Prometheus+Grafana监控系统通过kafka_exporter监控kafka
Kafka Dashboard模板：
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},
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"legendFormat": "{{instance}}-networkprocessor_1",
"refId": "B"
},
{
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"format": "time_series",
"intervalFactor": 1,
"legendFormat": "{{instance}}-networkprocessor_2",
"refId": "C"
}
],
"thresholds": [],
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"tooltip": {
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}
},
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"dashLength": 10,
"dashes": false,
"datasource": "${DS_PROMETHEUS}",
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"fill": 1,
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"points": false,
"renderer": "flot",
"seriesOverrides": [],
"spaceLength": 10,
"stack": false,
"steppedLine": false,
"targets": [
{
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"format": "time_series",
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"legendFormat": "{{instance}}-{{request}}",
"refId": "A"
}
],
"thresholds": [],
"timeFrom": null,
"timeShift": null,
"title": "请求在请求队列等待时间",
"tooltip": {
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},
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]
},
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"bars": false,
"dashLength": 10,
"dashes": false,
"datasource": "${DS_PROMETHEUS}",
"description": "请求(producer,Fetch-Consumer,Fetch-Follower)等待follower花费的时间",
"fill": 1,
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"points": false,
"renderer": "flot",
"seriesOverrides": [],
"spaceLength": 10,
"stack": false,
"steppedLine": false,
"targets": [
{
"expr": "rate(kafka_network_requestmetrics_remotetimems{request =~ \"Produce|FetchConsumer|FetchFollower\"}[15m])",
"format": "time_series",
"intervalFactor": 1,
"legendFormat": "{{instance}}-{{request}}",
"refId": "A"
}
],
"thresholds": [],
"timeFrom": null,
"timeShift": null,
"title": "等待follower花费的时间",
"tooltip": {
"shared": true,
"sort": 0,
"value_type": "individual"
},
"type": "graph",
"xaxis": {
"buckets": null,
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},
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}
]
},
{
"aliasColors": {},
"bars": false,
"dashLength": 10,
"dashes": false,
"datasource": "${DS_PROMETHEUS}",
"description": "Time the request waits in the response queue",
"fill": 1,
"gridPos": {
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},
"id": 132,
"legend": {
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"points": false,
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"stack": false,
"steppedLine": false,
"targets": [
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"format": "time_series",
"intervalFactor": 1,
"legendFormat": "{{instance}}{{request}}",
"refId": "A"
}
],
"thresholds": [],
"timeFrom": null,
"timeShift": null,
"title": "请求在响应队列中等待的时间",
"tooltip": {
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"value_type": "individual"
},
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}
]
},
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"bars": false,
"dashLength": 10,
"dashes": false,
"datasource": "${DS_PROMETHEUS}",
"description": "请求(producer,Fetch-Consumer,Fetch-Follower)在leader处理请求花的时间",
"fill": 1,
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},
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"legend": {
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},
"lines": true,
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"points": false,
"renderer": "flot",
"seriesOverrides": [],
"spaceLength": 10,
"stack": false,
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"targets": [
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"format": "time_series",
"intervalFactor": 1,
"legendFormat": "{{instance}}-{{request}}",
"refId": "A"
}
],
"thresholds": [],
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"timeShift": null,
"title": "leader处理请求花费的时间",
"tooltip": {
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},
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]
},
{
"aliasColors": {},
"bars": false,
"dashLength": 10,
"dashes": false,
"datasource": "${DS_PROMETHEUS}",
"description": "一个请求(producer,Fetch-Consumer,Fetch-Follower)耗费的所有时间",
"fill": 1,
"gridPos": {
"h": 9,
"w": 12,
"x": 0,
"y": 125
},
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},
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"pointradius": 5,
"points": false,
"renderer": "flot",
"seriesOverrides": [],
"spaceLength": 10,
"stack": false,
"steppedLine": false,
"targets": [
{
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"format": "time_series",
"intervalFactor": 1,
"legendFormat": "{{instance}}-{{request}}",
"refId": "A"
}
],
"thresholds": [],
"timeFrom": null,
"timeShift": null,
"title": "(producer,Fetch-Consumer,Fetch-Follower)请求耗费的所有时间",
"tooltip": {
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"sort": 0,
"value_type": "individual"
},
"type": "graph",
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}
]
},
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"dashes": false,
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"description": "Time to send the response",
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},
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},
"lines": true,
"linewidth": 1,
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"pointradius": 5,
"points": false,
"renderer": "flot",
"seriesOverrides": [],
"spaceLength": 10,
"stack": false,
"steppedLine": false,
"targets": [
{
"expr": "rate(kafka_network_requestmetrics_responsesendtimems{request =~ \"Produce|FetchConsumer|FetchFollower\"}[5m])",
"format": "time_series",
"intervalFactor": 1,
"legendFormat": "{{instance}}-{{request}}",
"refId": "A"
}
],
"thresholds": [],
"timeFrom": null,
"timeShift": null,
"title": "发送响应花费的时间",
"tooltip": {
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"sort": 0,
"value_type": "individual"
},
"type": "graph",
"xaxis": {
"buckets": null,
"mode": "time",
"name": null,
"show": true,
"values": []
},
"yaxes": [
{
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"max": null,
"min": null,
"show": true
},
{
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"max": null,
"min": null,
"show": true
}
]
}
],
"refresh": "1m",
"schemaVersion": 16,
"style": "dark",
"tags": [],
"templating": {
"list": []
},
"time": {
"from": "now/d",
"to": "now/d"
},
"timepicker": {
"refresh_intervals": [
"5s",
"10s",
"30s",
"1m",
"5m",
"15m",
"30m",
"1h",
"2h",
"1d"
],
"time_options": [
"5m",
"15m",
"1h",
"6h",
"12h",
"24h",
"2d",
"7d",
"30d"
]
},
"timezone": "",
"title": "Kafka Dashboard",
"uid": "Vbm7Botmk",
"version": 9
}
下载Prometheus：
https://github.com/prometheus/prometheus/releases/download/v2.8.1/prometheus-2.8.1.linux-amd64.tar.gz
下载Kafka_exporter:
https://github.com/danielqsj/kafka_exporter/releases/download/v1.2.0/kafka_exporter-1.2.0.linux-amd64.tar.gz
下载Grafana:
https://grafana.com/grafana/download
- 要在你想监控kafka的机器上装上kafka_exporter，每个都要装，我的机器是157、158、187：
解压kafka_exporter，进到目录，执行命令：
nohup ./kafka_exporter --kafka.server=10.131.178.157:9092 &
没有报错就成功了！
- 在要显示页面的机器上安装Prometheus，我的机器是186:
解压Prometheus，进入目录，
vim prometheus.yml(具体修改见下图)
nohup ./prometheus &
启动成功后在浏览器输入10.131.178.186:9090，成功效果图见下：
- 在186机器上安装Grafana，下载解压后进去
bin目录下：
nohup ./grafana-server &
-
打开浏览器，输入10.131.178.186:3000，就会显示页面：
-
配置Grafana数据源，见下图：
-
导入Kafka数据模板Kafka Dashboard：
-
成功截图，不截了，测试机器就一个图表有数据！
更多问题详见我博客的其他文章！！！
图废了！！！