promethues监控体系
promethues
前言：
最近项目中用到了promethues做服务告警，这里就把自己探索过程中收集到的文档整理出来，以及一些自己使用过程中的东西
简介
Prometheus 是一套开源的系统监控报警框架。它启发于 Google 的 borgmon 监控系统，由工作在 SoundCloud 的
google 前员工在 2012 年创建，作为社区开源项目进行开发，并于 2015 年正式发布。2016 年，Prometheus 正式加入
Cloud Native Computing Foundation，成为受欢迎度仅次于 Kubernetes 的项目。
有人可能会疑惑：promethues和grafana结合岂不是可以把预警、日志分析全做了？
其实官方强烈不推荐使用promethues和grafana做日志分析的，官方解释日志分析还是交由专业的ELK去做，不建议使用promethues和grafana。
作为新一代的监控框架，Prometheus 具有以下特点：
- 强大的多维度数据模型：
- 时间序列数据通过 metric 名和键值对来区分。
- 所有的 metrics 都可以设置任意的多维标签。
- 数据模型更随意，不需要刻意设置为以点分隔的字符串。
- 可以对数据模型进行聚合，切割和切片操作。
- 支持双精度浮点类型，标签可以设为全 unicode。
- 灵活而强大的查询语句（PromQL）：在同一个查询语句，可以对多个 metrics 进行乘法、加法、连接、取分数位等操作。
- 易于管理： Prometheus server 是一个单独的二进制文件，可直接在本地工作，不依赖于分布式存储。
- 高效：平均每个采样点仅占 3.5 bytes，且一个 Prometheus server 可以处理数百万的 metrics。
- 使用 pull 模式采集时间序列数据，这样不仅有利于本机测试而且可以避免有问题的服务器推送坏的 metrics。
- 可以采用 push gateway 的方式把时间序列数据推送至 Prometheus server 端。
- 可以通过服务发现或者静态配置去获取监控的 targets。
- 有多种可视化图形界面。
- 易于伸缩。
需要指出的是，由于数据采集可能会有丢失，所以 Prometheus 不适用对采集数据要 100% 准确的情形。但如果用于记录时间序列数据，Prometheus 具有很大的查询优势，此外，Prometheus 适用于微服务的体系架构
组成&工作流
架构
如图所示，即为promethues的架构图
概念介绍
Prometheus Server：
Prometheus Sever是Prometheus组件中的核心部分，负责实现对监控数据的获取，存储及查询。Prometheus
Server可以通过静态配置管理监控目标，也可以配合使用Service
Discovery的方式动态管理监控目标，并从这些监控目标中获取数据。其次Prometheus
Sever需要对采集到的数据进行存储，Prometheus
Server本身就是一个实时数据库，将采集到的监控数据按照时间序列的方式存储在本地磁盘当中。Prometheus
Server对外提供了自定义的PromQL，实现对数据的查询以及分析。另外Prometheus
Server的联邦集群能力可以使其从其他的Prometheus Server实例中获取数据。
Exporters：
Exporter将监控数据采集的端点通过HTTP服务的形式暴露给Prometheus Server，Prometheus
Server通过访问该Exporter提供的Endpoint端点，即可以获取到需要采集的监控数据。可以将Exporter分为2类：
直接采集：
这一类Exporter直接内置了对Prometheus监控的支持，比如cAdvisor，Kubernetes，Etcd，Gokit等，都直接内置了用于向Prometheus暴露监控数据的端点。
间接采集：
原有监控目标并不直接支持Prometheus，因此需要通过Prometheus提供的Client
Library编写该监控目标的监控采集程序。例如：Mysql Exporter，JMX Exporter，Consul Exporter等。
AlertManager：
在Prometheus Server中支持基于Prom QL创建告警规则，如果满足Prom
QL定义的规则，则会产生一条告警。在AlertManager从 Prometheus server 端接收到
alerts后，会进行去除重复数据，分组，并路由到对收的接受方式，发出报警。常见的接收方式有：电子邮件，pagerduty，webhook
等。
PushGateway:
Prometheus数据采集基于Prometheus Server从Exporter pull数据，因此当网络环境不允许Prometheus
Server和Exporter进行通信时，可以使用PushGateway来进行中转。通过PushGateway将内部网络的监控数据主动Push到Gateway中，Prometheus
Server采用针对Exporter同样的方式，将监控数据从PushGateway pull到Prometheus Server。
Prometheus的工作流：
pull(拉取)
Prometheus
server定期从配置好的jobs或者exporters中拉取metrics(所有拉取规则都是在rules.yml配置文件中配置)，或者接收来自Pushgateway发送过来的metrics，或者从其它的Prometheus
server中拉metrics。
存储
Prometheus server在本地存储收集到的metrics，并运行定义好的alerts.rules，记录新的时间序列或者向Alert
manager推送警报。
预警
Alertmanager根据配置文件，对接收到的警报进行处理，发出告警。
展示
在图形界面中，可视化采集数据。可以采用Grafana做最后的图形展示。
安装和配置
文中promethues相关下载链接(提前公示),点击此处即可跳转
包含以下:
- prometheus
- alertmanager
- node_exporter
其他的官方提供的exporter(提前公示),点击此处即可跳转
一、oracle监控安装
它是用来监控oracle数据库的，可以和oracle安装在同一个服务器，也可以不同，这里建议还是不要装在一台服务器上，对数据库服务器是有性能上的影响的。
1.1 首先需要下载以下安装包：
oracledb_exporter.0.2.2.linux-amd64.tar.gz ===>地址：https://prometheus.io/docs/instrumenting/exporters/
以下三个地址：====>https://www.oracle.com/database/technologies/instant-client/linux-x86-64-downloads.html
oracle-instantclient18.5-basic-18.5.0.0.0-3.x86_64.rpm
oracle-instantclient18.5-devel-18.5.0.0.0-3.x86_64.rpm
oracle-instantclient18.5-sqlplus-18.5.0.0.0-3.x86_64.rpm
1.2 安装：
1.2.1 如果是centos系统可以直接安装这三个oracle客户端组件，安装命令：
rpm -ivh 包全名
1.2.2 如果是Ubuntu系统，则需要转换为Ubuntu的安装包，再进行安装，转换命令如下：
sudo apt-get install alien #alien默认没有安装，所以首先要安装它
sudo alien xxxx.rpm #将rpm转换位deb，完成后会生成一个同名的xxxx.deb
sudo dpkg -i xxxx.deb #安装
1.3 环境变量设置：
修改环境变量
vim /etc/profile
文件末尾追加这三个环境变量
export DATA_SOURCE_NAME=oracle_exporter/Wl4L7CDM5@//172.30.130.116:1521/orcl #这里填写监控用的用户名及密码，需要注意的是，这个用户必须具有dba权限。
export LD_LIBRARY_PATH=/usr/lib/oracle/18.5/client64/lib:/usr/lib/oracle/18.5/client64 #这里是oracle客户端安装完后的位置，自行去'/usr/lib/oracle/'这个目录下核查目录路径是否正确，如果版本号不对，手动修改这个值
export ORACLE_HOME=/usr/lib/oracle/18.5/client64 #核对目录并检查版本号
之后使环境变量生效即可
source /etc/profile
1.4 安装oracledb_exporter
他不需要安装，解压即可使用
tar -zxvf oracledb_exporter.0.2.2.linux-amd64.tar.gz
cd oracledb_exporter.0.2.2.linux-amd64
nohup ./oracledb_exporter &
二、 node_exporter安装
它是用来监控各节点的状态，需要安装在各需要监控的服务器上，一个服务器安装一个。下载的地址如下：
https://prometheus.io/docs/instrumenting/exporters/
在上述地址请求后的页面中找到要下载的node_exporter，并下载。
下载后：
1. mkdir -p /server/deployment/
2. 将node_exporter-0.18.1.linux-amd64.tar.gz移至/server/deployment/
3. 解压node_exporter-0.18.1.linux-amd64.tar.gz =====》命令： tar -zxvf node_exporter-0.18.1.linux-amd64.tar.gz
4. 进入到/server/deployment/node_exporter-0.18.1.linux-amd64 ===>命令： cd /server/deployment/node_exporter-0.18.1.linux-amd64
5. nohup /server/deployment/node_exporter-0.18.1.linux-amd64/node_exporter & #后台启动即可
他的默认监听端口是9100，如果发现与本机的服务端口有所冲突，可以指定其监听的端口。但是需要注意的是，修改完监听端口后，一定要在 3.2.1 prometheus.yml配置 中修改你所指定的这个端口。
修改默认端口的命令(将下面的9100改为你所要监听的指定端口)：
nohup /server/deployment/node_exporter-0.18.1.linux-amd64/node_exporter --web.listen-address=":9100" &
三、安装promethues
他是用来汇总监控信息的中央控制器，并且会发送告警信息给alertmanager
3.1 下载prometheus-2.15.2.linux-amd64.tar.gz
https://prometheus.io/download/
选择自己需要的版本进行下载
3.2 解压即可用，重要的是需要进行配置
注意:
- 这里的格式一定不要错乱，要保证严格的yml格式，比如最简单的各种对齐，否则启动会报错
- 项目中有的机器会出现中文不兼容的问题，所以最好将我下文中的模板中中文注释去除
3.2.1 prometheus.yml配置
global:
scrape_interval: 15s #全局的间隔请求时间
evaluation_interval: 15s #指的是计算rule的间隔
scrape_timeout: 10s #间隔请求超时时间，这个是不能大于scrape_interval的
external_labels:
monitor: 'codelab_monitor'
alerting:
alertmanagers: #这个是alertmanager的配置，用来最后发出告警信息的模块，在哪安装的他，就配置安装的信息即可，他的默认端口号是9093
- static_configs:
- targets: ["localhost:9093"]
rule_files:
- "/server/prometheus-2.18.0-rc.0.linux-amd64/rules.yml" #prometheus的告警规则配置文件地址
scrape_configs:
- job_name: 'prometheus'
static_configs:
- targets: ['localhost:9090']
- job_name: 'node' #各节点的配置信息，这里配置的主要是node_exporter的监控信息，如果你没有对他的默认端口进行修改，那么就写9100即可
static_configs:
- targets: ['{IP}:9100'] #为了通用性，我将服务器ip换成了{IP}，使用时将其替换成真正的ip地址即可
- job_name: 'nginx'
scrape_interval: 5s #在这里配置这个请求间隔时间是会覆盖掉global里的全局间隔时间的
static_configs:
- targets: ['{IP}:9913']
- job_name: 'oracle'
scrape_interval: 10s
static_configs:
- targets: ['localhost:9161'] #这些端口号并不是随意填写的，他们都是各个监控器的监听端口，这个是oracledb_exporter
- job_name: 'redis'
scrape_interval: 10s
static_configs:
- targets: ['{IP1}:9121','{IP2}:9121']
- job_name: ‘rabbit_mq'
scrape_interval:10s
static_configs:
- targets: ['{IP1}:9419']
3.2.2 rules.yml配置
在prometheus文件夹下新建rules.yml,这个是告警规则，有的服务器不支持中文，有的支持，不支持的话翻译成英文即可，当然，写英文的更好，防止乱码的出现。部署时，建议务必删除下文中我的中文注释，以防报错
groups:
- name: hostStatsAlert
rules:
- alert: "memory-warning" #内存告警规则，持续1分钟大于90%即可告警
expr: ((node_memory_MemTotal_bytes-(node_memory_MemFree_bytes+node_memory_Buffers_bytes+node_memory_Cached_bytes))/node_memory_MemTotal_bytes)*100>90
for: 1m
labels:
severity: warning
annotations:
summary: "{{ $labels.instance }} Server memory usage is over 90%"
description: "{{ $labels.instance }} Server memory usage is over 90%, the current value is: {{ $value }}%"
- alert: "CPU-warning" #CPU告警规则，使用率持续1分钟大于90%，即可告警
expr: round(100-((avg by (instance,job)(irate(node_cpu_seconds_total{mode="idle",instance!~'bac-.*'}[5m]))) *100))>90
for: 1m
labels:
severity: warning
annotations:
summary: "{{ $labels.instance }} Excessive CPU utilization"
description: "{{ $labels.instance }} Excessive CPU utilization, current utilization is: {{ $value }}%"
- alert: "diskSpace-warning" #磁盘空间告警规则，可用磁盘小于5G持续10秒，即可告警
expr: round(node_filesystem_avail_bytes{fstype=~"ext4|xfs",instance!~"testnode",mountpoint!~"/boot.*"}/1024/1024/1024) < 5
for: 10s
labels:
severity: warning
annotations:
summary: "{{ $labels.instance }} Insufficient disk space"
description: "{{ $labels.instance }} Insufficient disk space, current disk space is: {{$labels.mountpoint}} remaining: {{ $value }}GB"
- alert: "nodeStatus-warning" #节点存活状态告警规则，1就是正常，0就是挂了，如果持续15秒都是挂的状态，即可告警
expr: up == 0
for: 15s
labels:
severity: warning
annotations:
summary: "{{ $labels.instance }} Machine survival test"
description: "{{ $labels.instance }} The machine is down, please check!"
- alert: "oracle-warning" #oracle存活状态告警规则，1就是正常，0就是挂了，如果持续15秒都是挂的状态，即可告警
expr: probe_success == 0
for: 15s
labels:
severity: warning
annotations:
summary: "{{ $labels.job }} oracle is breakdown"
description: "{{ $labels.job }} oracle is breakdown"
3.3 启动
nohup /server/prometheus-2.15.2.linux-amd64/prometheus --config.file=/server/prometheus-2.15.2.linux-amd64/prometheus.yml &
说明： 如果需要新增其他的监控，比如rabbit mq、redis等，需要注意的有三点：
1) 到[监控插件下载地址](https://prometheus.io/docs/instrumenting/exporters/ ) 这个地址去下载相关的exporter，大部分都是开箱即用，解压即可使用，当然也会有需要填写一些附带信息的。
2）接着需要修改prometheus.yml，新增一个job_name模块即可。
3）接着需要修改rules.yml，新增相关的告警指标即可。具体的指标可以访问prometheus提供的页面http://172.16.52.37:9090/targets，（就是prometheus的默认提供服务的接口：9090，在那边可以找到很多参数指标，可自行组合设置）
4）最后重启prometheus即可，可以直接kill掉原来的，直接重启即可。
四、安装Alertmanager
alertmanager是告警模块，他负责将prometheus的告警信息收集并统一发送出去，里面可以直接配置钉钉的机器人接口地址，具体方法可以网上搜寻一下，我们是使用web.hook将告警信息发送到指定的web服务里，将其进行一些处理后在发送给钉钉。
4.1 下载
https://prometheus.io/download/
在上述地址中可以找到alertmanager的下载。下载完后将其解压，配置基本信息即可配合prometheus使用
4.2 配置
编辑alertmanager.yml
global:
resolve_timeout: 5m
route:
group_by: ['prometheus']
group_wait: 10s
group_interval: 10s
repeat_interval: 10m
receiver: 'web.hook'
receivers:
- name: 'web.hook'
webhook_configs:
- url: 'http://{IP}:8012/api/messages/receive' #web服务接收告警信息地址
http_config:
bearer_token: LhTIaDGXAu1yAeKiAWobgZDo0GMQZR6l #设置这个token，增加相应的安全性，这个token是在header里
inhibit_rules:
- source_match:
severity: 'critical'
target_match:
severity: 'warning'
equal: ['alertname', 'dev', 'instance']
4.3 启动
nohup ./alertmanager --config.file=/server/alertmanager-0.20.0.linux-amd64/alertmanager.yml &
五、安装Grafana
5.1 下载
https://grafana.com/grafana/download
下载Grafana,解压后直接进入bin目录,执行下面的命令即可启动，grafana最麻烦的地方在于配置监控信息
./grafana-server web
5.2 配置
默认端口3000，{部署的服务器ip}:3000 即可访问页面。默认的初始用户名/密码：admin/admin
第一次登陆会提示修改密码。修改即可。
进入后，如下图所示操作即可
5.2.1 配置数据源（prometheus）
保存即可
5.2.2 配置监控面板
导入模板
这里有技巧，你可以自己写，但是会很麻烦，费力不讨好，自己写一些模板里没有的特定的还是可以的，其他的还是建议直接导入模板
这里有你想要的各类模板
https://grafana.com/grafana/dashboards?orderBy=name&direction=asc
这里有已经调试过得两个模板,新建两个json文件，将他们的内容保存进去，文件见 七、附件
保存完了之后
点击这些监控面板即可，可以看到很多监控信息
六、总结
6.1 怎么知道自己有没有启动成功prometheus？
答：
http://{prometheus部署的ip}:9090
直接访问即可，如果部署成功，会有web页面的
6.2 需要注意的地方：
6.2.1 防火墙要开几个特殊的端口
比如这个机子上安装的各类监控器的监听端口：9100、9090等等，按需开启，centos的开启命令.
如果你没有开启，那么会导致你的监控器无法访问
firewall-cmd --zone=public --add-port=9090/tcp --permanent
systemctl restart firewalld.service
6.2.2 服务器时间
项目中有碰到过因服务器时间未同步导致的grafana无法获取信息的问题，所以以上完成后，请检查一下自己的服务器时间是否已经同步
七、附件
Oracledb监控-性能与表空间-1587890196110.json
{
"annotations": {
"list": [
{
"builtIn": 1,
"datasource": "Prometheus",
"enable": false,
"hide": true,
"iconColor": "rgba(0, 211, 255, 1)",
"limit": 100,
"name": "Annotations & Alerts",
"showIn": 0,
"type": "dashboard"
}
]
},
"description": "使用oracledb-exporter进行oracle数据库监控，相对其他dashboard增加了tablespace的监控，可拓展设置为表空间告警；\n\n",
"editable": true,
"gnetId": 11121,
"graphTooltip": 1,
"id": 17,
"iteration": 1587890174657,
"links": [
{
"asDropdown": true,
"icon": "external link",
"tags": [],
"type": "dashboards"
}
],
"panels": [
{
"collapsed": false,
"gridPos": {
"h": 1,
"w": 24,
"x": 0,
"y": 0
},
"id": 67,
"panels": [],
"title": "数据库",
"type": "row"
},
{
"cacheTimeout": null,
"colorBackground": false,
"colorValue": true,
"colors": [
"rgba(245, 54, 54, 0.9)",
"rgba(237, 129, 40, 0.89)",
"rgba(50, 172, 45, 0.97)"
],
"datasource": "Prometheus",
"decimals": null,
"editable": true,
"error": false,
"format": "none",
"gauge": {
"maxValue": 100,
"minValue": 0,
"show": false,
"thresholdLabels": false,
"thresholdMarkers": true
},
"gridPos": {
"h": 3,
"w": 3,
"x": 0,
"y": 1
},
"height": "125px",
"id": 12,
"interval": "$interval",
"links": [],
"mappingType": 1,
"mappingTypes": [
{
"name": "value to text",
"value": 1
},
{
"name": "range to text",
"value": 2
}
],
"maxDataPoints": 100,
"nullPointMode": "connected",
"nullText": null,
"options": {},
"postfix": "",
"postfixFontSize": "80%",
"prefix": "",
"prefixFontSize": "80%",
"rangeMaps": [
{
"from": "null",
"text": "N/A",
"to": "null"
}
],
"sparkline": {
"fillColor": "rgba(31, 118, 189, 0.18)",
"full": false,
"lineColor": "rgb(31, 120, 193)",
"show": false
},
"tableColumn": "",
"targets": [
{
"calculatedInterval": "10m",
"datasourceErrors": {},
"errors": {},
"expr": "oracledb_up{instance=\"$host\"}",
"format": "time_series",
"interval": "5m",
"intervalFactor": 1,
"legendFormat": "",
"metric": "",
"refId": "A",
"step": 300
}
],
"thresholds": "0,1",
"title": "数据库状态",
"type": "singlestat",
"valueFontSize": "100%",
"valueMaps": [
{
"op": "=",
"text": "DEAD",
"value": "0"
},
{
"op": "=",
"text": "ALIVE",
"value": "1"
}
],
"valueName": "current"
},
{
"cacheTimeout": null,
"colorBackground": false,
"colorValue": false,
"colors": [
"#299c46",
"rgba(237, 129, 40, 0.89)",
"#d44a3a"
],
"datasource": "Prometheus",
"format": "none",
"gauge": {
"maxValue": 1000,
"minValue": 0,
"show": false,
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参考文献
https://www.ctolib.com/docs/sfile/prometheus-book/quickstart/why-monitor.html
https://www.ibm.com/developerworks/cn/cloud/library/cl-lo-prometheus-getting-started-and-practice/index.html
https://blog.51cto.com/youerning/2050543?from=timeline
https://blog.csdn.net/qq_42606051/article/details/82625163
https://prometheus.io/docs/introduction/faq/