Adaptive Application Scheduling under Interference in Kubernetes

Abstract

Containers are rapidly replacing Virtual Machines (VMs) as the compute instance in cloud-based deployments. The significantly lower overhead of deploying containers (compared to VMs) has often been cited as one reason for this. However, interference caused by the limited isolation in shared resources can impact into the performance of hosted applications. We develop a Reference Net-based model of resource management within Kubernetes, primarily to better characterise such performance issues. Our model makes use of data obtained from a Kubernetes deployment, and can be used as a basis to design scalable (and potentially interference tolerant) applications that make use of Kubernetes.