2018-06-19 21:45:17 +08:00
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# Metrics Server
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从 v1.8 开始,资源使用情况的度量(如容器的 CPU 和内存使用)可以通过 Metrics API 获取;前提是集群中要部署 Metrics Server,它从Kubelet 公开的Summary API采集指标信息,关于更多的背景介绍请参考如下文档:
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- Metrics Server[设计提案](https://github.com/kubernetes/community/blob/master/contributors/design-proposals/instrumentation/metrics-server.md)
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大致是说它符合k8s的监控架构设计,受heapster项目启发,并且比heapster优势在于:访问不需要apiserver的代理机制,提供认证和授权等;很多集群内组件依赖它(HPA,scheduler,kubectl top),因此它应该在集群中默认运行;部分k8s集群的安装工具已经默认集成了Metrics Server的安装,以下概述下它的安装:
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- 1.metric-server是扩展的apiserver,依赖于[kube-aggregator](https://github.com/kubernetes/kube-aggregator),因此需要在apiserver中开启相关参数。
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2018-06-23 22:50:27 +08:00
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- 2.需要在集群中运行deployment处理请求
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2018-06-19 21:45:17 +08:00
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2021-09-24 15:47:32 +08:00
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从kubeasz 0.1.0 开始,metrics-server已经默认集成安装,请查看`/etc/kubeasz/clusters/xxxx/config.yml`中的设置
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2018-06-19 21:45:17 +08:00
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2021-09-24 15:47:32 +08:00
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## 前提
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2018-06-19 21:45:17 +08:00
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- 1.设置apiserver相关[参数](../../roles/kube-master/templates/kube-apiserver.service.j2)
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``` bash
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... # 省略
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--requestheader-client-ca-file={{ ca_dir }}/ca.pem \
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--requestheader-allowed-names=aggregator \
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--requestheader-extra-headers-prefix=X-Remote-Extra- \
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--requestheader-group-headers=X-Remote-Group \
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--requestheader-username-headers=X-Remote-User \
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--proxy-client-cert-file={{ ca_dir }}/aggregator-proxy.pem \
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--proxy-client-key-file={{ ca_dir }}/aggregator-proxy-key.pem \
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--enable-aggregator-routing=true \
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```
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- 2.生成[aggregator proxy相关证书](../../roles/kube-master/tasks/main.yml)
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参考1:https://kubernetes.io/docs/tasks/access-kubernetes-api/configure-aggregation-layer/
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参考2:https://kubernetes.io/docs/tasks/access-kubernetes-api/setup-extension-api-server/
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2021-09-24 15:47:32 +08:00
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## 安装
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``` bash
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# 默认已经集成安装,假设集群名为xxxx
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ezctl setup xxxx all
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# 如果需要分步安装
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ezctl setup xxxx 07
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# 如果需要手动安装
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kubectl apply -f /etc/kubeasz/clusters/xxxx/yml/metrics-server.yaml
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```
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2018-06-19 21:45:17 +08:00
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## 验证
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- 查看生成的新api:v1beta1.metrics.k8s.io
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``` bash
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$ kubectl get apiservice|grep metrics
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v1beta1.metrics.k8s.io 1d
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```
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- 查看kubectl top命令(无需额外安装heapster)
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``` bash
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$ kubectl top node
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NAME CPU(cores) CPU% MEMORY(bytes) MEMORY%
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192.168.1.1 116m 2% 2342Mi 60%
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192.168.1.2 79m 1% 1824Mi 47%
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192.168.1.3 82m 2% 1897Mi 49%
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$ kubectl top pod --all-namespaces # 输出略
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```
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- 验证基于metrics-server实现的基础hpa自动缩放,请参考[hpa.md](hpa.md)
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