A bi-metric autoscaling approach for n-tier web applications on kubernetes

摘要

Container-based virtualization techniques are becoming an alternative to traditional virtual machines, due to less overhead and better scaling. As one of the most widely used open-source container orchestration systems, Kubernetes provides a built-in mechanism, that is, horizontal pod autoscaler (HPA), for dynamic resource provisioning. By default, scaling pods only based on CPU utilization, a single performance metric, HPA may create more pods than actually needed. Through extensive measurements of a containerized n-tier application benchmark, RUBBoS, we find that excessive pods consume more CPU and memory and even deteriorate response times of applications, due to interference. Furthermore, a Kubernetes service does not balance incoming requests among old pods and new pods created by HPA, due to stateful HTTP.