Modeling virtual machine performance: challenges and approaches

Data centers are increasingly employing virtualization and consolidation as a means to support a large number of disparate applications running simultaneously on server platforms. However, server platforms are still being designed and evaluated based on performance modeling of a single highly parallel application or a set of homogenous work-loads running simultaneously. Since most future datacenters are expected to employ server virtualization, this paper takes a look at the challenges of modeling virtual machine (VM) performance on a datacenter server. Based on vConsolidate (a server virtualization benchmark) and latest multi-core servers, we show that the VM modeling challenge requires addressing three key problems: (a) modeling the contention of visible resources (cores, memory capacity, I/O devices, etc), (b) modeling the contention of invisible resources (shared microarchitecture resources, shared cache, shared memory bandwidth, etc) and (c) modeling overheads of virtual machine monitor (or hypervisor) implementation. We take a first step to addressing this problem by describing a VM performance modeling approach and performing a detailed case study based on the vConsolidate benchmark. We conclude by outlining outstanding problems for future work.