Taming IO spikes in enterprise and campus VM deployment

Abstract

Enterprises and campuses have widely employed virtualiza-tion to improve resource utilization and save capital costs. The virtualized storage infrastructure usually comprises a pool of storage nodes (disks, RAID groups and storage servers), each consolidating a number of virtual machines (VMs). The IO workload on each storage node is highly bursty where a few overloaded periods, namely IO spikes, incur lags and greatly affect VM performance. In this paper, we design VMpart, a system that automatically reconfigures VM deployment to remove IO spikes from a deployed VM environment. Firstly, VMpart collects IO parameters and identifies IO spikes for deployed VMs during production periods. Secondly, during the maintenance phase, VMpart divides every VM based on its disk partitions and reconfigures the system with a fine-grained optimized partition deployment for better load balancing. We set up a representative VM environment with desktop and server VMs used in enterprises and campuses to evaluate VMpart. Our experiments show that the optimized deployment reduces the average booting time of desktop VMs during boot storm from 9[%] to 28[%], improves server VM throughput by more than 60[%] and reduces VM storage migration time by about 57[%].