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docs: fix typo (#869)
Signed-off-by: jinvei <[email protected]>
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docs/benchmark.md

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## Benchmarks
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Three instances from ai-benchmark have been used to evaluate vGPU-device-plugin performance as follows
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Three instances from ai-benchmark have been used to evaluate vGPU-device-plugin performance as follows:
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| Test Environment | description |
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| ---------------- | :------------------------------------------------------: |
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To reproduce:
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1. install k8s-vGPU-schedulerand configure properly
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1. install k8s-vGPU-scheduler, and configure properly
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2. run benchmark job
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```

docs/dashboard.md

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# Abstract
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For the sake of simplicity, this article provides only one possible way to ultimately use prometheus to capture monitoring metrics as a data source and grafana to present monitoring information.
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For the sake of simplicity, this article provides only one possible way to ultimately use prometheus to capture monitoring metrics as a data source and grafana to present monitoring information.
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Many users feedback from creating issues that they do not know how to install and configure related components, resulting in failure to use related dashboard normally. The installation and configuration steps are described as follows, Hope you use it smoothly! Any feedback is welcome.
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Many users feedback from creating issues that they do not know how to install and configure related components, resulting in failure to use related dashboard normally. The installation and configuration steps are described as follows, Hope you use it smoothly! Any feedback is welcome.
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This article assumes that Kubernetes cluster and HAMi has been deployed successfully. The following components are installed in a kubernetes cluster. The components or software versions are as follows:
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This article assumes that Kubernetes cluster and HAMi has been deployed successfully. The following components are installed in a kubernetes cluster. The components or software versions are as follows:
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| components or software name | version | remark |
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| --------------------------- | ------------------- | ---------------- |
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## Deploy kube-prometheus stack
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**Note:**See the version compatibility matrix for kubernetes and kube-prometheus stack in:https://github.com/prometheus-operator/kube-prometheus?tab=readme-ov-file#compatibility
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**Note:** See the version compatibility matrix for kubernetes and kube-prometheus stack in:https://github.com/prometheus-operator/kube-prometheus?tab=readme-ov-file#compatibility
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```shell
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#Clone kube-prometheus code repository(using release-0.11 here)
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prometheus-k8s NodePort 10.233.38.113 <none> 9090:30090/TCP,8080:31273/TCP 19h
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```
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If ip address of controller node is 10.0.0.21, then grafana, prometheus, and alertmanager can be accessed using the following urls: http://10.0.0.21:30300 , http://10.0.0.21:30090 , and http://10.0.0.21:30093 , and the default user name and password for accessing grafana are admin
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If ip address of controller node is 10.0.0.21, then grafana, prometheus, and alertmanager can be accessed using the following urls: http://10.0.0.21:30300 , http://10.0.0.21:30090 , and http://10.0.0.21:30093 , and the default user name and password for accessing grafana are admin
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## Configure grafana
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### Create Datasource ALL
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Go to the "Configuration" -> "Data soutces" page in grafana and create a datasource named "ALL", and keep the value of HTTP.URL be same with the counterpart in default "prometheus" datasource.
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Go to the "Configuration" -> "Data soutces" page in grafana and create a datasource named "ALL", and keep the value of HTTP.URL be same with the counterpart in default "prometheus" datasource.
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### Import dashboard
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Go to the "Configuration" -> "Data soutces" page in grafana and import the dashboard from https://grafana.com/grafana/dashboards/22043-hami-vgpu-metrics-dashboard/ , and a dashboard page named "hami-vgpu-metrics-dashboard" will be created. 22043-hami-vgpu-metrics-dashboard is valid in grafana8.5.5 and grafana9.1.0, and it's grealty possible that this dashboard is vaild in grafana version later than 9.1.0. Now data of some panels in this dashboard page are missing, which requires you read the rest of the document.
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Go to the "Configuration" -> "Data soutces" page in grafana and import the dashboard from https://grafana.com/grafana/dashboards/22043-hami-vgpu-metrics-dashboard/ , and a dashboard page named "hami-vgpu-metrics-dashboard" will be created. 22043-hami-vgpu-metrics-dashboard is valid in grafana8.5.5 and grafana9.1.0, and it's grealty possible that this dashboard is vaild in grafana version later than 9.1.0. Now data of some panels in this dashboard page are missing, which requires you read the rest of the document.
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For versions earlier than grafana8.5.5, such as grafana7.5.17, please refer to:https://grafana.com/grafana/dashboards/21833-hami-vgpu-dashboard/
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For versions earlier than grafana8.5.5, such as grafana7.5.17, please refer to:https://grafana.com/grafana/dashboards/21833-hami-vgpu-dashboard/
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# Deploy dcgm-exporter
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gpu-pod-01 0/1 Completed 0 52s 10.233.81.70 controller01 <none> <none>
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```
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You can see the monitoring details in the dashboard. The contents are as follows:
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You can see the monitoring details in the dashboard. The contents are as follows:
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![hami-vgpu-metrics-dashboard](../imgs/hami-vgpu-metrics-dashboard.png)

docs/dashboard_cn.md

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# 说明
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为了阐述的简明性,本文只提供一种可行的办法,最终实现使用prometheus抓取监控指标并作为数据源、使用grafana来展示监控信息的目的。
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为了阐述的简明性,本文只提供一种可行的办法,最终实现使用prometheus抓取监控指标并作为数据源、使用grafana来展示监控信息的目的。
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很多使用者通过issue反馈不知如何安装与配置相关组件导致无法正常使用相关dashboard,现将安装与配置步骤叙述如下,希望大家使用顺利!如有问题欢迎创建issue反馈,如有不足欢迎补充!
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很多使用者通过issue反馈不知如何安装与配置相关组件导致无法正常使用相关dashboard,现将安装与配置步骤叙述如下,希望大家使用顺利!如有问题欢迎创建issue反馈,如有不足欢迎补充!
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本文假设读者已经部署好Kubernetes集群、HAMi。以下涉及到的相关组件都是在kubernetes集群内安装的,相关组件或软件版本信息如下:
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本文假设读者已经部署好Kubernetes集群、HAMi。以下涉及到的相关组件都是在kubernetes集群内安装的,相关组件或软件版本信息如下:
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| 组件或软件名称 | 版本 | 备注 |
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## 部署kube-prometheus stack
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**注:**kubernetes与kube-prometheus stack的版本兼容矩阵请查看 https://github.com/prometheus-operator/kube-prometheus?tab=readme-ov-file#compatibility ,请根据自己的kubernetes版本选择合适版本的kube-prometheus stack
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**注:** kubernetes与kube-prometheus stack的版本兼容矩阵请查看 https://github.com/prometheus-operator/kube-prometheus?tab=readme-ov-file#compatibility ,请根据自己的kubernetes版本选择合适版本的kube-prometheus stack
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```shell
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prometheus-k8s NodePort 10.233.38.113 <none> 9090:30090/TCP,8080:31273/TCP 19h
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```
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此时,假如控制节点的ip是10.0.0.21,则可以分别使用如下url访问grafana、prometheus与alertmanager:http://10.0.0.21:30300http://10.0.0.21:30090http://10.0.0.21:30093 ,其中访问grafana的默认用户名与密码都是admin
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此时,假如控制节点的ip是10.0.0.21,则可以分别使用如下url访问grafana、prometheus与alertmanager:http://10.0.0.21:30300http://10.0.0.21:30090http://10.0.0.21:30093 ,其中访问grafana的默认用户名与密码都是admin
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## 配置grafana
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### 创建数据源ALL
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访问”Configuration“->“Data soutces”页面,创建一个名为"ALL"的数据源,其中HTTP.URL的值保持跟默认创建的数据源“prometheus”中的一样即可为 “http://prometheus-k8s.monitoring.svc:9090” ,然后保存上述数据源“ALL”
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访问”Configuration“->“Data soutces”页面,创建一个名为"ALL"的数据源,其中HTTP.URL的值保持跟默认创建的数据源“prometheus”中的一样即可为 “http://prometheus-k8s.monitoring.svc:9090” ,然后保存上述数据源“ALL”
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### 导入HAMi默认的dashboard
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访问“Dashboards”->“Browse”页面,导入此dashboard:https://grafana.com/grafana/dashboards/22043-hami-vgpu-metrics-dashboard/ ,grafana中将创建一个名为“hami-vgpu-metrics-dashboard”的dashboard,22043这个编号对应的dashboard在grafana8.5.5与grafana9.1.0验证过,在grafana9.1.0之后应该也能用。此时此页面中有一些Panel如vGPUCorePercentage还没有数据,请继续看完此文档,执行完"部署dcgm-exporter"与“创建ServiceMonitor”中的步骤之后Panel数据将正常显示。
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访问“Dashboards”->“Browse”页面,导入此dashboard:https://grafana.com/grafana/dashboards/22043-hami-vgpu-metrics-dashboard/ ,grafana中将创建一个名为“hami-vgpu-metrics-dashboard”的dashboard,22043这个编号对应的dashboard在grafana8.5.5与grafana9.1.0验证过,在grafana9.1.0之后应该也能用。此时此页面中有一些Panel如vGPUCorePercentage还没有数据,请继续看完此文档,执行完"部署dcgm-exporter"与“创建ServiceMonitor”中的步骤之后Panel数据将正常显示。
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对于grafana8.5.5之前的版本如grafana7.5.17,请使用此dashboard:https://grafana.com/grafana/dashboards/21833-hami-vgpu-dashboard/
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对于grafana8.5.5之前的版本如grafana7.5.17,请使用此dashboard:https://grafana.com/grafana/dashboards/21833-hami-vgpu-dashboard/
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# 部署dcgm-exporter
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gpu-pod-01 0/1 Completed 0 52s 10.233.81.70 controller01 <none> <none>
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此时,应该可以dashboard中看到监控详情。内容大概如下
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此时,应该可以dashboard中看到监控详情。内容大概如下
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![hami-vgpu-metrics-dashboard](../imgs/hami-vgpu-metrics-dashboard.png)

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