Optimizing autoscaling in Kubernetes involves much more than just monitoring CPU and memory, as this blogpost by Cristian Sepulveda demonstrates through a practical application workflow. By leveraging KEDA to scale based on real-world metrics like message queue length, teams can achieve faster, cost-effective scaling tailored to specific application needs.

https://medium.com/@csepulvedab/how-to-optimize-autoscaling-in-kubernetes-using-metrics-based-on-application-workflows-7f899fdef4d9