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jmeter+prometheus+grafana监控搭建_prometheus grafana jmeter 部署
作者：从前慢现在也慢 | 2024-04-23 03:18:18
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prometheus grafana jmeter 部署
目录
一、jmeter、prometheus、grafana安装
我这里用的软件版本：jdk-11.0.21，jmeter-5.4.2，prometheus-2.47.2、grafana-10.0.3
本地Mac系统：jdk、Charles、GoReplay、NodeJs、grafana在Mac环境安装教程
服务器Linux系统：JDK、python、influxdb、jmeter在Linux服务器测试环境搭建教程
二、jmeter配置prometheus监听器
1、下载jmeter对应的prometheus监听器插件
目前jmeter对应的prometheus监听器插件github上有多个，我这里用的是下载量最多的jmeter-prometheus-plugin插件，版本jmeter-prometheus-plugin-0.7.1
常用的Prometheus Listener for Jmete插件
| 名称 | 适用平台 | 插件下载地址 | 开源地址 | 简介 | 备注 |
|---|---|---|---|---|---|
| jmeter-prometheus-plugin | window mac Linux | https://github.com/johrstrom/jmeter-prometheus-plugin/releases | https://github.com/johrstrom/jmeter-prometheus-plugin | 这个 JMeter 插件是高度可配置的监听器（和配置元素），允许用户定义他们自己的指标（名称、类型等），并通过 Prometheus /metrics API 公开它们，以供 Prometheus 服务器抓取。 | 需要自己配置自定义指标，只支持pull方式公开指标，有对应的grafana监控面板 |
| jmeter-prometheus-listener | window、 mac Linux | https://github.com/kolesnikovm/jmeter-prometheus-listener/releases | https://github.com/kolesnikovm/jmeter-prometheus-listener | 用于 Prometheus 指标导出的 Apache JMeter 后端侦听器实现。基于拉式和基于推式的模型都通过不同的实现来支持。 | 不需要自定义指标，支持通过pull跟push两种方式采集指标，需要自己配置监控面板 |
| jmeter_prom_exporter | docker | 启动命令：docker run --rm --name jmeter -i -v 密码:\tmp -p 9270:9270 chiabre/jmeter_prom_exporter:5.4.1-0.6.0 -t [YOUR_SCRIPT].jmx | https://github.com/chiabre/jmeter_prom_exporter | 复用jmeter-prometheus-plugin插件打包的docker镜像 | 这个没用过，自测 |
我这里用的示范是第一个插件，下载jmeter-prometheus-plugin-0.7.1.jar插件后，放在对应的jmeter/lib/ext目录下，重启jmeter
2、添加取样器
添加线程组-->添加http请求→添加查看结果树/聚合报告等
如果只需要测试一下插件是否可用，直接添加一个java请求测试一下即可
3、添加prometheus监听器
线程组-->添加Prometheus Listener，如果没有找到Prometheus Listener，请检查下载的jar包放的路径是否正确，需要重启jmeter
4、暴露相关指标
1、配置插件默认指标
需要暴露自带的指标，需要自己配置现有的指标名称跟类型，以下是插件内默认的指标跟类型
可以按如下图配置监听面板
第一列表示插件定义好的指标名，第一行表示对应的指标类型，x表示这个指标名称可以定义的指标类型
这是哪些指标类型可以衡量哪些指标的矩阵，如果你定义的指标名不在以下指标类型中，则该插件可能不会执行任何操作来更新该指标
| Histogram | Summary | Counter | Guage | Success Ratio | |
|---|---|---|---|---|---|
| Response time | x | x | |||
| Response size | x | x | |||
| Latency | x | x | |||
| Idle time | x | x | |||
| Connect time | x | x | |||
| Count total | x | ||||
| Failure total | x | ||||
| Success total | x | ||||
| Success Ratio | x |
2、默认指标添加标签
默认的指标标签，只有label跟code，我需要手动添加断言名称跟断言结果指标
使用JSR223监听器
import org.apache.jmeter.assertions.AssertionResult
// 获取当前采样器的名称
String samplerName = sampleResult.getSampleLabel();
// 获取响应代码
String responseCode = prev.getResponseCode();
// 获取前一个采样器的断言结果
AssertionResult[] assertionResults = prev.getAssertionResults();
for (AssertionResult assertionResult : assertionResults) {
if (assertionResult.isFailure() || assertionResult.isError()) {
// 如果断言失败或出现错误，获取断言名称、失败消息和断言类型，并存储为 JMeter 变量
String assertionName = assertionResult.getName();
String failureMessage = assertionResult.getFailureMessage();
vars.put("assertionName", assertionName);
vars.put("failureMessage", failureMessage);
}
} |
然后在prometheus listener监听器配置标签名称，直接引用jmeter变量即可
在jmeter_failure_total指标添加标签：label,code,assertionName,failureMessage
启动jmeter后，可以看到具体的标签有数据
3、配置自定义指标
配置自定义指标，需要提前创建指标名称跟指标类型，可以用插件自带的Prometheus Metrics完成，也可以用JSS223监听器创建
1、配置Prometheus Metrics面板
线程组-->配置元件-->添加Prometheus Metrics
配置Prometheus Metrics面板如下图
name：指标名称
help：帮助
lables：标签
type：指标类型
2、获取自定义指标
创建setUp线程组-->Prometheus Metrics→添加jmeter_assert_success、jmeter_assert_failures、jmeter_assert_total三个指标名称，定义计数器类型
每次压测前初始化指标，然后用JSR223监听器获取指标数据
获取断言失的名称、判断如果断言失败，获取响应的code，返回的断言结果
3、更新指标数据
用JR223监听器更新上面获取到的指标数据
JR223监听器完整代码如果下
import org.apache.jmeter.assertions.AssertionResult;
import io.prometheus.client.Counter;
// 获取当前取样器的名称
String samplerName = sampleResult.getSampleLabel();
// 获取并打印响应代码
String responseCode = prev.getResponseCode()
//log.info("Response Code: " + responseCode)
// 初始化断言成功和失败的计数器
Counter successes = (Counter) vars.getObject("jmeter_assert_success");
Counter failures = (Counter) vars.getObject("jmeter_assert_failures");
Counter total = (Counter) vars.getObject("jmeter_assert_total");
// 获取前一个取样器的断言结果
AssertionResult[] assertionResults = prev.getAssertionResults();
// 标记样本所有断言是否成功
boolean allAssertionsPassed = true;
// 检查断言结果并对计数器进行操作
for (AssertionResult assertionResult : assertionResults) {
if (assertionResult.isFailure() || assertionResult.isError()) {
// 如果断言失败，增加失败计数器
failures.labels(samplerName, responseCode, assertionResult.getFailureMessage()).inc();
allAssertionsPassed = false;
// 打印断言失败的信息
// log.info("----- Assertion Failed for Sampler: " + samplerName + " -----");
// log.info("Failure Message: " + assertionResult.getFailureMessage());
}
}
// 如果所有断言都成功，增加成功计数器
if (allAssertionsPassed) {
successes.labels(samplerName).inc();
}
// 最后增加总数量计算器
total.labels(samplerName).inc(); |
5、查看指标
1、当所有的prometheus指标都配置完成后，开始运行jmx文件。
2、在http://0.0.0.0:9270/metrics页面看到刚才配置的指标数据
常见问题：
1、指标名称不存在，但是指标TYPE存在。 --说明对应指标没有收集到内容，检查对应的指标类型跟指标名称是否有数据
2、指标名称不存在，指标TYPE也不存在 --说明对应的指标没有配置成功，需要结合jmeter报错日志进一步排查原因
3、指标名称存在，对应标签为null。–标签数据为null，说明没有取到标签的值，默认的指标名称，只有两个标签，label（取样器名称）跟code（hhtp状态码），如果是自己定义的指标标签为空，请确认标签获取到正确的值，并且成功更新指标
指标内容如下图
6、插件配置
要修改配置插件的配置，请在jmeter.properties文件（jmeter_HOME/bin文件夹）中添加properties，然后重新启动jmeter以使其生效
| Property | default | description |
|---|---|---|
| prometheus.port | 9270 | The port the http server will bind to |
| prometheus.ip | 127.0.0.1 | The ip the http server will bind to. Containers may need 0.0.0.0 |
| prometheus.delay | 0 | The delay (in seconds) the http server will wait before being destroyed |
| prometheus.save.threads | true | True or false value to save and collect jmeter thread metrics |
| prometheus.save.threads.name | jmeter_threads | The name of the metric describing jmeter threads |
| prometheus.save.jvm | true | Collect metrics from the JVM |
以下是具体的配置
# jmeter-prometheus-plugin插件配置 # http 服务器将绑定到的端口 prometheus.port=9270 # http 服务器将绑定到的 ip。容器可能需要0.0.0.0 prometheus.ip=0.0.0.0 # http 服务器在被销毁之前等待的延迟（以秒为单位） prometheus.delay=3 # 保存和收集 jmeter 线程指标的 True 或 false 值 prometheus.save.threads=true # 描述 jmeter 线程的指标名称 prometheus.save.threads.name=jmeter_threads # 从 JVM 收集指标 prometheus.save.jvm=true |
三、grafana添加prometheus数据源
添加数据源
1、grafana找到Data sources-->Add new data source-->Prometheus
测试访问
2、填写数据库地址、端口号、账号密码等，点击Save & test，提示Successfully queried the Prometheus API，就是能够正常访问
四、配置grafana监控面板
官方面板配置
1、在grafana找到Dashboards-->New-->Import→2492
这里官方配置的面板ID为，2492
2、查看面板监控是否生效，具体监控图参考这个
自定义面板配置
PS：官方的面板感觉有些指标是没生效的，我在它的基础上重新配置了一个面板
{
"annotations": {
"list": [
{
"builtIn": 1,
"datasource": {
"type": "datasource",
"uid": "grafana"
},
"enable": false,
"hide": true,
"iconColor": "rgba(0, 211, 255, 1)",
"name": "Annotations & Alerts",
"target": {
"limit": 100,
"matchAny": false,
"tags": [],
"type": "dashboard"
},
"type": "dashboard"
},
{
"datasource": {
"type": "prometheus",
"uid": "e592656e-dbb8-47b9-807f-fb74303af5c4"
},
"enable": false,
"expr": "jmeter_success_ratio_success",
"iconColor": "dark-blue",
"name": "Start/Stop marker",
"useValueForTime": false
}
]
},
"description": "A grafana dashboard to inspect jmeter metrics via prometheus ",
"editable": true,
"fiscalYearStartMonth": 0,
"gnetId": 14927,
"graphTooltip": 1,
"id": 22,
"links": [],
"liveNow": false,
"panels": [
{
"datasource": {
"type": "prometheus",
"uid": "e592656e-dbb8-47b9-807f-fb74303af5c4"
},
"fieldConfig": {
"defaults": {
"color": {
"mode": "thresholds"
},
"mappings": [
{
"options": {
"match": "null",
"result": {
"text": "N/A"
}
},
"type": "special"
}
],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green",
"value": null
},
{
"color": "red",
"value": 80
}
]
},
"unit": "none"
},
"overrides": []
},
"gridPos": {
"h": 4,
"w": 6,
"x": 0,
"y": 0
},
"id": 12,
"links": [],
"maxDataPoints": 100,
"options": {
"colorMode": "background",
"graphMode": "area",
"justifyMode": "center",
"orientation": "horizontal",
"reduceOptions": {
"calcs": [],
"fields": "",
"values": false
},
"text": {},
"textMode": "auto"
},
"pluginVersion": "10.0.3",
"targets": [
{
"datasource": {
"type": "prometheus",
"uid": "e592656e-dbb8-47b9-807f-fb74303af5c4"
},
"editorMode": "code",
"exemplar": true,
"expr": "sum(jmeter_threads{state=\"active\"})",
"format": "time_series",
"hide": false,
"instant": true,
"interval": "",
"intervalFactor": 1,
"legendFormat": "",
"refId": "A",
"step": 4
}
],
"title": "Threads",
"type": "stat"
},
{
"datasource": {
"type": "prometheus",
"uid": "e592656e-dbb8-47b9-807f-fb74303af5c4"
},
"fieldConfig": {
"defaults": {
"color": {
"mode": "thresholds"
},
"decimals": 0,
"mappings": [
{
"options": {
"match": "null",
"result": {
"text": "N/A"
}
},
"type": "special"
}
],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green",
"value": null
}
]
},
"unit": "none"
},
"overrides": []
},
"gridPos": {
"h": 4,
"w": 6,
"x": 6,
"y": 0
},
"id": 7,
"links": [],
"maxDataPoints": 100,
"options": {
"colorMode": "background",
"graphMode": "area",
"justifyMode": "center",
"orientation": "horizontal",
"reduceOptions": {
"calcs": [],
"fields": "",
"values": false
},
"text": {},
"textMode": "auto"
},
"pluginVersion": "10.0.3",
"targets": [
{
"datasource": {
"type": "prometheus",
"uid": "e592656e-dbb8-47b9-807f-fb74303af5c4"
},
"editorMode": "code",
"exemplar": true,
"expr": "sum(jmeter_count_total{})",
"format": "time_series",
"instant": false,
"interval": "",
"intervalFactor": 1,
"legendFormat": "",
"refId": "E"
}
],
"title": "Total Request ",
"type": "stat"
},
{
"datasource": {
"type": "prometheus",
"uid": "e592656e-dbb8-47b9-807f-fb74303af5c4"
},
"fieldConfig": {
"defaults": {
"color": {
"mode": "thresholds"
},
"decimals": 1,
"mappings": [
{
"options": {
"match": "null",
"result": {
"text": "N/A"
}
},
"type": "special"
}
],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green",
"value": null
},
{
"color": "red",
"value": 1
}
]
},
"unit": "none"
},
"overrides": []
},
"gridPos": {
"h": 4,
"w": 6,
"x": 12,
"y": 0
},
"id": 14,
"links": [],
"maxDataPoints": 100,
"options": {
"colorMode": "background",
"graphMode": "area",
"justifyMode": "center",
"orientation": "horizontal",
"reduceOptions": {
"calcs": [],
"fields": "",
"values": false
},
"text": {},
"textMode": "auto"
},
"pluginVersion": "10.0.3",
"targets": [
{
"datasource": {
"type": "prometheus",
"uid": "e592656e-dbb8-47b9-807f-fb74303af5c4"
},
"editorMode": "code",
"exemplar": true,
"expr": "sum(jmeter_failure_total)",
"format": "time_series",
"hide": false,
"instant": false,
"interval": "",
"intervalFactor": 1,
"legendFormat": "__auto",
"metric": "",
"refId": "A",
"step": 4
}
],
"title": "Failure Request Count",
"type": "stat"
},
{
"datasource": {
"type": "prometheus",
"uid": "e592656e-dbb8-47b9-807f-fb74303af5c4"
},
"fieldConfig": {
"defaults": {
"color": {
"mode": "thresholds"
},
"decimals": 1,
"mappings": [
{
"options": {
"match": "null",
"result": {
"text": "N/A"
}
},
"type": "special"
}
],
"thresholds": {
"mode": "percentage",
"steps": [
{
"color": "#37872D",
"value": null
},
{
"color": "#FF9830",
"value": 0.1
},
{
"color": "#E02F44",
"value": 10
}
]
},
"unit": "percentunit"
},
"overrides": []
},
"gridPos": {
"h": 4,
"w": 6,
"x": 18,
"y": 0
},
"id": 8,
"links": [],
"maxDataPoints": 100,
"options": {
"orientation": "horizontal",
"reduceOptions": {
"calcs": [],
"fields": "",
"values": false
},
"showThresholdLabels": false,
"showThresholdMarkers": true,
"text": {}
},
"pluginVersion": "10.0.3",
"targets": [
{
"datasource": {
"type": "prometheus",
"uid": "e592656e-dbb8-47b9-807f-fb74303af5c4"
},
"editorMode": "code",
"exemplar": true,
"expr": "(sum(rate(jmeter_failure_total[$__rate_interval]))/sum(rate(jmeter_count_total[$__rate_interval])))",
"format": "time_series",
"instant": false,
"interval": "",
"intervalFactor": 1,
"legendFormat": "",
"range": true,
"refId": "A",
"step": 4
}
],
"title": "Failure Rate %",
"type": "gauge"
},
{
"collapsed": false,
"datasource": {
"type": "influxdb",
"uid": "e18c3112-795a-412c-926c-982c2e078ad2"
},
"gridPos": {
"h": 1,
"w": 24,
"x": 0,
"y": 4
},
"id": 17,
"panels": [],
"targets": [
{
"datasource": {
"type": "influxdb",
"uid": "e18c3112-795a-412c-926c-982c2e078ad2"
},
"refId": "A"
}
],
"title": "Load Test Summary",
"type": "row"
},
{
"datasource": {
"type": "prometheus",
"uid": "e592656e-dbb8-47b9-807f-fb74303af5c4"
},
"description": "",
"fieldConfig": {
"defaults": {
"color": {
"mode": "palette-classic"
},
"custom": {
"axisCenteredZero": false,
"axisColorMode": "text",
"axisLabel": "ops",
"axisPlacement": "auto",
"barAlignment": 0,
"drawStyle": "line",
"fillOpacity": 10,
"gradientMode": "none",
"hideFrom": {
"legend": false,
"tooltip": false,
"viz": false
},
"lineInterpolation": "linear",
"lineWidth": 1,
"pointSize": 5,
"scaleDistribution": {
"type": "linear"
},
"showPoints": "never",
"spanNulls": false,
"stacking": {
"group": "A",
"mode": "none"
},
"thresholdsStyle": {
"mode": "off"
}
},
"links": [],
"mappings": [],
"thresholds": {
"mode": "absolute",
"steps": [
{
"color": "green",
"value": null
},
{
"color": "red",
"value": 80
}
]
},
"unit": "none"
},
"overrides": [
{
"matcher": {
"id": "byName",
"options": "Failure "
},
"properties": [
{
"id": "color",
"value": {
"fixedColor": "#bf1b00",
"mode": "fixed"
}
}
]
},
{
"matcher": {
"id": "byName",
"options": "OK"
},
"properties": [
{
"id": "color",
"value": {
"fixedColor": "dark-green",
"mode": "fixed"
}
}
]
},
{
"matcher": {
"id": "byName",
"options": "Virtual Users"
},
"properties": [
{
"id": "color",
"value": {
"fixedColor": "#3274D9",
"mode": "fixed"
}
},
{
"id": "custom.fillOpacity",
"value": 40
},
{
"id": "custom.lineWidth",
"value": 0
},
{
"id": "custom.lineWidth",
"value": 3
},
{
"id": "unit",
"value": "short"
},
{
"id": "custom.axisPlacement",
"value": "hidden"
},
{
"id": "custom.axisLabel",
"value": "VU"
}
]
},
{
"matcher": {
"id": "byName",
"options": "Request OK per second"
},
"properties": [
{
"id": "color",
"value": {
"fixedColor": "#19730E",
"mode": "fixed"
}
}
]
},
{
"matcher": {
"id": "byName",
"options": "Request KO per second"
},
"properties": [
{
"id": "color",
"value": {
"fixedColor": "#AD0317",
"mode": "fixed"
}
}
]
}
]
},
"gridPos": {
"h": 7,
"w": 8,
"x": 0,
"y": 5
},
"id": 36,
"links": [],
"options": {
"legend": {
"calcs": [
"mean",
"max",
"min"
],
"displayMode": "table",
"placement": "bottom",
"showLegend": true
},
"tooltip": {
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