h": 8,"w": 15,"x": 0,"y": 6},"hiddenSeries": false,"id": 12,"legend": {"avg": false,"current": false,"max": false,"min": false,"show": true,"total": false,"values": false},"lines": true,"linewidth": 1,"nullPointMode": "null","options": {"alertThreshold": true},"percentage": false,"pluginVersion": "7.2.0","pointradius": 2,"points": false,"renderer": "flot","seriesOverrides": [],"spaceLength": 10,"stack": false,"steppedLine": false,"targets": [{"expr": "rate(gin_request_body_total[5m])","interval": "","legendFormat": "{{instance}}-in","refId": "A"},{"expr": "rate(gin_response_body_total[5m])","interval": "","legendFormat": "{{instance}}-out","refId": "B"}],"thresholds": [],"timeFrom": null,"timeRegions": [],"timeShift": null,"title": "Traffic In-Out","tooltip": {"shared": true,"sort": 0,"value_type": "individual"},"type": "graph","xaxis": {"buckets": null,"mode": "time","name": null,"show": true,"values": []},"yaxes": [{"format": "Bps","label": null,"logBase": 1,"max": null,"min": null,"show": true},{"format": "bytes","label": null,"logBase": 1,"max": null,"min": null,"show": true}],"yaxis": {"align": false,"alignLevel": null}},{"cacheTimeout": null,"datasource": null,"fieldConfig": {"defaults": {"custom": {"align": null,"filterable": false},"mappings": [],"thresholds": {"mode": "absolute","steps": [{"color": "blue","value": null},{"color": "green","value": 80}]},"unit": 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0,"y": 14},"id": 13,"interval": null,"legend": {"show": true,"values": true},"legendType": "Right side","links": [],"nullPointMode": "connected","pieType": "pie","pluginVersion": "7.2.0","strokeWidth": 1,"targets": [{"expr": "sum by(method, instance) (gin_uri_request_total)","format": "time_series","instant": false,"interval": "","intervalFactor": 1,"legendFormat": "{{instance}}-{{method}}","refId": "A"}],"timeFrom": null,"timeShift": null,"title": "Method","type": "grafana-piechart-panel","valueName": "current"},{"aliasColors": {},"bars": false,"dashLength": 10,"dashes": false,"datasource": null,"fieldConfig": {"defaults": {"custom": {},"unit": "s"},"overrides": []},"fill": 1,"fillGradient": 0,"gridPos": {"h": 7,"w": 17,"x": 7,"y": 14},"hiddenSeries": false,"id": 16,"legend": {"avg": false,"current": false,"max": false,"min": false,"show": true,"total": false,"values": false},"lines": true,"linewidth": 1,"nullPointMode": "null","options": {"alertThreshold": true},"percentage": false,"pluginVersion": "7.2.0","pointradius": 2,"points": false,"renderer": "flot","seriesOverrides": [],"spaceLength": 10,"stack": false,"steppedLine": false,"targets": [{"expr": "histogram_quantile(0.95, sum (rate(gin_request_duration_bucket[5m])) by (le, instance))","interval": "","legendFormat": "p95","refId": "A"},{"expr": "histogram_quantile(0.99, sum (rate(gin_request_duration_bucket[5m])) by (le, instance))","interval": "","legendFormat": "p99","refId": "B"},{"expr": "sum (gin_request_duration_sum) / sum(gin_request_duration_count)","interval": "","legendFormat": "avg","refId": "C"}],"thresholds": [],"timeFrom": null,"timeRegions": [],"timeShift": null,"title": "Request Duration","tooltip": {"shared": true,"sort": 0,"value_type": "individual"},"type": "graph","xaxis": {"buckets": null,"mode": "time","name": null,"show": true,"values": []},"yaxes": [{"format": "s","label": null,"logBase": 1,"max": null,"min": null,"show": true},{"format": "bytes","label": null,"logBase": 1,"max": null,"min": null,"show": true}],"yaxis": {"align": false,"alignLevel": null}},{"aliasColors": {},"breakPoint": "50%","cacheTimeout": null,"combine": {"label": "Others","threshold": 0},"datasource": null,"decimals": null,"description": "","fieldConfig": {"defaults": {"custom": {"align": null,"filterable": false},"mappings": [],"thresholds": {"mode": "absolute","steps": [{"color": "blue","value": null},{"color": "green","value": 80}]},"unit": "none"},"overrides": []},"fontSize": "80%","format": "none","gridPos": {"h": 5,"w": 7,"x": 0,"y": 21},"id": 14,"interval": null,"legend": {"show": true,"values": true},"legendType": "Right side","links": [],"nullPointMode": "connected","pieType": "pie","pluginVersion": "7.2.0","strokeWidth": 1,"targets": [{"expr": "sum by(code, instance) (gin_uri_request_total)","format": "time_series","instant": false,"interval": "","intervalFactor": 1,"legendFormat": "{{instance}}-{{code}}","refId": "A"}],"timeFrom": null,"timeShift": null,"title": "Code","type": "grafana-piechart-panel","valueName": "current"},{"cacheTimeout": null,"datasource": null,"fieldConfig": {"defaults": {"custom": {"align": null,"filterable": false},"mappings": [],"thresholds": {"mode": "absolute","steps": [{"color": "blue","value": null},{"color": "green","value": 80}]},"unit": "none"},"overrides": []},"gridPos": {"h": 5,"w": 17,"x": 7,"y": 21},"id": 19,"interval": null,"links": [],"options": {"displayMode": "basic","orientation": "horizontal","reduceOptions": {"calcs": ["last"],"fields": "","values": false},"showUnfilled": true},"pluginVersion": "7.2.0","targets": [{"expr": "sum by(uri, instance) (gin_slow_request_total)","format": "time_series","instant": false,"interval": "","intervalFactor": 1,"legendFormat": "{{instance}}-{{uri}}","refId": "A"}],"timeFrom": null,"timeShift": null,"title": "Slow Request(default 5s)","type": "bargauge"}],"refresh": "5s","schemaVersion": 26,"style": "dark","tags": [],"templating": {"list": []},"time": {"from": "now-1h","to": "now"},"timepicker": {},"timezone": "","title": "Gin Application Metrics","uid": "FDB061FMz","version": 11
}

如果直方图报错Panel plugin not found: grafana-piechart-panel
那就给garfana安装插件

下载安装后放到插件目录/var/lib/grafana/plugins后重启grafana就可以了。

wget  https://grafana.com/api/plugins/grafana-piechart-panel/versions/latest/download -O grafana-piechart-panel.zip
unzip grafana-piechart-panel.zip 
mv grafana-piechart-panel grafana_data/plugins/
chown -R 472:472 *
docker restart grafana

把程序放到自己的服务器中多写几条get post命令进行测试：

测试结果：

在这里插入图片描述