Radio: Reconciling Disk I/O Interference in a Para-virtualized Cloud

Abstract

As more virtual machines (VMs) are consolidated in the cloud system, interference among VMs sharing underlying resources may occur more frequently than ever. In particular, certain VMs’ disk I/O performance gets impacted, leading to related cloud services being seriously compromised. Existing interference analysis approaches cannot guarantee desired results due to 1) lack of effective techniques for characterizing disk I/O interference and 2) considerable runtime overhead for determining interference and related culprits. To overcome these barriers, we present Radio, an end-to-end analysis tool for disk I/O interference diagnostics in a para-virtualized cloud. Radio quantifies the dynamic changes in I/O strength across virtual CPUs (vCPUs), constructs the performance repository to efficiently identify VMs’ abnormal behaviors, and then exploits interference heat maps and non-constant correlation approaches to infer the culprits of interference. With Radio's deployment at the National Supercomputing Center in Wuxi for more than 10 months, we demonstrate its effectiveness in real-world use cases on the cloud system with more than 300 VMs deployed. Radio can effectively analyze the interference issues within 20 seconds, incurring only 0.2% extra CPU overhead on the host machine. With this achievement, Radio has successfully assisted system administrators in reducing the daily incidence of interference from more than 65% to less than 10% and improving the overall disk throughput of the cloud system by more than 27.5%.