Horizontal Pod Autoscalers in Kubernetes

Length: 00:17:57

Lesson Summary:

Kubernetes provides some powerful tools for doing autoscaling. A horizontal pod autoscaler (HPA) is one way to implement pod scaling based upon a variety of metrics. This lesson demonstrates how to implement a simple horizontal pod autoscaler within a Kubernetes cluster.


Be sure to check out the full HPA documentation: https://kubernetes.io/docs/tasks/run-application/horizontal-pod-autoscale/


Here is the GitHub repo for the source code used in the demo. Check the example-solution branch for the demo's final state: https://github.com/linuxacademy/cicd-pipeline-train-schedule-autoscaling


Here are the commands used to set up the autoscaler in the demo:

cd ~/
git clone https://github.com/kubernetes-incubator/metrics-server.git
cd metrics-server/
kubectl create -f deploy/1.8+/
kubectl get --raw /apis/metrics.k8s.io/
cd ~/
git clone 
cd cicd-pipeline-train-schedule-autoscaling/
vi train-schedule-kube.yml
kubectl apply -f train-schedule-kube.yml
You can find the changes made to train-schedule-kube.yml in the example-solution branch of the GitHub repo. Once you have deployed the app and the HPA, you can generate CPU load to test it by spinning up a busybox shell:
kubectl run -i --tty load-generator --image=busybox /bin/sh
Then run this in the busybox shell to create load:
while true; do wget -q -O- http://:8080/generate-cpu-load; done


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