promethues

前言：

最近項目中用到了promethues做服務告警，這裏就把自己探索過程中收集到的文檔整理出來，以及一些自己使用過程中的東西

簡介

Prometheus 是一套開源的系統監控報警框架。它啓發於 Google 的 borgmon 監控系統，由工作在 SoundCloud 的
google 前員工在 2012 年創建，作爲社區開源項目進行開發，並於 2015 年正式發佈。2016 年，Prometheus 正式加入
Cloud Native Computing Foundation，成爲受歡迎度僅次於 Kubernetes 的項目。

有人可能會疑惑：promethues和grafana結合豈不是可以把預警、日誌分析全做了？
其實官方強烈不推薦使用promethues和grafana做日誌分析的，官方解釋日誌分析還是交由專業的ELK去做，不建議使用promethues和grafana。

作爲新一代的監控框架，Prometheus 具有以下特點：

強大的多維度數據模型：
時間序列數據通過 metric 名和鍵值對來區分。
所有的 metrics 都可以設置任意的多維標籤。
數據模型更隨意，不需要刻意設置爲以點分隔的字符串。
可以對數據模型進行聚合，切割和切片操作。
支持雙精度浮點類型，標籤可以設爲全 unicode。
靈活而強大的查詢語句（PromQL）：在同一個查詢語句，可以對多個 metrics 進行乘法、加法、連接、取分數位等操作。
易於管理： Prometheus server 是一個單獨的二進制文件，可直接在本地工作，不依賴於分佈式存儲。
高效：平均每個採樣點僅佔 3.5 bytes，且一個 Prometheus server 可以處理數百萬的 metrics。
使用 pull 模式採集時間序列數據，這樣不僅有利於本機測試而且可以避免有問題的服務器推送壞的 metrics。
可以採用 push gateway 的方式把時間序列數據推送至 Prometheus server 端。
可以通過服務發現或者靜態配置去獲取監控的 targets。
有多種可視化圖形界面。
易於伸縮。

需要指出的是，由於數據採集可能會有丟失，所以 Prometheus 不適用對採集數據要 100% 準確的情形。但如果用於記錄時間序列數據，Prometheus 具有很大的查詢優勢，此外，Prometheus 適用於微服務的體系架構

組成&工作流

架構

如圖所示，即爲promethues的架構圖

概念介紹

Prometheus Server：

Prometheus Sever是Prometheus組件中的核心部分，負責實現對監控數據的獲取，存儲及查詢。Prometheus
Server可以通過靜態配置管理監控目標，也可以配合使用Service
Discovery的方式動態管理監控目標，並從這些監控目標中獲取數據。其次Prometheus
Sever需要對採集到的數據進行存儲，Prometheus
Server本身就是一個實時數據庫，將採集到的監控數據按照時間序列的方式存儲在本地磁盤當中。Prometheus
Server對外提供了自定義的PromQL，實現對數據的查詢以及分析。另外Prometheus
Server的聯邦集羣能力可以使其從其他的Prometheus Server實例中獲取數據。

Exporters：

Exporter將監控數據採集的端點通過HTTP服務的形式暴露給Prometheus Server，Prometheus
Server通過訪問該Exporter提供的Endpoint端點，即可以獲取到需要採集的監控數據。可以將Exporter分爲2類：

直接採集：

這一類Exporter直接內置了對Prometheus監控的支持，比如cAdvisor，Kubernetes，Etcd，Gokit等，都直接內置了用於向Prometheus暴露監控數據的端點。

間接採集：

原有監控目標並不直接支持Prometheus，因此需要通過Prometheus提供的Client
Library編寫該監控目標的監控採集程序。例如：Mysql Exporter，JMX Exporter，Consul Exporter等。

AlertManager：

在Prometheus Server中支持基於Prom QL創建告警規則，如果滿足Prom
QL定義的規則，則會產生一條告警。在AlertManager從 Prometheus server 端接收到
alerts後，會進行去除重複數據，分組，並路由到對收的接受方式，發出報警。常見的接收方式有：電子郵件，pagerduty，webhook
等。

PushGateway:

Prometheus數據採集基於Prometheus Server從Exporter pull數據，因此當網絡環境不允許Prometheus
Server和Exporter進行通信時，可以使用PushGateway來進行中轉。通過PushGateway將內部網絡的監控數據主動Push到Gateway中，Prometheus
Server採用針對Exporter同樣的方式，將監控數據從PushGateway pull到Prometheus Server。

Prometheus的工作流：

pull(拉取)

Prometheus
server定期從配置好的jobs或者exporters中拉取metrics(所有拉取規則都是在rules.yml配置文件中配置)，或者接收來自Pushgateway發送過來的metrics，或者從其它的Prometheus
server中拉metrics。

存儲

Prometheus server在本地存儲收集到的metrics，並運行定義好的alerts.rules，記錄新的時間序列或者向Alert
manager推送警報。

預警

Alertmanager根據配置文件，對接收到的警報進行處理，發出告警。

展示

在圖形界面中，可視化採集數據。可以採用Grafana做最後的圖形展示。

安裝和配置

文中promethues相關下載鏈接(提前公示),點擊此處即可跳轉

包含以下:

prometheus

alertmanager

node_exporter

其他的官方提供的exporter(提前公示),點擊此處即可跳轉

一、oracle監控安裝

它是用來監控oracle數據庫的，可以和oracle安裝在同一個服務器，也可以不同，這裏建議還是不要裝在一臺服務器上，對數據庫服務器是有性能上的影響的。

1.1 首先需要下載以下安裝包：

oracledb_exporter.0.2.2.linux-amd64.tar.gz    ===>地址：https://prometheus.io/docs/instrumenting/exporters/

以下三個地址：====>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 安裝：

1.2.1 如果是centos系統可以直接安裝這三個oracle客戶端組件，安裝命令：

rpm -ivh 包全名

1.2.2 如果是Ubuntu系統，則需要轉換爲Ubuntu的安裝包，再進行安裝，轉換命令如下：

sudo apt-get install alien               #alien默認沒有安裝，所以首先要安裝它

sudo alien xxxx.rpm #將rpm轉換位deb，完成後會生成一個同名的xxxx.deb

sudo dpkg -i xxxx.deb #安裝

1.3 環境變量設置：

修改環境變量

vim /etc/profile

文件末尾追加這三個環境變量

export DATA_SOURCE_NAME=oracle_exporter/Wl4L7CDM5@//172.30.130.116:1521/orcl   #這裏填寫監控用的用戶名及密碼，需要注意的是，這個用戶必須具有dba權限。
export LD_LIBRARY_PATH=/usr/lib/oracle/18.5/client64/lib:/usr/lib/oracle/18.5/client64   #這裏是oracle客戶端安裝完後的位置，自行去'/usr/lib/oracle/'這個目錄下覈查目錄路徑是否正確，如果版本號不對，手動修改這個值
export ORACLE_HOME=/usr/lib/oracle/18.5/client64   #覈對目錄並檢查版本號

之後使環境變量生效即可

source /etc/profile

1.4 安裝oracledb_exporter

他不需要安裝，解壓即可使用

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安裝

它是用來監控各節點的狀態，需要安裝在各需要監控的服務器上，一個服務器安裝一個。下載的地址如下：

https://prometheus.io/docs/instrumenting/exporters/

在上述地址請求後的頁面中找到要下載的node_exporter，並下載。
下載後：

1. mkdir  -p  /server/deployment/
2. 將node_exporter-0.18.1.linux-amd64.tar.gz移至/server/deployment/
3. 解壓node_exporter-0.18.1.linux-amd64.tar.gz =====》命令： tar -zxvf node_exporter-0.18.1.linux-amd64.tar.gz
4. 進入到/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 &       #後臺啓動即可

他的默認監聽端口是9100，如果發現與本機的服務端口有所衝突，可以指定其監聽的端口。但是需要注意的是，修改完監聽端口後，一定要在 3.2.1 prometheus.yml配置 中修改你所指定的這個端口。
修改默認端口的命令(將下面的9100改爲你所要監聽的指定端口)：

nohup  /server/deployment/node_exporter-0.18.1.linux-amd64/node_exporter  --web.listen-address=":9100"  &

三、安裝promethues

他是用來彙總監控信息的中央控制器，並且會發送告警信息給alertmanager

3.1 下載prometheus-2.15.2.linux-amd64.tar.gz

 https://prometheus.io/download/

選擇自己需要的版本進行下載

3.2 解壓即可用，重要的是需要進行配置

注意:

這裏的格式一定不要錯亂，要保證嚴格的yml格式，比如最簡單的各種對齊，否則啓動會報錯

項目中有的機器會出現中文不兼容的問題，所以最好將我下文中的模板中中文註釋去除

3.2.1 prometheus.yml配置

global:
  scrape_interval:     15s   #全局的間隔請求時間
  evaluation_interval: 15s  #指的是計算rule的間隔
  scrape_timeout: 10s    #間隔請求超時時間，這個是不能大於scrape_interval的
  external_labels:
   monitor: 'codelab_monitor'

alerting:
 alertmanagers:       #這個是alertmanager的配置，用來最後發出告警信息的模塊，在哪安裝的他，就配置安裝的信息即可，他的默認端口號是9093
 - static_configs:
   - targets: ["localhost:9093"]

rule_files:
 - "/server/prometheus-2.18.0-rc.0.linux-amd64/rules.yml"    #prometheus的告警規則配置文件地址

scrape_configs:
  - job_name: 'prometheus'
    static_configs:
    - targets: ['localhost:9090']

  - job_name: 'node'    #各節點的配置信息，這裏配置的主要是node_exporter的監控信息，如果你沒有對他的默認端口進行修改，那麼就寫9100即可
    static_configs:
    - targets: ['{IP}:9100']  #爲了通用性，我將服務器ip換成了{IP}，使用時將其替換成真正的ip地址即可

  - job_name: 'nginx'
    scrape_interval: 5s   #在這裏配置這個請求間隔時間是會覆蓋掉global裏的全局間隔時間的
    static_configs:
    - targets: ['{IP}:9913']

  - job_name: 'oracle'
    scrape_interval: 10s
    static_configs:
    - targets: ['localhost:9161']    #這些端口號並不是隨意填寫的，他們都是各個監控器的監聽端口，這個是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文件夾下新建rules.yml,這個是告警規則，有的服務器不支持中文，有的支持，不支持的話翻譯成英文即可，當然，寫英文的更好，防止亂碼的出現。部署時，建議務必刪除下文中我的中文註釋，以防報錯

groups:
- name: hostStatsAlert
  rules:
  - alert: "memory-warning"     #內存告警規則，持續1分鐘大於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告警規則，使用率持續1分鐘大於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"    #磁盤空間告警規則，可用磁盤小於5G持續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"  #節點存活狀態告警規則，1就是正常，0就是掛了，如果持續15秒都是掛的狀態，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存活狀態告警規則，1就是正常，0就是掛了，如果持續15秒都是掛的狀態，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 啓動

nohup /server/prometheus-2.15.2.linux-amd64/prometheus --config.file=/server/prometheus-2.15.2.linux-amd64/prometheus.yml &

說明： 如果需要新增其他的監控，比如rabbit mq、redis等，需要注意的有三點：

1) 到[監控插件下載地址](https://prometheus.io/docs/instrumenting/exporters/ )   這個地址去下載相關的exporter，大部分都是開箱即用，解壓即可使用，當然也會有需要填寫一些附帶信息的。
2）接着需要修改prometheus.yml，新增一個job_name模塊即可。
3）接着需要修改rules.yml，新增相關的告警指標即可。具體的指標可以訪問prometheus提供的頁面http://172.16.52.37:9090/targets，（就是prometheus的默認提供服務的接口：9090，在那邊可以找到很多參數指標，可自行組合設置）
4）最後重啓prometheus即可，可以直接kill掉原來的，直接重啓即可。

四、安裝Alertmanager

alertmanager是告警模塊，他負責將prometheus的告警信息收集並統一發送出去，裏面可以直接配置釘釘的機器人接口地址，具體方法可以網上搜尋一下，我們是使用web.hook將告警信息發送到指定的web服務裏，將其進行一些處理後在發送給釘釘。

4.1 下載

https://prometheus.io/download/

在上述地址中可以找到alertmanager的下載。下載完後將其解壓，配置基本信息即可配合prometheus使用

4.2 配置

編輯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服務接收告警信息地址
        http_config:
          bearer_token: LhTIaDGXAu1yAeKiAWobgZDo0GMQZR6l    #設置這個token，增加相應的安全性，這個token是在header裏

inhibit_rules:
  - source_match:
      severity: 'critical'
    target_match:
      severity: 'warning'
    equal: ['alertname', 'dev', 'instance']

4.3 啓動

nohup ./alertmanager --config.file=/server/alertmanager-0.20.0.linux-amd64/alertmanager.yml &

五、安裝Grafana

5.1 下載

https://grafana.com/grafana/download

下載Grafana,解壓後直接進入bin目錄,執行下面的命令即可啓動，grafana最麻煩的地方在於配置監控信息

./grafana-server web

5.2 配置

默認端口3000，{部署的服務器ip}:3000 即可訪問頁面。默認的初始用戶名/密碼：admin/admin
第一次登陸會提示修改密碼。修改即可。
進入後，如下圖所示操作即可

5.2.1 配置數據源（prometheus）

保存即可

5.2.2 配置監控面板

導入模板

這裏有技巧，你可以自己寫，但是會很麻煩，費力不討好，自己寫一些模板裏沒有的特定的還是可以的，其他的還是建議直接導入模板
這裏有你想要的各類模板

https://grafana.com/grafana/dashboards?orderBy=name&direction=asc

這裏有已經調試過得兩個模板,新建兩個json文件，將他們的內容保存進去，文件見七、附件

保存完了之後

點擊這些監控面板即可，可以看到很多監控信息

六、總結

6.1 怎麼知道自己有沒有啓動成功prometheus？

答：

http://{prometheus部署的ip}:9090

直接訪問即可，如果部署成功，會有web頁面的

6.2 需要注意的地方：

6.2.1 防火牆要開幾個特殊的端口

比如這個機子上安裝的各類監控器的監聽端口：9100、9090等等，按需開啓，centos的開啓命令.
如果你沒有開啓，那麼會導致你的監控器無法訪問

firewall-cmd --zone=public --add-port=9090/tcp --permanent
systemctl restart firewalld.service

6.2.2 服務器時間

項目中有碰到過因服務器時間未同步導致的grafana無法獲取信息的問題，所以以上完成後，請檢查一下自己的服務器時間是否已經同步

七、附件

Oracledb監控-性能與表空間-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進行oracle數據庫監控，相對其他dashboard增加了tablespace的監控，可拓展設置爲表空間告警；\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": "數據庫",
      "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": [],
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服務器監控面板-1587890262488.json

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      "pointradius": 5,
      "points": false,
      "renderer": "flot",
      "seriesOverrides": [
        {
          "alias": "/,*_讀取$/",
          "transform": "negative-Y"
        }
      ],
      "spaceLength": 10,
      "stack": false,
      "steppedLine": false,
      "targets": [
        {
          "expr": "irate(node_disk_read_time_seconds_total{instance=~\"$node\"}[30m]) / irate(node_disk_reads_completed_total{instance=~\"$node\"}[30m])",
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          "interval": "",
          "intervalFactor": 1,
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          "step": 10
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      ],
      "thresholds": [],
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        },
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      ],
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    },
    {
      "aliasColors": {
        "192.168.200.241:9100_TCP_alloc": "semi-dark-blue",
        "TCP": "#6ED0E0"
      },
      "bars": false,
      "dashLength": 10,
      "dashes": false,
      "datasource": "Prometheus",
      "description": "Sockets_used - 已使用的所有協議套接字總量\n\nCurrEstab - 當前狀態爲 ESTABLISHED 或 CLOSE-WAIT 的 TCP 連接數\n\nTCP_alloc - 已分配（已建立、已申請到sk_buff）的TCP套接字數量\n\nTCP_tw - 等待關閉的TCP連接數\n\nUDP_inuse - 正在使用的 UDP 套接字數量",
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      "fillGradient": 0,
      "gridPos": {
        "h": 6,
        "w": 24,
        "x": 0,
        "y": 43
      },
      "height": "300",
      "id": 158,
      "interval": "",
      "legend": {
        "alignAsTable": true,
        "avg": true,
        "current": true,
        "hideEmpty": true,
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        "max": true,
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        "rightSide": false,
        "show": true,
        "sort": "current",
        "sortDesc": true,
        "total": false,
        "values": true
      },
      "lines": true,
      "linewidth": 2,
      "links": [],
      "nullPointMode": "null",
      "options": {
        "dataLinks": []
      },
      "paceLength": 10,
      "percentage": false,
      "pointradius": 5,
      "points": false,
      "renderer": "flot",
      "seriesOverrides": [
        {
          "alias": "/.*_Sockets_used/",
          "color": "#C4162A",
          "fill": 0
        }
      ],
      "spaceLength": 10,
      "stack": false,
      "steppedLine": false,
      "targets": [
        {
          "expr": "node_netstat_Tcp_CurrEstab{instance=~'$node'}",
          "format": "time_series",
          "hide": false,
          "instant": false,
          "interval": "",
          "intervalFactor": 1,
          "legendFormat": "{{instance}}_CurrEstab",
          "refId": "A",
          "step": 20
        },
        {
          "expr": "node_sockstat_TCP_tw{instance=~'$node'}",
          "format": "time_series",
          "intervalFactor": 1,
          "legendFormat": "{{instance}}_TCP_tw",
          "refId": "D"
        },
        {
          "expr": "node_sockstat_sockets_used{instance=~'$node'}",
          "format": "time_series",
          "intervalFactor": 1,
          "legendFormat": "{{instance}}_Sockets_used",
          "refId": "B"
        },
        {
          "expr": "node_sockstat_UDP_inuse{instance=~'$node'}",
          "format": "time_series",
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          "refId": "C"
        },
        {
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          "format": "time_series",
          "intervalFactor": 1,
          "legendFormat": "{{instance}}_TCP_alloc",
          "refId": "E"
        }
      ],
      "thresholds": [],
      "timeFrom": null,
      "timeRegions": [],
      "timeShift": null,
      "title": "網絡連接信息",
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      },
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      ],
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  ],
  "refresh": "",
  "schemaVersion": 18,
  "style": "dark",
  "tags": [
    "Prometheus",
    "node_exporter",
    "StarsL.cn"
  ],
  "templating": {
    "list": [
      {
        "allValue": null,
        "current": {
          "text": "node",
          "value": "node"
        },
        "datasource": "Prometheus",
        "definition": "label_values(node_uname_info, job)",
        "hide": 0,
        "includeAll": false,
        "label": "JOB",
        "multi": false,
        "name": "job",
        "options": [],
        "query": "label_values(node_uname_info, job)",
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        "regex": "",
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        "datasource": "Prometheus",
        "definition": "label_values(node_uname_info{job=~\"$job\"}, nodename)",
        "hide": 0,
        "includeAll": true,
        "label": "主機名",
        "multi": true,
        "name": "hostname",
        "options": [],
        "query": "label_values(node_uname_info{job=~\"$job\"}, nodename)",
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        "datasource": "Prometheus",
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        "hide": 0,
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        "label": "IP( 自動關聯主機名)",
        "multi": false,
        "multiFormat": "regex values",
        "name": "node",
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        "query": "label_values(node_uname_info{nodename=~\"$hostname\"},instance)",
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      },
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        },
        "datasource": "Prometheus",
        "definition": "",
        "hide": 2,
        "includeAll": false,
        "label": "",
        "multi": false,
        "name": "maxmount",
        "options": [],
        "query": "query_result(topk(1,sort_desc (max(node_filesystem_size_bytes{instance=~'$node',fstype=~\"ext4|xfs\"}) by (mountpoint))))",
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        "regex": "/.*\\\"(.*)\\\".*/",
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        "hide": 2,
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        "label": "環境",
        "multi": false,
        "multiFormat": "regex values",
        "name": "env",
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        "includeAll": false,
        "label": "名稱",
        "multi": true,
        "multiFormat": "regex values",
        "name": "name",
        "options": [],
        "query": "label_values(node_exporter_build_info{env=~'$env'},name)",
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      }
    ]
  },
  "time": {
    "from": "now-2d",
    "to": "now"
  },
  "timepicker": {
    "now": true,
    "refresh_intervals": [
      "5s",
      "10s",
      "30s",
      "1m",
      "5m",
      "15m",
      "30m",
      "1h",
      "2h",
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    ],
    "time_options": [
      "5m",
      "15m",
      "1h",
      "6h",
      "12h",
      "24h",
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    ]
  },
  "timezone": "browser",
  "title": "服務器監控面板",
  "uid": "9CWBz0bik1",
  "version": 7
}

參考文獻

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/

promethues監控體系