Scaling further

In this lab exercise, we'll scale up our entire application architecture further than we did in the CA section and see how the responsiveness differs.

~/environment/eks-workshop/modules/autoscaling/compute/overprovisioning/scale/deployment.yaml

apiVersion: apps/v1
kind: Deployment
metadata:
  name: all
spec:
  replicas: 5

Apply the updates to your cluster:

~$kubectl apply -k ~/environment/eks-workshop/modules/autoscaling/compute/overprovisioning/scale

~$kubectl wait --for=condition=Ready --timeout=180s pods -l app.kubernetes.io/created-by=eks-workshop -A

As the new pods roll out there will eventually be a conflict where the pause pods are consuming resources that the workload services could make use of. Because of our priority configuration the pause pod will be evicted to allow the workload pods to start. This will leave some or all of the pause pods in a Pending state:

~$kubectl get pod -n other -l run=pause-pods

NAME                          READY   STATUS    RESTARTS   AGE

pause-pods-5556d545f7-2pt9g   0/1     Pending   0          16m

pause-pods-5556d545f7-k5vj7   0/1     Pending   0          16m

This in turn will allow our workload pods transition to ContainerCreating and Running quicker.