In this exercise, we'll leverage the metrics we've observed in the previous step to automatically scale our UI application in response to load.
Before we can setup autoscaling for our pods, we first need to set resource limits on the pods running in our cluster. Limits allows you to choose the minimum and maximum CPU and memory usage for a pod.
Navigate to Applications > Deployments, then choose your deployment. Then, choose Actions > Edit Resource Limits.
Hopefully you have your running script simulating load (if not go here),
Grafana showed you that your application was consuming anywhere between ".002" to
".02" cores. This translates to 2-20 "millicores". That seems like a good range for
our CPU request, but to be safe, let's bump the higher-end up to 30 millicores. In
addition, Grafana showed that the app consumes about 25-35 MB of RAM. Set the
following resource limits for your deployment now.
{% hint style="info" %} Remember to set the correct unit -- millicores and MB (not MiB) {% endhint %}
Hit save. If there's an error saying that the deployment has changed, you may need to go back to your deployment, refersh the page, and try again.
Now that we have resource limits, let's enable autoscaler. Go back to the deployment, but this time choose Actions > Edit Autoscaler.
By default, the autoscaler allows you to scale based on CPU or Memory. The UI allows
you to do CPU only (for now). Pods are balanced between the minimum and maximum
number of pods that you specify. With the autoscaler, pods are automatically created
or deleted to ensure that the average CPU usage of the pods is below the CPU request
target as defined. In general, you probably want to start scaling up when you get near
50-90% of the CPU usage of a pod. In our case, let's make it 1% to test the autoscaler
since we are generating minimal load.
Click Save.
If you're not running the script from the previous exercise, the pods should stay at 1. Check by going to the overview page.
Start simulating load by hitting the page several times, or running the script. You'll see that it starts to scale up:
That's it! You now have a highly available and automatically scaled front-end Node.js application. OpenShift is automatically scaling your application pods since the CPU usage of the pods greatly exceeded 1% of the resource limit, 30 millicores.
Find the Autoscaler information in the Deployment.
If you're interested in setting up the CLI, follow the steps here. Then, run the following command in your CLI oc get hpa to get information about your horizontal pod autoscaler. Remember to switch to your project first with oc project <project-name>.