Kubernetes 1.8 关于资源使用情况的 metrics,可以通过 Metrics API 获取到, Kubernetes 1.11 已经废弃 heapster。这里我们基于 Kubernetes 1.14.1 版本安装 Metrics Server。

首先,先说明下集群环境:

[root@node-01]# kubectl get nodes
NAME STATUS ROLES AGE VERSION
node-01 Ready master 2d1h v1.14.1
node-02 Ready master 2d1h v1.14.1
node-03 Ready master 2d1h v1.14.1
node-04 Ready <none> 2d1h v1.14.1
node-05 Ready <none> 2d1h v1.14.1
node-06 Ready <none> 2d1h v1.14.1

当整个集群部署完成后,kubectl top 命令不会返回任何内容,因为 Heapster 和 metrics-server 都没有安装,但是自 Kubernetes 1.11版本后 heapster已经被废弃了,取而代之的是更丰富的 metrics-server。

配置 /etc/kubernetes/manifests/kube-controller-manager.yaml

--horizontal-pod-autoscaler-use-rest-clients=true

kubedam 创建的集群,修改配置文件后会自动加载。如果手动创建的集群,需要重启kube-controller-manager服务。

准备部署 Metrics Server 的 yaml文件

[root@node-01]# git clone https://github.com/kubernetes-incubator/metrics-server

下载完成后还需要对 metrics-server/deploy/1.8+/resource-reader.yaml文件进行修改,需要修改的内容如下:

[root@node-01 1.8+]# cat resource-reader.yaml
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: system:metrics-server
rules:
- apiGroups:
- ""
resources:
- pods
- nodes
- namespaces # 增加此行
- nodes/stats
verbs:
- get
- list
- watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: system:metrics-server
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: system:metrics-server
subjects:
- kind: ServiceAccount
name: metrics-server
namespace: kube-system

修改 metrics-server/deploy/1.8+/metrics-server-deployment.yaml文件:

[root@node-01 1.8+]# cat metrics-server-deployment.yaml
---
apiVersion: v1
kind: ServiceAccount
metadata:
name: metrics-server
namespace: kube-system
---
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: metrics-server
namespace: kube-system
labels:
k8s-app: metrics-server
spec:
selector:
matchLabels:
k8s-app: metrics-server
template:
metadata:
name: metrics-server
labels:
k8s-app: metrics-server
spec:
serviceAccountName: metrics-server
volumes:
# mount in tmp so we can safely use from-scratch images and/or read-only containers
- name: tmp-dir
emptyDir: {}
containers:
- name: metrics-server
image: k8s.gcr.io/metrics-server-amd64:v0.3.2
command:
- /metrics-server
- --kubelet-insecure-tls
- --kubelet-preferred-address-types=InternalIP # 如果不配置此项,会报错找不到node
imagePullPolicy: Always
volumeMounts:
- name: tmp-dir
mountPath: /tmp

上面如果报错是因为 node-01 和 node-02 是一个独立的 Kubernetes 演示环境,只是修改了这两个节点系统的 /etc/hosts文件,而并没有内网的 DNS 服务器,所以 metrics-server 中不认识 node-01 和 node-02 的名字。

修改完成就可以正式部署了:

[root@node-01 1.8+]# kubectl apply -f .
clusterrole.rbac.authorization.k8s.io/system:aggregated-metrics-reader created
clusterrolebinding.rbac.authorization.k8s.io/metrics-server:system:auth-delegator created
rolebinding.rbac.authorization.k8s.io/metrics-server-auth-reader created
apiservice.apiregistration.k8s.io/v1beta1.metrics.k8s.io created
serviceaccount/metrics-server created
deployment.extensions/metrics-server created
service/metrics-server created
clusterrole.rbac.authorization.k8s.io/system:metrics-server created
clusterrolebinding.rbac.authorization.k8s.io/system:metrics-server created

Metrics Server 相关 pod 、service 默认部署在 kube-system的 NAMESPACE 下:

[root@node-01 1.8+]# kubectl get pods -n kube-system | grep metrics
metrics-server-5845cc8fd4-kkq6b 1/1 Running 0 18m [root@node-01 1.8+]# kubectl get svc -n kube-system | grep metrics
metrics-server ClusterIP 10.245.141.103 <none> 443/TCP 20m

部署完成后使用如下命令查看node相关指标,需要等30s左右的时间:

[root@node-01 1.8+]# kubectl get --raw "/apis/metrics.k8s.io/v1beta1/nodes"
{"kind":"NodeMetricsList","apiVersion":"metrics.k8s.io/v1beta1","metadata":{"selfLink":"/apis/metrics.k8s.io/v1beta1/nodes"},"items":[
{"metadata":{"name":"node-02","selfLink":"/apis/metrics.k8s.io/v1beta1/nodes/node-02","creationTimestamp":"2019-05-08T08:17:11Z"},"timestamp":"2019-05-08T08:17:01Z","window":"30s","usage":{"cpu":"221367011n","memory":"1914616Ki"}},
{"metadata":{"name":"node-03","selfLink":"/apis/metrics.k8s.io/v1beta1/nodes/node-03","creationTimestamp":"2019-05-08T08:17:11Z"},"timestamp":"2019-05-08T08:17:08Z","window":"30s","usage":{"cpu":"198021879n","memory":"1809160Ki"}},
{"metadata":{"name":"node-04","selfLink":"/apis/metrics.k8s.io/v1beta1/nodes/node-04","creationTimestamp":"2019-05-08T08:17:11Z"},"timestamp":"2019-05-08T08:17:03Z","window":"30s","usage":{"cpu":"55570780n","memory":"719012Ki"}},
{"metadata":{"name":"node-05","selfLink":"/apis/metrics.k8s.io/v1beta1/nodes/node-05","creationTimestamp":"2019-05-08T08:17:11Z"},"timestamp":"2019-05-08T08:17:01Z","window":"30s","usage":{"cpu":"60116633n","memory":"851180Ki"}},
{"metadata":{"name":"node-06","selfLink":"/apis/metrics.k8s.io/v1beta1/nodes/node-06","creationTimestamp":"2019-05-08T08:17:11Z"},"timestamp":"2019-05-08T08:16:59Z","window":"30s","usage":{"cpu":"51157291n","memory":"677532Ki"}},
{"metadata":{"name":"node-01","selfLink":"/apis/metrics.k8s.io/v1beta1/nodes/node-01","creationTimestamp":"2019-05-08T08:17:11Z"},"timestamp":"2019-05-08T08:17:02Z","window":"30s","usage":{"cpu":"263183209n","memory":"2460972Ki"}}]}

Metrics API

Metrics Server 从 Kubernetes 集群中每个 Node 上 kubelet 的 API 收集 metrics 数据。通过 Metrics API 可以获取Kubernetes 资源的 Metrics 指标,Metrics API 挂载/apis/metrics.k8s.io/下。 可以使用kubectl top命令访问 Metrics API,例如:

[root@node-01 ~]# kubectl top pods
NAME CPU(cores) MEMORY(bytes)
my-nginx-6785b88976-7rrll 0m 1Mi
nginx-deployment-6d6fdc59f7-pfcfj 1m 1Mi
nginx-deployment-6d6fdc59f7-vcclz 1m 1Mi
[root@node-01 ~]# kubectl top nodes
NAME CPU(cores) CPU% MEMORY(bytes) MEMORY%
node-01 276m 6% 2403Mi 31%
node-02 245m 6% 1868Mi 24%
node-03 206m 5% 1766Mi 22%
node-04 74m 1% 703Mi 9%
node-05 77m 1% 832Mi 10%
node-06 56m 1% 661Mi 8%

至此,Kubernetes 集群中的 Metrics Server 就配置完成了。但是在dashboard中看不到内存和CPU信息,而如果使用heapster则能看到。

所有yaml文件如下

# cat aggregated-metrics-reader.yaml
kind: ClusterRole
apiVersion: rbac.authorization.k8s.io/v1
metadata:
name: system:aggregated-metrics-reader
labels:
rbac.authorization.k8s.io/aggregate-to-view: "true"
rbac.authorization.k8s.io/aggregate-to-edit: "true"
rbac.authorization.k8s.io/aggregate-to-admin: "true"
rules:
- apiGroups: ["metrics.k8s.io"]
resources: ["pods"]
verbs: ["get", "list", "watch”] # cat auth-delegator.yaml
---
apiVersion: rbac.authorization.k8s.io/v1beta1
kind: ClusterRoleBinding
metadata:
name: metrics-server:system:auth-delegator
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: system:auth-delegator
subjects:
- kind: ServiceAccount
name: metrics-server
namespace: kube-system # cat auth-reader.yaml
---
apiVersion: rbac.authorization.k8s.io/v1beta1
kind: RoleBinding
metadata:
name: metrics-server-auth-reader
namespace: kube-system
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: Role
name: extension-apiserver-authentication-reader
subjects:
- kind: ServiceAccount
name: metrics-server
namespace: kube-system
————— # cat metrics-apiservice.yaml
---
apiVersion: apiregistration.k8s.io/v1beta1
kind: APIService
metadata:
name: v1beta1.metrics.k8s.io
spec:
service:
name: metrics-server
namespace: kube-system
group: metrics.k8s.io
version: v1beta1
insecureSkipTLSVerify: true
groupPriorityMinimum: 100
versionPriority: 100 # cat metrics-server-deployment.yaml
---
apiVersion: v1
kind: ServiceAccount
metadata:
name: metrics-server
namespace: kube-system
---
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
name: metrics-server
namespace: kube-system
labels:
k8s-app: metrics-server
spec:
selector:
matchLabels:
k8s-app: metrics-server
template:
metadata:
name: metrics-server
labels:
k8s-app: metrics-server
spec:
serviceAccountName: metrics-server
volumes:
# mount in tmp so we can safely use from-scratch images and/or read-only containers
- name: tmp-dir
emptyDir: {}
containers:
- name: metrics-server
image: k8s.gcr.io/metrics-server-amd64:v0.3.2
command:
- /metrics-server
- --kubelet-insecure-tls
- --kubelet-preferred-address-types=InternalIP
imagePullPolicy: Always
volumeMounts:
- name: tmp-dir
mountPath: /tmp # cat metrics-server-service.yaml
---
apiVersion: v1
kind: Service
metadata:
name: metrics-server
namespace: kube-system
labels:
kubernetes.io/name: "Metrics-server"
kubernetes.io/cluster-service: "true"
spec:
selector:
k8s-app: metrics-server
ports:
- port: 443
protocol: TCP
targetPort: 443 # cat resource-reader.yaml
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: system:metrics-server
rules:
- apiGroups:
- ""
resources:
- pods
- nodes
- namespaces # 增加此行
- nodes/stats
verbs:
- get
- list
- watch
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: system:metrics-server
roleRef:
apiGroup: rbac.authorization.k8s.io
kind: ClusterRole
name: system:metrics-server
subjects:
- kind: ServiceAccount
name: metrics-server
namespace: kube-system

kubernetes之配置Metrics Server的更多相关文章

  1. 启用k8s metrics server监控

    1.创建aggregator证书 方法一:直接使用二进制源码包安装 $ wget https://pkg.cfssl.org/R1.2/cfssl_linux-amd64 $ chmod +x cfs ...

  2. 在容器服务kubernetes上配置https

    当前容器服务Kubernetes集群支持多种应用访问的形式,最常见形式如SLB:Port,NodeIP:NodePort和域名访问等.但是Kubernetes集群默认不支持HTTPS访问,如果用户希望 ...

  3. kubeadm1.14.1 安装Metrics Server

    Metrics API 介绍Metrics-Server之前,必须要提一下Metrics API的概念 Metrics API相比于之前的监控采集方式(hepaster)是一种新的思路,官方希望核心指 ...

  4. k8s搭建监控:安装metrics server和dashboard

      安装metrics server 参考:https://github.com/kubernetes-sigs/metrics-server kubectl  create -f component ...

  5. K8S原来如此简单(五)Metrics Server与HPA

    什么是HPA https://kubernetes.io/zh/docs/tasks/run-application/horizontal-pod-autoscale/ 我们前面有通过kubectl ...

  6. Postgresql 简单配置 (ubuntu server 14.04.3)

    安装和配置 ubuntu server 已经自动安装了progresql,故安装步骤就省略 初始postgresql没有密码,不能使用,需要先设置密码,命令(从网上随意找的)如下: sudo su p ...

  7. 配置SQL Server去使用 Windows的 Large-Page/Huge-Page allocations

    配置SQL Server去使用 Windows的 Large-Page/Huge-Page  allocations 目录表->页表->物理内存页 看这篇文章之前可以先看一下下面这篇文章 ...

  8. 配置sql server 2000以允许远程访问 及 连接中的四个最常见错误

    地址:http://www.cnblogs.com/JoshuaDreaming/archive/2010/12/01/1893242.html 配置sql server 2000以允许远程访问适合故 ...

  9. 配置SQL Server 2008 R2 Reporting Services

    记录如何在本地配置SQL Server 2008 R2 Reporting Services,笔者环境为Windows 7 64位 + SQL Server 2008 R2 一.准备工作 其实准备工作 ...

随机推荐

  1. 【LeetCode】1399. 统计最大组的数目 Count Largest Group

    作者: 负雪明烛 id: fuxuemingzhu 个人博客:http://fuxuemingzhu.cn/ 目录 题目描述 题目大意 解题方法 直接求 日期 题目地址:https://leetcod ...

  2. 如何利用Python实现Office在线预览

    目前,市场对于Office在线预览功能的需求是很大的.对于我们用户本身来说,下载Office文件后再实现预览是极其不方便的,何况还有一些不能打开的专业文档.压缩文件等.此时,能提供在线预览服务的软件就 ...

  3. POJ 3278:The merchant(LCA&DP)

    The merchant Time Limit: 3000MS   Memory Limit: 65536K Total Submissions: 6864   Accepted: 2375 Desc ...

  4. 洛谷 P1439 【模板】最长公共子序列(DP,LIS?)

    题目描述 给出1-n的两个排列P1和P2,求它们的最长公共子序列. 输入输出格式 输入格式: 第一行是一个数n, 接下来两行,每行为n个数,为自然数1-n的一个排列. 输出格式: 一个数,即最长公共子 ...

  5. 使用 windows bat 脚本命令 一键启动MySQL服务

    @echo off rem Copyright (c) 2019 Moses and/or its affiliates. rem Get Administrator Rights >nul 2 ...

  6. 编写Java程序,实现一个简单的echo程序(网络编程TCP实践练习)

    首先启动服务端,客户端通过TCP的三次握手与服务端建立连接: 然后,客户端发送一段字符串,服务端收到字符串后,原封不动的发回给客户端. ECHO 程序是网络编程通信交互的一个经典案例,称为回应程序,即 ...

  7. Java支持IPv6研究

    1.Java对IPv6的支持 相对其他开发语言而言,Java对IPv6的支持是比较透明的, 如果全部采用域名(主机名)的方式进行通信,那么基本不需要修改也无需编译原来的代码就可以直接在IPv6上运行. ...

  8. 初识MASA Blazor

    MASA Blazor是一个Blazor的UI组件库.就像大家写前端熟知的Bootstrap, Ant Design一样. MASA Blazor官网地址:https://blazor.masasta ...

  9. MongoDB分片设计

    #### 如何做好分片集群 * 合理的架构 * 是否需要分片? * 要分多少片? * 数据分布规则? * 正确的姿势 * 选择需要分片的表 * 选择正确的片键 * 使用合适的均衡策略 * 足够的资源 ...

  10. Mysql字符串字段判断是否包含某个字符串的方法

    方法一:like SELECT * FROM 表名 WHERE 字段名 like "%字符%"; 方法二:find_in_set() 利用mysql 字符串函数 find_in_s ...