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Horizontal Pod Autoscaler

PREREQUISITE

For setting up HPA you must have a working kubernetes cluster with proper master and nodes server in proper up and ready state, you may need to edit the cluster to fetch metrics and for that you need to deploy metric-server deployment on to your cluster. To apply HPA follow the steps that are mentioned in this website as below.

UPDATING CLUSTER CONFIGURATION

First edit the cluster configuration by using the below command:-

kops edit cluster

It will show you the cluster configuration, replace the kubelet part in the configuration with the part mentioned below:- 

kubelet: 
   anonymousAuth: false 
   authenticationTokenWebhook: true 
   authorizationMode: Webhook

Save this configuration and update your cluster with the command below:- 

kops update cluster --name=( cluster -name) --yes

If asks for rolling update then update cluster with rolling update:-

kops rolling - update cluster --yes

NOTE:- It may take some time to update because you have edited the cluster configuration as it may terminate the old instances and bring up the new instances on its own, so have to do nothing just wait for 5-10 minutes.

DEPLOYING METRICS SERVER ON THE CLUSTER FOR HPA

For deploying the metrics server clone the github repository on your server 

git clone https ://github.com/kubernetes-incubator/metrics-server.git

Now change to directory metrics-server/deploy/kubernetes 

cd metrics-server/ deploy /kubernetes

You will find some yaml files in this location, edit the metrics-server-deployment.yaml file and replace the contents of file with contents mentioned below:- 

---
apiVersion : v1
kind : ServiceAccount
metadata :
 name : metrics-server
 namespace : kube-system
---
apiVersion : apps/v1
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:v0.3.6
    command :
      - /metrics-server
      - --v=2
      - --kubelet-insecure-tls
      - --kubelet-preferred-address-types=InternalIP
    args :
      - --cert-dir=/tmp
      - --secure-port=4443
    ports :
    - name : main-port
      containerPort : 4443
      protocol : TCP
    securityContext :
      readOnlyRootFilesystem : true
      runAsNonRoot : true
      runAsUser : 1000
    imagePullPolicy : Always
    volumeMounts :
    - name : tmp-dir
      mountPath : /tmp
nodeSelector :
  beta.kubernetes.io/os : linux
  kubernetes.io/arch : "amd64"

Now execute the below command to deploy metric-server on your cluster:-

kubectl create -f .

Now wait for few seconds and execute the below commands to check your pods for metric-server 

kubectl get pods -n kube- system

To check logs of metric-server 

kubectl -n kube-system logs (mertic-server-pod-name)

It should start fetching metrics from nodes and pods

TESTING HORIZONTAL POD SCALER

For testing HPA we will create a deployment and service and do not forget to add limits and resources in your deployment.yaml, because if you will skip them in your yaml then you won’t be able to apply hpa.

For example create a deployment and service.yaml as mentioned in below example:- 

apiVersion: apps/v1 
kind: Deployment 
metadata: 
  name: php-apache 
spec: 
 selector: 
   matchLabels: 
     run: php-apache 
  replicas: 1 
  template: 
    metadata: 
      labels: 
        run: php-apache 
    spec: 
      containers: 
      - name: php-apache 
        image: k8s.gcr.io/hpa-example 
        ports: 
        - containerPort: 80 
        resources: 
          limits: 
            cpu: 500m 
          requests: 
            cpu: 200m 
--- 
apiVersion: v1 
kind: Service 
metadata: 
  name: php-apache 
  labels: 
    run: php-apache 
 spec: 
   ports: 
   - port: 80 
   selector: 
     run: php-apache

Save the above yaml file with the name that you want, in my case i have named it as php-deployment.yaml
Now create deployment with command:- 


kubectl create -f php-deployment .yaml

CREATE HORIZONTAL POD AUTOSCALER

Now that the server is up and running, we will now create the autoscaler using kubectl autoscale. The below command will create a Horizontal Pod Autoscaler which will maintain between 1 and 10 replicas of the Pods with CPU utilization of 50% controlled by the php-apache deployment we created in the above step of these instructions.

kubectl autoscale deployment php-apache --cpu-percent =50 --min =1 --max =10

We can check the current status of autoscaler by running below command:

kubectl get hpa

Now wait for 1 or 2 minutes as it will start fetching metrics .

INCREASE LOAD

Now, we will see how the autoscaler reacts to our increased load. Kindly run the blow command in different terminal:

kubectl run --generator=run-pod/v1 -it --rm load-generator --image=busybox /bin/sh 
# Hit enter for command prompt 
while true; do wget -q -O- http://php-apache.default.svc.cluster.local; done

Within a minute or so, we should see the higher CPU load by executing/running below command: 

kubectl get hpa 

NAME       REFERENCE                   TARGET  MINPODS  MAXPODS REPLICAS AGE 
php-apache Deployment/php-apache/scale 305%/50%   1        10       1       3 m

Here, CPU consumption has increased to 405% of the request. As a result, the deployment was resized to 7 replicas: 

kubectl get deployment php-apache
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