Windows监控：基于Prometheus+Grafana监控CPU、内存、磁盘、网络、GPU信息
2024-05-14 06:30:39
目录
1. 系统环境准备
windows_exporter-0.13.0-amd64
Collectors 指标
nvidia_smi_exporter
nvidia-smi.exe查看GPU信息
nvidia-smi 输出信息解释
prometheus-2.19.2.windows-amd64
grafana-7.1.5.windows-amd64
2. 安装wmi-exporter
3. 安装nvidia_smi_exporter
构建
运行
访问：localhost:9101/metrics
等价Command
Prometheus 配置
4. 安装prometheus
prometheus配置
prometheus启动
访问prometheus
5. 安装Grafana
启动Grafana
Grafana配置数据源
Grafana选择监控仪表盘
6. 自动化启动脚本
1. 系统环境准备
windows_exporter-0.13.0-amd64
下载地址：https://github.com/martinlindhe/wmi_exporter/releases
A Prometheus exporter for Windows machines. 可以帮助收集windows上的CPU、内存、磁盘、网络
Collectors 指标
| Name | Description | Enabled by default |
|---|---|---|
| ad | Active Directory Domain Services | |
| adfs | Active Directory Federation Services | |
| cpu | CPU usage | ✓ |
| cs | "Computer System" metrics (system properties, num cpus/total memory) | ✓ |
| container | Container metrics | |
| dhcp | DHCP Server | |
| dns | DNS Server | |
| exchange | Exchange metrics | |
| fsrmquota | Microsoft File Server Resource Manager (FSRM) Quotas collector | |
| hyperv | Hyper-V hosts | |
| iis | IIS sites and applications | |
| logical_disk | Logical disks, disk I/O | ✓ |
| logon | User logon sessions | |
| memory | Memory usage metrics | |
| msmq | MSMQ queues | |
| mssql | SQL Server Performance Objects metrics | |
| netframework_clrexceptions | .NET Framework CLR Exceptions | |
| netframework_clrinterop | .NET Framework Interop Metrics | |
| netframework_clrjit | .NET Framework JIT metrics | |
| netframework_clrloading | .NET Framework CLR Loading metrics | |
| netframework_clrlocksandthreads | .NET Framework locks and metrics threads | |
| netframework_clrmemory | .NET Framework Memory metrics | |
| netframework_clrremoting | .NET Framework Remoting metrics | |
| netframework_clrsecurity | .NET Framework Security Check metrics | |
| net | Network interface I/O | ✓ |
| os | OS metrics (memory, processes, users) | ✓ |
| process | Per-process metrics | |
| remote_fx | RemoteFX protocol (RDP) metrics | |
| service | Service state metrics | ✓ |
| system | System calls | ✓ |
| tcp | TCP connections | |
| thermalzone | Thermal information | |
| terminal_services | Terminal services (RDS) | |
| textfile | Read prometheus metrics from a text file | ✓ |
| vmware | Performance counters installed by the Vmware Guest agent |
有关报指标，配置设置和使用示例的更多信息，请参见每个收集器上的链接文档。
nvidia_smi_exporter
下载地址：https://github.com/zhebrak/nvidia_smi_exporter
他是用于Prometheus的一个nvidia-smi metrics exporter ，可以帮助手机windows中的GPU信息，相当于执行了如下命令
nvidia-smi --query-gpu=name,index,temperature.gpu,utilization.gpu,utilization.memory,memory.total,memory.free,memory.used --format=csv,noheader,nounits
nvidia-smi.exe查看GPU信息
（1）打开cmd窗口（win+R，再输入cmd）
（2）进入C:\Program Files\NVIDIA Corporation\NVSMI中，执行nvidia-smi.exe
C:\Users\Administrator
λ cd C:\Program Files\NVIDIA Corporation\NVSMIC:\Program Files\NVIDIA Corporation\NVSMI
λ nvidia-smi.exe -l
Fri Aug 28 10:58:21 2020
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 446.14 Driver Version: 446.14 CUDA Version: 11.0 |
|-------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|===============================+======================+======================|
| 0 GeForce GTX 106... WDDM | 00000000:01:00.0 On | N/A |
| 27% 36C P8 10W / 120W | 1079MiB / 6144MiB | 2% Default |
+-------------------------------+----------------------+----------------------++-----------------------------------------------------------------------------+
| Processes: |
| GPU PID Type Process name GPU Memory |
| Usage |
|=============================================================================|
| 0 680 C+G ...lPanel\SystemSettings.exe N/A |
| 0 1388 C+G ...U-2019.1.3\bin\idea64.exe N/A |
| 0 1704 C+G ...w5n1h2txyewy\SearchUI.exe N/A |
| 0 2328 C+G ...gram\WeChat\WeChatApp.exe N/A |
| 0 3220 C+G ...sk\baidunetdiskrender.exe N/A |
| 0 5296 C+G ...y\ShellExperienceHost.exe N/A |
| 0 5940 C+G ...me\Application\chrome.exe N/A |
| 0 6976 C+G ...b3d8bbwe\WinStore.App.exe N/A |
| 0 8636 C+G ...ekyb3d8bbwe\YourPhone.exe N/A |
| 0 8664 C+G ...es.TextInput.InputApp.exe N/A |
| 0 9880 C+G ...kyb3d8bbwe\Calculator.exe N/A |
| 0 11552 C+G ...2701\Applet\WeChatApp.exe N/A |
| 0 11560 C+G ...1055.127\DesktopMgr64.exe N/A |
| 0 11864 C+G ...gram\WeChat\wechatweb.exe N/A |
| 0 12840 C+G Insufficient Permissions N/A |
| 0 13792 C+G C:\Windows\explorer.exe N/A |
| 0 16004 C+G ...typora\program\Typora.exe N/A |
+-----------------------------------------------------------------------------+nvidia-smi 输出信息解释
表格中会显示显卡的一些信息，第一行是版本信息，第二行是标题栏，第三行就是具体的显卡信息了，如果有多个显卡，会有多行，每一行的信息值对应标题栏对应位置的信息。
GPU：编号，0
Name：显卡名，NVS 4200M
TCC/WDDM：WDDM
Fan：风扇转速，在0到100%之间变动。N/A，表示没转
Temp：显卡温度，这里是66摄氏度
Perf：性能状态，congP0-P12，P0性能最大，P12最小，这里是P0
Pwr：能耗，Usage是使用量，Cap是总量
BusId：涉及GPU总线
Disp.A：表示GPU的显示是否已经初始化
Memory-Usage：显存使用率，这里才用很少，5%不到
CPU-Util：GPU利用率
Compute M：计算模式
需要注意的一点是显存占用率和GPU占用率是两个不一样的东西，类似于内存和CPU，两个指标的占用率不一定是互相对应的。
prometheus-2.19.2.windows-amd64
下载地址：https://prometheus.io/download/
选择windows 版本即可
grafana-7.1.5.windows-amd64
下载地址：https://grafana.com/grafana/download
选择windows 版本即可
2. 安装wmi-exporter
- 下载地址：https://github.com/martinlindhe/wmi_exporter/releases选择最新msi文件下载安装即可。
- 完成安装后会自动创建一个开机自启的服务，通过服务(services.msc)判断是否有有windows_exporter
- 通过访问http://ip+默认端口9182（如：http://localhost:9182） 出现下图，即代表安装采集数据成功。
3. 安装nvidia_smi_exporter
依赖于go的编译环境
go的下载：https://golang.google.cn/dl/
构建
> go build -v nvidia_smi_exporter
会自动生成一个nvidia_smi_exporter.exe文件
运行
> ./nvidia_smi_exporter [<port>]
Default port is 9101
访问：localhost:9101/metrics
temperature_gpu{gpu="TITAN X (Pascal)[0]"} 41
utilization_gpu{gpu="TITAN X (Pascal)[0]"} 0
utilization_memory{gpu="TITAN X (Pascal)[0]"} 0
memory_total{gpu="TITAN X (Pascal)[0]"} 12189
memory_free{gpu="TITAN X (Pascal)[0]"} 12189
memory_used{gpu="TITAN X (Pascal)[0]"} 0
temperature_gpu{gpu="TITAN X (Pascal)[1]"} 78
utilization_gpu{gpu="TITAN X (Pascal)[1]"} 95
utilization_memory{gpu="TITAN X (Pascal)[1]"} 59
memory_total{gpu="TITAN X (Pascal)[1]"} 12189
memory_free{gpu="TITAN X (Pascal)[1]"} 1738
memory_used{gpu="TITAN X (Pascal)[1]"} 10451
temperature_gpu{gpu="TITAN X (Pascal)[2]"} 83
utilization_gpu{gpu="TITAN X (Pascal)[2]"} 99
utilization_memory{gpu="TITAN X (Pascal)[2]"} 82
memory_total{gpu="TITAN X (Pascal)[2]"} 12189
memory_free{gpu="TITAN X (Pascal)[2]"} 190
memory_used{gpu="TITAN X (Pascal)[2]"} 11999
temperature_gpu{gpu="TITAN X (Pascal)[3]"} 84
utilization_gpu{gpu="TITAN X (Pascal)[3]"} 97
utilization_memory{gpu="TITAN X (Pascal)[3]"} 76
memory_total{gpu="TITAN X (Pascal)[3]"} 12189
memory_free{gpu="TITAN X (Pascal)[3]"} 536
memory_used{gpu="TITAN X (Pascal)[3]"} 11653
等价Command
nvidia-smi --query-gpu=name,index,temperature.gpu,utilization.gpu,utilization.memory,memory.total,memory.free,memory.used --format=csv,noheader,nounits
Prometheus 配置
- job_name: "gpu_exporter"static_configs:- targets: ['localhost:9101']4. 安装prometheus
- 下载地址：https://prometheus.io/download/
- 选择windows 版本即可
prometheus配置
下载解压后，修改配置文件，修改新增windows_exporter、nvidia_smi_exporter数据采集器配置：
# my global config
global:scrape_interval: 15s # Set the scrape interval to every 15 seconds. Default is every 1 minute.evaluation_interval: 15s # Evaluate rules every 15 seconds. The default is every 1 minute.# scrape_timeout is set to the global default (10s).# Alertmanager configuration
alerting:alertmanagers:- static_configs:- targets:# - alertmanager:9093# Load rules once and periodically evaluate them according to the global 'evaluation_interval'.
rule_files:# - "first_rules.yml"# - "second_rules.yml"# A scrape configuration containing exactly one endpoint to scrape:
# Here it's Prometheus itself.
scrape_configs:# The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.- job_name: 'Win-162'# metrics_path defaults to '/metrics'# scheme defaults to 'http'.static_configs:- targets: ['10.0.50.162:9182']# The job name is added as a label `job=<job_name>` to any timeseries scraped from this config.- job_name: 'Win-162-GPU'# metrics_path defaults to '/metrics'# scheme defaults to 'http'.static_configs:- targets: ['10.0.50.162:9101']prometheus启动
启动，cmd进入安装目录（& – -> 后台运行）
prometheus.exe --config.file=prometheus.yml --web.listen-address=:9090 &
访问prometheus
访问 http://ip:9090 ,（如：http://localhost:9090）出现如下界面即为prometheus安装成功、数据采集器验证成功 （PS: up为成功，down 为不成功。）
5. 安装Grafana
- 下载地址：https://grafana.com/grafana/download
- 选择windows 版本即可
启动Grafana
解压完成，进入bin目录启动grafana-server.exe 打开浏览器访问 http://ip:3000,（如：http://localhost:3000） 用户名/密码 admin/admin
Grafana配置数据源
Configuration -- Add data source --- Prometheus ， 输入名称，prometheus的访问url ，点击保存测试，验证是否成功
Grafana选择监控仪表盘
访问地址：https://grafana.com/dashboards --- serch框输入windows ---- 选择心仪模板 (注意模板所支持的数据源为prometheus) ----- 进行 ID 或者JOSN文件两种方式导入。
推荐使用ID
仪表盘模板推荐
模板ID: 10467
-- Windows的Prometheus监控看板展示，增加了资源汇总展示，优化了明细展示。更新支持windows_exporter 0.13.0。
模板导入成功即可看到监控数据
但是他没有GPU信息，我们通过添加panel来显示GPU的温度和使用率，改造后的仪表盘JOSN文件
{"annotations": {"list": [{"builtIn": 1,"datasource": "-- Grafana --","enable": true,"hide": true,"iconColor": "rgba(0, 211, 255, 1)","name": "Annotations & Alerts","type": "dashboard"}]},"description": "Windows的Prometheus监控看板展示，增加了资源汇总展示，优化了明细展示。更新支持windows_exporter 0.13.0。同时支持nvidia_smi_exporter的GPU温度和使用率展示","editable": true,"gnetId": 10467,"graphTooltip": 1,"id": 1,"iteration": 1598863585509,"links": [{"asDropdown": true,"icon": "external link","tags": [],"targetBlank": true,"type": "dashboards"}],"panels": [{"collapsed": false,"datasource": "Prometheus","gridPos": {"h": 1,"w": 24,"x": 0,"y": 0},"id": 41,"panels": [],"title": "资源总览（关联JOB项）当前选中主机：【$show_hostname】实例：$instance","type": "row"},{"columns": [],"datasource": "Prometheus","fieldConfig": {"defaults": {"custom": {}},"overrides": []},"fontSize": "80%","gridPos": {"h": 6,"w": 24,"x": 0,"y": 1},"id": 45,"pageSize": null,"showHeader": true,"sort": {"col": 0,"desc": true},"styles": [{"alias": "操作系统","align": "auto","colorMode": null,"colors": ["rgba(245, 54, 54, 0.9)","rgba(237, 129, 40, 0.89)","rgba(50, 172, 45, 0.97)"],"dateFormat": "YYYY-MM-DD HH:mm:ss","decimals": 2,"mappingType": 1,"pattern": "product","preserveFormat": false,"sanitize": false,"thresholds": [],"type": "string","unit": "short","valueMaps": []},{"alias": "主机名","align": "auto","colorMode": null,"colors": ["rgba(245, 54, 54, 0.9)","rgba(237, 129, 40, 0.89)","rgba(50, 172, 45, 0.97)"],"dateFormat": "YYYY-MM-DD HH:mm:ss","decimals": 2,"link": false,"linkTooltip": "","linkUrl": "","mappingType": 1,"pattern": "hostname","preserveFormat": false,"thresholds": [],"type": "string","unit": "short"},{"alias": "instance(连接到明细)","align": "auto","colorMode": null,"colors": ["rgba(245, 54, 54, 0.9)","rgba(237, 129, 40, 0.89)","rgba(50, 172, 45, 0.97)"],"dateFormat": "YYYY-MM-DD HH:mm:ss","decimals": 2,"link": true,"linkTargetBlank": false,"linkTooltip": "${__cell_4}","linkUrl": "/d/Kdh0OoSGz/?var-job=${__cell_5}&var-hostname=All&var-instance=${__cell_4}","mappingType": 1,"pattern": "instance","thresholds": [],"type": "string","unit": "short"},{"alias": "CPU核数","align": "auto","colorMode": null,"colors": ["rgba(245, 54, 54, 0.9)","rgba(237, 129, 40, 0.89)","rgba(50, 172, 45, 0.97)"],"dateFormat": "YYYY-MM-DD HH:mm:ss","decimals": 2,"mappingType": 1,"pattern": "Value #B","thresholds": [],"type": "string","unit": "short"},{"alias": "总内存","align": "auto","colorMode": null,"colors": ["rgba(245, 54, 54, 0.9)","rgba(237, 129, 40, 0.89)","rgba(50, 172, 45, 0.97)"],"dateFormat": "YYYY-MM-DD HH:mm:ss","decimals": null,"mappingType": 1,"pattern": "Value #C","thresholds": [],"type": "number","unit": "bytes"},{"alias": "运行时间","align": "auto","colorMode": "cell","colors": ["rgba(245, 54, 54, 0.9)","rgba(237, 129, 40, 0.89)","rgba(50, 172, 45, 0.97)"],"dateFormat": "YYYY-MM-DD HH:mm:ss","decimals": null,"mappingType": 1,"pattern": "Value #D","thresholds": ["259200","432000"],"type": "number","unit": "s"},{"alias": "C盘使用率","align": "auto","colorMode": "cell","colors": ["rgba(50, 172, 45, 0.97)","rgba(237, 129, 40, 0.89)","rgba(245, 54, 54, 0.9)"],"dateFormat": "YYYY-MM-DD HH:mm:ss","decimals": 2,"mappingType": 1,"pattern": "Value #E","thresholds": ["60","80"],"type": "number","unit": "percentunit"},{"alias": "使用最多分区%","align": "auto","colorMode": "cell","colors": ["rgba(50, 172, 45, 0.97)","rgba(237, 129, 40, 0.89)","rgba(245, 54, 54, 0.9)"],"dateFormat": "YYYY-MM-DD HH:mm:ss","decimals": 2,"mappingType": 1,"pattern": "Value #F","thresholds": ["60","80"],"type": "number","unit": "percentunit"},{"alias": "进程数","align": "auto","colorMode": null,"colors": ["rgba(245, 54, 54, 0.9)","rgba(237, 129, 40, 0.89)","rgba(50, 172, 45, 0.97)"],"dateFormat": "YYYY-MM-DD HH:mm:ss","decimals": 2,"link": false,"mappingType": 1,"pattern": "Value #G","thresholds": [],"type": "string","unit": "short"},{"alias": "运行服务","align": "auto","colorMode": null,"colors": ["rgba(245, 54, 54, 0.9)","rgba(237, 129, 40, 0.89)","rgba(50, 172, 45, 0.97)"],"dateFormat": "YYYY-MM-DD HH:mm:ss","decimals": 2,"mappingType": 1,"pattern": "Value #H","thresholds": [],"type": "string","unit": "short"},{"alias": "CPU使用率","align": "auto","colorMode": "cell","colors": ["rgba(50, 172, 45, 0.97)","rgba(237, 129, 40, 0.89)","rgba(245, 54, 54, 0.9)"],"dateFormat": "YYYY-MM-DD HH:mm:ss","decimals": 2,"mappingType": 1,"pattern": "Value #I","thresholds": ["50","70"],"type": "number","unit": "percent"},{"alias": "内存使用率","align": "auto","colorMode": "cell","colors": ["rgba(50, 172, 45, 0.97)","rgba(237, 129, 40, 0.89)","rgba(245, 54, 54, 0.9)"],"dateFormat": "YYYY-MM-DD HH:mm:ss","decimals": 2,"mappingType": 1,"pattern": "Value #J","thresholds": ["60","80"],"type": "number","unit": "percent"},{"alias": "CPU频率","align": "auto","colorMode": null,"colors": ["rgba(245, 54, 54, 0.9)","rgba(237, 129, 40, 0.89)","rgba(50, 172, 45, 0.97)"],"dateFormat": "YYYY-MM-DD HH:mm:ss","decimals": 2,"mappingType": 1,"pattern": "Value #K","thresholds": [],"type": "number","unit": "rothz"},{"alias": "","align": "right","colorMode": null,"colors": ["rgba(245, 54, 54, 0.9)","rgba(237, 129, 40, 0.89)","rgba(50, 172, 45, 0.97)"],"decimals": 2,"pattern": "/.*/","thresholds": [],"type": "hidden","unit": "short"}],"targets": [{"expr": "windows_os_info{job=~\"$job\"} * on(instance) group_right(product) windows_cs_hostname","format": "table","instant": true,"interval": "","legendFormat": "","refId": "A"},{"expr": "time() - windows_system_system_up_time{job=~\"$job\"}","format": "table","instant": true,"interval": "","legendFormat": "","refId": "D"},{"expr": "windows_cs_logical_processors{job=~\"$job\"} - 0","format": "table","instant": true,"interval": "","legendFormat": "","refId": "B"},{"expr": "avg by (instance) (windows_cpu_core_frequency_mhz{job=~\"$job\"})","format": "table","instant": true,"interval": "","legendFormat": "","refId": "K"},{"expr": "100 - (avg by (instance) (irate(windows_cpu_time_total{job=~\"$job\",mode=\"idle\"}[2m])) * 100)","format": "table","instant": true,"interval": "","legendFormat": "CPU使用率","refId": "I"},{"expr": "windows_cs_physical_memory_bytes{job=~\"$job\"} - 0","format": "table","instant": true,"interval": "","legendFormat": "","refId": "C"},{"expr": "100 - 100 * windows_os_physical_memory_free_bytes{job=~\"$job\"} / windows_cs_physical_memory_bytes{job=~\"$job\"}","format": "table","instant": true,"interval": "","legendFormat": "内存使用率","refId": "J"},{"expr": "1 - (windows_logical_disk_free_bytes{job=~\"$job\",volume=~\"C:\"}/windows_logical_disk_size_bytes{job=~\"$job\",volume=~\"C:\"})","format": "table","instant": true,"interval": "","legendFormat": "","refId": "E"},{"expr": "max by (instance) (1-windows_logical_disk_free_bytes/windows_logical_disk_size_bytes)","format": "table","instant": true,"interval": "","legendFormat": "","refId": "F"},{"expr": "windows_os_processes{job=~\"$job\"}","format": "table","instant": true,"interval": "","legendFormat": "","refId": "G"},{"expr": "sum by (instance) (windows_service_state{job=~\"$job\",state=~\"running\"})","format": "table","instant": true,"interval": "","legendFormat": "","refId": "H"}],"timeFrom": null,"timeShift": null,"title": "$job：服务器资源总览","transform": "table","type": "table-old"},{"aliasColors": {},"bars": false,"dashLength": 10,"dashes": false,"datasource": "Prometheus","decimals": 1,"fieldConfig": {"defaults": {"custom": {}},"overrides": []},"fill": 1,"fillGradient": 0,"gridPos": {"h": 6,"w": 8,"x": 0,"y": 7},"hiddenSeries": false,"id": 47,"legend": {"alignAsTable": true,"avg": true,"current": true,"max": true,"min": false,"rightSide": true,"show": false,"sort": "current","sortDesc": false,"total": false,"values": true},"lines": true,"linewidth": 1,"links": [],"nullPointMode": "null","paceLength": 10,"percentage": false,"pluginVersion": "7.1.5","pointradius": 5,"points": false,"renderer": "flot","seriesOverrides": [],"spaceLength": 10,"stack": false,"steppedLine": false,"targets": [{"expr": "100 - (avg by (instance) (irate(windows_cpu_time_total{job=~\"$job\",mode=\"idle\"}[2m])) * 100)","hide": false,"interval": "","intervalFactor": 1,"legendFormat": "{{instance}}","refId": "B"}],"thresholds": [],"timeFrom": null,"timeRegions": [],"timeShift": null,"title": "各主机CPU使用率","tooltip": {"shared": true,"sort": 2,"value_type": "cumulative"},"type": "graph","xaxis": {"buckets": null,"mode": "time","name": null,"show": true,"values": []},"yaxes": [{"format": "percent","label": null,"logBase": 1,"max": null,"min": "0","show": true},{"format": "short","label": null,"logBase": 1,"max": null,"min": null,"show": false}],"yaxis": {"align": false,"alignLevel": null}},{"aliasColors": {},"bars": false,"dashLength": 10,"dashes": false,"datasource": "Prometheus","decimals": 1,"fieldConfig": {"defaults": {"custom": {}},"overrides": []},"fill": 1,"fillGradient": 0,"gridPos": {"h": 6,"w": 8,"x": 8,"y": 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["Prometheus","windows_exporter"],"templating": {"list": [{"allValue": null,"current": {"selected": false,"text": "Win-225","value": "Win-225"},"datasource": "Prometheus","definition": "label_values(windows_cs_hostname, job)","hide": 0,"includeAll": false,"label": "JOB","multi": false,"name": "job","options": [],"query": "label_values(windows_cs_hostname, job)","refresh": 1,"regex": "","skipUrlSync": false,"sort": 1,"tagValuesQuery": "","tags": [],"tagsQuery": "","type": "query","useTags": false},{"allValue": null,"current": {"selected": false,"text": "All","value": "$__all"},"datasource": "Prometheus","definition": "label_values(windows_cs_hostname{job=~\"$job\"}, hostname)","hide": 0,"includeAll": true,"label": "主机名","multi": false,"name": "hostname","options": [],"query": "label_values(windows_cs_hostname{job=~\"$job\"}, hostname)","refresh": 1,"regex": "","skipUrlSync": false,"sort": 5,"tagValuesQuery": "","tags": [],"tagsQuery": "","type": "query","useTags": false},{"allValue": null,"current": {"selected": false,"text": "10.0.50.225:9182","value": "10.0.50.225:9182"},"datasource": "Prometheus","definition": "label_values(windows_cs_hostname{job=~\"$job\",hostname=~\"$hostname\"}, instance)","hide": 0,"includeAll": false,"label": "instance","multi": false,"name": "instance","options": [],"query": "label_values(windows_cs_hostname{job=~\"$job\",hostname=~\"$hostname\"}, instance)","refresh": 1,"regex": "","skipUrlSync": false,"sort": 5,"tagValuesQuery": "","tags": [],"tagsQuery": "","type": "query","useTags": false},{"allValue": null,"current": {"selected": false,"text": "SKY-20190610LFO","value": "SKY-20190610LFO"},"datasource": "Prometheus","definition": "label_values(windows_cs_hostname{job=~\"$job\",instance=~\"$instance\"}, hostname)","hide": 2,"includeAll": false,"label": "展示使用的主机名","multi": false,"name": "show_hostname","options": [],"query": "label_values(windows_cs_hostname{job=~\"$job\",instance=~\"$instance\"}, hostname)","refresh": 1,"regex": "","skipUrlSync": false,"sort": 0,"tagValuesQuery": "","tags": [],"tagsQuery": "","type": "query","useTags": false}]},"time": {"from": "now-3h","to": "now"},"timepicker": {"refresh_intervals": ["10s","30s","1m","5m","15m","30m","1h","2h","1d"],"time_options": ["5m","15m","1h","6h","12h","24h","2d","7d","30d"]},"timezone": "","title": "Windows Overriew","uid": "Kdh0OoSGz","version": 2
}6. 自动化启动脚本
@echo off
echo.
echo Windows指标采集[开始准备]
echo.echo CPU\Mem\Disk\Net采集[开始]
echo 依赖于windows_exporter-0.13.0-amd64服务，完成安装后会自动创建一个开机自启的服务，通过服务(services.msc)判断有windows_exporter
echo CPU\Mem\Disk\Net采集[开始]-- 可以通过 http://localhost:9182/metrics 访问echo GPU采集[开始]
start /d "D:\JT\java\prometheus\nvidia_smi_exporter" nvidia_smi_exporter.exe & ping localhost -n 2
::urlstatus=$(curl -X GET -i http://localhost:9101/metrics | grep 200)
::if [ "$urlstatus" != "" ];then
:: echo "GPU采集准备好了"
::fi
echo "GPU采集[完成]-- 可以通过 http://localhost:9101/metrics 访问"echo Prometheus[开始]
start /d "D:\JT\java\prometheus\prometheus-2.19.2.windows-amd64" prometheus.exe --config.file=prometheus.yml --web.listen-address=:9090 & ping localhost -n 30
echo Prometheus[完成] -- 可以通过 http://localhost:9090 访问echo Grafana[开始]
start /d "D:\JT\java\prometheus\grafana-7.1.5.windows-amd64\grafana-7.1.5\bin" grafana-server.exe & ping localhost -n 30
echo Grafana[完成] -- 可以通过 http://localhost:3000/d/Kdh0OoSGz/win-162?orgId=1 访问 【账号：admin 密码：123456】::执行完命令后关闭cmd命令窗口
::设置开机时运行
::bat脚本复制到此文件夹C:\ProgramData\Microsoft\Windows\Start Menu\Programs\StartUp
echo Windows指标采集[准备完毕]
::taskkill /f /im cmd.exe
::exit
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