A Feasibility Study of Host-Level Contention Detection by Guest Virtual Machines

Abstract

We investigate the feasibility of detecting host-level CPU contention from inside a guest virtual machine (VM). Our methodology involves running benchmarks with deterministic and randomized execution times inside a guest VM in a private cloud testbed. Simultaneously, using the recently proposed COCOMA tool, we expose the guest VM to host-level CPU stealing events of increasing intensity. This leads us to observe that the use of hyper-threading in the host can hinder detection of CPU contention, which otherwise can be done accurately using the CPU steal metric. For systems where hyper-threading is enabled, we investigate the performance of some basic detection algorithms. We find that thresholding often outperforms more sophisticated statistical tests.