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DAY 24
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DevOps

Kubernetes的30天養成計劃系列 第 24

[Day24] k8s進階篇延伸與EKS(二):Scheduling

前言

今天我們主要來探討關於“排程”,也就是所謂的Scheduling這件事情,牽涉到這類的功能有:Affinity and Anti-Affinity、Taints and Tolerations、Cordon and Uncordon、Drain等等,接下來的時間,我們就來綜合運用操作一下,體驗下在AWS上集群操作和minikube有何不同。

進階篇(下)

我們來測試一個簡單的例子,模擬一般日常維運時可能會有的操作

這個例子會結合NodeAffinity、Taints and Tolerations、Cordon and Uncordon、Drain的觀念

步驟如下:

  1. 集群內有兩個節點,分別為A、B
  2. 將ReplicaSet=2且NodeAffinity為machine=maintain的Deployment部署到集群上
  3. 檢查集群Pod狀態,此時AB上都可見其對應的Pod
  4. 將A設定Drain,這時候A上的Pod會轉移到B上,檢查集群Pod就看到
  5. 將A設定Uncordon,這時候A可以調度了
  6. 將A設定Taint,如果沒有Toleraion就不能調度到A上
  7. 重啟Deployment,這時候Pod還是只會調度到B上
  8. 修改Deployment,A增加Toleraion
  9. 重啟Deployment,這時候Pod會調度在A、B上

複習傳送門:

檢查集群的節點狀態

$kubectl get nodes
NAME                                               STATUS   ROLES    AGE     VERSION
ip-192-168-41-48.ap-southeast-1.compute.internal   Ready    <none>   3h15m   v1.13.8-eks-cd3eb0
ip-192-168-66-13.ap-southeast-1.compute.internal   Ready    <none>   3h15m   v1.13.8-eks-cd3eb0

這裡的意思是他有開了兩台計算節點,也就是Slave,兩個EC2,我們複習下:

Elastic Compute Cloud(EC2) ,是由亞馬遜公司提供的Web服務,是一個讓使用者可以租用雲端電腦運行所需應用的系統。EC2藉由提供Web服務的方式讓使用者可以彈性地運行自己的機器映像檔,使用者將可以在這個虛擬機器上運行任何自己想要的軟體或應用程式,也可以隨時建立、執行、終止自己的虛擬伺服器,使用多少時間算多少錢,也因此這個系統是「彈性」使用的。EC2讓使用者可以控制執行虛擬伺服器的主機地理位置,這可以改善讓延遲還有備援性例如,為了讓系統維護時間最短,用戶可以在每個時區都運行自己的虛擬伺服器。

在這裡可以看到

https://ithelp.ithome.com.tw/upload/images/20191009/20120468DfQPY8oVwm.png

我們前面有提過,主節點是看不到的,也就是Master,因為它是由EKS所管理。

我們再詳細看下節點狀態(節錄部分

$kubectl describe nodes
Name:               ip-192-168-66-13.ap-southeast-1.compute.internal
Roles:              <none>
Labels:             alpha.eksctl.io/cluster-name=eks-cluster
                    alpha.eksctl.io/instance-id=i-06579f236b49d404c
                    alpha.eksctl.io/nodegroup-name=ng-c8598d87
                    beta.kubernetes.io/arch=amd64
                    beta.kubernetes.io/instance-type=m5.large
                    beta.kubernetes.io/os=linux
                    failure-domain.beta.kubernetes.io/region=ap-southeast-1
                    failure-domain.beta.kubernetes.io/zone=ap-southeast-1b
                    kubernetes.io/hostname=ip-192-168-66-13.ap-southeast-1.compute.internal
Annotations:        node.alpha.kubernetes.io/ttl: 0
                    volumes.kubernetes.io/controller-managed-attach-detach: true
CreationTimestamp:  Wed, 09 Oct 2019 10:50:49 +0800
Taints:             <none>
Unschedulable:      false
Addresses:
  InternalIP:   192.168.66.13
  ExternalIP:   13.229.86.100
  Hostname:     ip-192-168-66-13.ap-southeast-1.compute.internal
  InternalDNS:  ip-192-168-66-13.ap-southeast-1.compute.internal
  ExternalDNS:  ec2-13-229-86-100.ap-southeast-1.compute.amazonaws.com
Capacity:
 attachable-volumes-aws-ebs:  25
 cpu:                         2
 ephemeral-storage:           20959212Ki
 hugepages-1Gi:               0
 hugepages-2Mi:               0
 memory:                      7865400Ki
 pods:                        29
Allocatable:
 attachable-volumes-aws-ebs:  25
 cpu:                         2
 ephemeral-storage:           19316009748
 hugepages-1Gi:               0
 hugepages-2Mi:               0
 memory:                      7763000Ki
 pods:                        29
System Info:
 Machine ID:                 ec2b79d38b6086059acbbc1ee59fecfe
 System UUID:                EC2B79D3-8B60-8605-9ACB-BC1EE59FECFE
 Boot ID:                    1b2c2493-8c4a-4930-92ea-5086dd7a4d77
 Kernel Version:             4.14.133-113.112.amzn2.x86_64
 OS Image:                   Amazon Linux 2
 Operating System:           linux
 Architecture:               amd64
 Container Runtime Version:  docker://18.6.1
 Kubelet Version:            v1.13.8-eks-cd3eb0
 Kube-Proxy Version:         v1.13.8-eks-cd3eb0
ProviderID:                  aws:///ap-southeast-1b/i-06579f236b49d404c
Non-terminated Pods:         (4 in total)
Namespace                  Name                        CPU Requests  CPU Limits  Memory Requests  Memory Limits  AGE
  ---------                  ----                        ------------  ----------  ---------------  -------------  ---
  kube-system                aws-node-mrnzb              10m (0%)      0 (0%)      0 (0%)           0 (0%)         3h32m
  kube-system                coredns-5d8659f47b-f4gc6    100m (5%)     0 (0%)      70Mi (0%)        170Mi (2%)     3h37m
  kube-system                coredns-5d8659f47b-qrxh5    100m (5%)     0 (0%)      70Mi (0%)        170Mi (2%)     3h37m
  kube-system                kube-proxy-p4prg            100m (5%)     0 (0%)      0 (0%)           0 (0%)         3h32m
Allocated resources:
  (Total limits may be over 100 percent, i.e., overcommitted.)
  Resource                    Requests    Limits
  --------                    --------    ------
  cpu                         310m (15%)  0 (0%)
  memory                      140Mi (1%)  340Mi (4%)
  ephemeral-storage           0 (0%)      0 (0%)
  attachable-volumes-aws-ebs  0           0
Events:                       <none>

可以注意到兩個節點的Taint都沒有設置,相較於minikube,有增加了一些內容:

  • attachable-volumes-aws-ebs:這個是AWS才有的參數,意思是說可以將EBS中的Volume附加到節點上的數量,這裡是25
  • aws-node-xxx:這個是在kube-system的namespace開起來的Pod,每個代表在AWS中運行的EC2
  • hugepages-1Gi/2Mi:Huge Page 是指使用到的 Memory Page 大小超過 4Ki,在 x86_64 架構下有 2Mi 和 1Gi 兩種常見的大小

OK,可以知道有兩個節點,接著我們來操作下

我們先準備一個測試用的Pod,這是我們之前測試Deployment的內容

$vim pod-deploy-affinity.yaml
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: helloworld-deployment
spec:
  replicas: 2
  template:
    metadata:
      labels:
        app: helloworld
    spec:
      containers:
      - name: k8s-demo
        image: 105552010/k8s-demo
        ports:
        - containerPort: 3000
        resources:
          requests:
            cpu: 100m
            memory: 50Mi
      affinity:
        nodeAffinity:
          requiredDuringSchedulingIgnoredDuringExecution:
            nodeSelectorTerms:
            - matchExpressions:
              - key: machine
                operator: NotIn
                values:
                - maintain

接著我們啟動它

$kubectl apply -f pod-deploy-affinity.yaml
deployment.extensions/helloworld-deployment created

檢查Pod狀態

$kubectl get po
NAME                                     READY   STATUS              RESTARTS   AGE
helloworld-deployment-5b5457694d-k2l8n   0/1     ContainerCreating   0          5s
helloworld-deployment-5b5457694d-rxcx4   0/1     ContainerCreating   0          5s
$kubectl get po
NAME                                     READY   STATUS    RESTARTS   AGE
helloworld-deployment-5b5457694d-k2l8n   1/1     Running   0          46s
helloworld-deployment-5b5457694d-rxcx4   1/1     Running   0          46s

看起來正常,我們來看下這2個Pod是在哪個節點上跑的

$kubectl describe po helloworld-deployment-5b5457694d-k2l8n |grep Node:
Node:               ip-192-168-66-13.ap-southeast-1.compute.internal/192.168.66.13
$kubectl describe po helloworld-deployment-5b5457694d-rxcx4|grep Node:
Node:               ip-192-168-41-48.ap-southeast-1.compute.internal/192.168.41.48

可以發現到他有自動分配,沒有把兩個Pod放在同個節點上,不錯

接著我們開始進行Scheduling的操作

假設我們要維護ip-192-168-66-13.ap-southeast-1.compute.internal/192.168.66.13這個節點

所以我們要先做的是Drain,這裡有預告過。

$kubectl drain ip-192-168-66-13.ap-southeast-1.compute.internal --ignore-daemonsets
node/ip-192-168-66-13.ap-southeast-1.compute.internal already cordoned
WARNING: Ignoring DaemonSet-managed pods: aws-node-mrnzb, kube-proxy-p4prg
pod/coredns-5d8659f47b-qrxh5 evicted
pod/coredns-5d8659f47b-f4gc6 evicted
pod/helloworld-deployment-5b5457694d-k2l8n evicted
node/ip-192-168-66-13.ap-southeast-1.compute.internal evicted

可以發現到這個節點已經是Cordon的狀態,在這個節點上跑的元件都已經evicted

我們來看看Pod的狀態

$kubectl get po
NAME                                     READY   STATUS    RESTARTS   AGE
helloworld-deployment-5b5457694d-48gth   1/1     Running   0          59s
helloworld-deployment-5b5457694d-rxcx4   1/1     Running   0          23m

第一個Pod是重新開的,我們來看一下它在哪個節點上跑

$kubectl describe po helloworld-deployment-5b5457694d-48gth|grep Node:
Node:               ip-192-168-41-48.ap-southeast-1.compute.internal/192.168.41.48

有了,它已經轉移到另一個節點上了!

附帶一提,因為我們在啟動Deployment的時候有給Pod一個NodeAffinity的限制,它將不會調度Pod到節點Label是machine=maintain的機器上,因為在ip-192-168-41-48.ap-southeast-1.compute.internal這個機器沒有這個Label,所以Pod可以成功調度,也就可以從另外一個Cordon的節點轉移過來。

接著我們把現在可調度的節點也Cordon,這時候在它上面跑的Pod應該要活得好好的

$kubectl cordon ip-192-168-41-48.ap-southeast-1.compute.internal
node/ip-192-168-41-48.ap-southeast-1.compute.internal cordoned

檢查節點狀態

$kubectl get no
NAME                                               STATUS                     ROLES    AGE     VERSION
ip-192-168-41-48.ap-southeast-1.compute.internal   Ready,SchedulingDisabled   <none>   5h35m   v1.13.8-eks-cd3eb0
ip-192-168-66-13.ap-southeast-1.compute.internal   Ready,SchedulingDisabled   <none>   5h35m   v1.13.8-eks-cd3eb0

有的,現在兩個節點都不能調度了

我們來看看Pod的狀態

$kubectl get po
NAME                                     READY   STATUS    RESTARTS   AGE
helloworld-deployment-7cdb76fc48-g9t88   1/1     Running   0          13m
helloworld-deployment-7cdb76fc48-z7z8p   1/1     Running   0          13m

看樣子還行,檢查下開在哪個節點上

$kubectl describe po |grep Node:
Node:               ip-192-168-41-48.ap-southeast-1.compute.internal/192.168.41.48
Node:               ip-192-168-41-48.ap-southeast-1.compute.internal/192.168.41.48

所以還是在同個節點上,看樣子沒啥問題

維護好後,接著我們把ip-192-168-66-13.ap-southeast-1.compute.internal這個節點的Cordon的狀態解除

$kubectl uncordon ip-192-168-66-13.ap-southeast-1.compute.internal
node/ip-192-168-66-13.ap-southeast-1.compute.internal uncordoned

發現到現在這個節點可以調度了

$kubectl get no
NAME                                               STATUS                     ROLES    AGE     VERSION
ip-192-168-41-48.ap-southeast-1.compute.internal   Ready,SchedulingDisabled   <none>   5h44m   v1.13.8-eks-cd3eb0
ip-192-168-66-13.ap-southeast-1.compute.internal   Ready                      <none>   5h44m   v1.13.8-eks-cd3eb0

這裡我們先把可以調度的這個節點加個Taint

$kubectl taint nodes ip-192-168-66-13.ap-southeast-1.compute.internal app=helloworld:NoSchedule
node/ip-192-168-66-13.ap-southeast-1.compute.internal tainted

因為它被Taint了,所以如果它沒有Toleration,所以就算它滿足Affinity,也不會調度喔!

我們重啟Deployment試試

$kubectl delete -f pod-deploy-affinity.yaml
deployment.extensions "helloworld-deployment" deleted
$kubectl get po
NAME                                     READY   STATUS        RESTARTS   AGE
helloworld-deployment-7cdb76fc48-g9t88   1/1     Terminating   0          35m
helloworld-deployment-7cdb76fc48-z7z8p   1/1     Terminating   0          35m
$kubectl describe po |grep Node:
Node:                      ip-192-168-41-48.ap-southeast-1.compute.internal/192.168.41.48
Node:                      ip-192-168-41-48.ap-southeast-1.compute.internal/192.168.41.48
$kubectl get po
No resources found.
$kubectl create -f pod-deploy-affinity.yaml
deployment.extensions/helloworld-deployment created
$kubectl get po
NAME                                     READY   STATUS    RESTARTS   AGE
helloworld-deployment-7cdb76fc48-ccfpj   0/1     Pending   0          11s
helloworld-deployment-7cdb76fc48-dcwq9   0/1     Pending   0          11s

可以發現到Pod都是Pending的狀態!

先把Deployment停掉

$kubectl delete -f pod-deploy-affinity.yaml
deployment.extensions "helloworld-deployment" deleted

我們修改之前的Pod Affinity and AntiAffinity及Toleration的YAML去測試

這個內容和之前的Pod Affinity那份不同,更進一步把Pod Affinity的設定應用到Deployment上

$vim pod-deploy-podaffinity-tol.yaml
apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: helloworld-deployment
spec:
  replicas: 2
  template:
    metadata:
      labels:
        app: helloworld
    spec:
		  containers:
		  - name: k8s-demo
		    image: 105552010/k8s-demo
		    ports:
		    - name: nodejs-port
		      containerPort: 3000
		  affinity:
		    podAffinity:
		      requiredDuringSchedulingIgnoredDuringExecution:
		      - labelSelector:
		          matchExpressions:
		          - key: app
		            operator: In
		            values:
		            - helloworld
		        topologyKey: kubernetes.io/hostname
		    podAntiAffinity:
		      preferredDuringSchedulingIgnoredDuringExecution:
		      - weight: 1
		        podAffinityTerm:
		          labelSelector:
		            matchExpressions:
		            - key: app
		              operator: In
		              values:
		              - node-affinity-pod
		          topologyKey: kubernetes.io/hostname
		  tolerations:
		  - key: "app"
		    operator: "Equal"
		    value: "helloworld"
		    effect: "NoSchedule"

好了就create試試

$kubectl create -f pod-deploy-podaffinity-tol.yaml
deployment.extensions/helloworld-deployment created

檢查Pod狀態

$kubectl get po
NAME                                    READY   STATUS    RESTARTS   AGE
helloworld-deployment-87db87ff7-kt2j5   1/1     Running   0          8s
helloworld-deployment-87db87ff7-sxrmj   1/1     Running   0          8s

有了,但是是開在同個節點上嗎?別忘了我們之前有把另一個Cordon喔!

$kubectl describe po|grep Node:
Node:               ip-192-168-66-13.ap-southeast-1.compute.internal/192.168.66.13
Node:               ip-192-168-66-13.ap-southeast-1.compute.internal/192.168.66.13

有的,兩個Pod開在同個節點上,這個節點是有Taint的,因為有了Toleration,所以可以調度Pod到上面~

恢復原狀

$kubectl delete -f pod-deploy-podaffinity-tol.yaml
deployment.extensions "helloworld-deployment" deleted
$kubectl describe no |grep Taint
Taints:             app=helloworld:NoSchedule
Taints:             node.kubernetes.io/unschedulable:NoSchedule
$kubectl taint nodes ip-192-168-66-13.ap-southeast-1.compute.internal app-
node/ip-192-168-66-13.ap-southeast-1.compute.internal untainted
$kubectl get no
NAME                                               STATUS                     ROLES    AGE     VERSION
ip-192-168-41-48.ap-southeast-1.compute.internal   Ready,SchedulingDisabled   <none>   5h47m   v1.13.8-eks-cd3eb0
ip-192-168-66-13.ap-southeast-1.compute.internal   Ready                      <none>   5h47m   v1.13.8-eks-cd3eb0
$kubectl uncordon ip-192-168-41-48.ap-southeast-1.compute.internal
node/ip-192-168-41-48.ap-southeast-1.compute.internal uncordoned
$kubectl get no
NAME                                               STATUS                     ROLES    AGE     VERSION
ip-192-168-41-48.ap-southeast-1.compute.internal   Ready                      <none>   5h48m   v1.13.8-eks-cd3eb0
ip-192-168-66-13.ap-southeast-1.compute.internal   Ready                      <none>   5h48m   v1.13.8-eks-cd3eb0

OK,測試結束囉!

小結

今天我們在AWS群集上進一步操作了Affinity and Anti-Affinity、Taints and Toleration、以及前面所提過的管理三劍客:Drain、Cordon、Uncordon等等,這次的例子將整個Scheduling的觀念系統化地結合了一起,有些不熟悉的朋友,請務必將前面的內容瀏覽過,這樣會比較好喔!明天我們會更進一步,前往AWS上的管理篇內容,可以發現到與minikube的細微差異,加油!我們明天見囉!

參考連結

本文同步刊載於https://github.com/x1y2z3456/ironman

感謝您撥冗閱讀此文章,不喜勿噴,有任何問題建議歡迎下方留言:)

說個笑話,希望我能寫滿30天啊(笑


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[Day23] k8s進階篇延伸與EKS(一):Ingress、ELB、Service
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[Day25] k8s管理篇延伸與EKS(一):Service Discovery、Dashboard、Monitoring
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