[따배쿠] Kubernetes Autoscaling - 운영

Metric Server

 

Metric server 설치

 

[Metric Server 설치]

root@master:~/Getting-Start-Kubernetes/18# git clone https://github.com/237summit/kubernetes-metrics-server.git
Cloning into 'kubernetes-metrics-server'...
remote: Enumerating objects: 25, done.
remote: Counting objects: 100% (25/25), done.
remote: Compressing objects: 100% (24/24), done.
remote: Total 25 (delta 9), reused 9 (delta 1), pack-reused 0 (from 0)
Receiving objects: 100% (25/25), 5.48 KiB | 5.48 MiB/s, done.
Resolving deltas: 100% (9/9), done.

root@master:~/Getting-Start-Kubernetes/18# ls
deploy_web.yaml  hpa_web.yaml  kubernetes-metrics-server

root@master:~/Getting-Start-Kubernetes/18# cd kubernetes-metrics-server

root@master:~/Getting-Start-Kubernetes/18/kubernetes-metrics-server# 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.apps/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

 

[Metric Server 확인]

root@master:~/Getting-Start-Kubernetes/18/kubernetes-metrics-server# kubectl get deploy -A
NAMESPACE      NAME                      READY   UP-TO-DATE   AVAILABLE   AGE
default        my-nginx                  2/2     2            2           11d
kube-logging   elasticsearch-client      1/1     1            1           10d
kube-logging   elasticsearch-master      1/1     1            1           10d
kube-system    calico-kube-controllers   1/1     1            1           11d
kube-system    coredns                   2/2     2            2           11d
kube-system    metrics-server            1/1     1            1           113s

 

Pod 및 Service 생성

 

[Pod 및 Service 생성]

root@master:~/Getting-Start-Kubernetes/18# vi deploy_web.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: deploy-web
spec:
  replicas: 1
  selector:
    matchLabels:
      app: web
  template:
    metadata:
      labels:
        app: web
    spec:
      containers:
      - image: smlinux/hpa-example
        name: web
        ports:
        - containerPort: 80
        resources: 
          requests: 
            cpu: 200m  
---
apiVersion: v1
kind: Service
metadata:
  name: svc-web
spec:
  ports:
  - port: 80
    targetPort: 80
  selector:
    app: web

 

[Pod 및 Service 확인]

root@master:~/Getting-Start-Kubernetes/18# kubectl get deploy,service
NAME                         READY   UP-TO-DATE   AVAILABLE   AGE
deployment.apps/deploy-web   1/1     1            1           94s
deployment.apps/my-nginx     2/2     2            2           11d

NAME                 TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)   AGE
service/kubernetes   ClusterIP   10.96.0.1       <none>        443/TCP   11d
service/svc-web      ClusterIP   10.100.59.214   <none>        80/TCP    94s

 

Horizontal Pod Autoscaler 생성

 

[Horizontal Pod Autoscaler 생성]

root@master:~/Getting-Start-Kubernetes/18# vi hpa_web.yaml
apiVersion: autoscaling/v1
kind: HorizontalPodAutoscaler
metadata:
  name: hpe-web
spec:
  maxReplicas: 10
  minReplicas: 1
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: deploy-web
  targetCPUUtilizationPercentage: 50

 

CPU가 50% 넘기면, Replicas를 최소 1개에서 10개까지 자동으로 scaling 요청

 

root@master:~/Getting-Start-Kubernetes/18# kubectl apply -f hpa_web.yaml
horizontalpodautoscaler.autoscaling/hpe-web created

 

[확인]

root@master:~/Getting-Start-Kubernetes/18# kubectl get hpa
NAME      REFERENCE               TARGETS              MINPODS   MAXPODS   REPLICAS   AGE
hpe-web   Deployment/deploy-web   cpu: <unknown>/50%   1         10        1          30s

 

[무한루프 실행]

 

무한루프를 실행해서 CPU 부하를 가한다.

 

HPA를 통해 Pod가 Scale in 된 것을 확인

 

 

무한루프 실행을 멈추면 CPU가 감소하고 다시 Scale Out

Scale in 되면 5분 대기 후 작동

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[참고 영상]

https://www.youtube.com/watch?v=gaYBOH-obJA&list=PLApuRlvrZKohLYdvfX-UEFYTE7kfnnY36&index=11