Performance impact of virtual machine placement in a datacenter

In virtualized systems, several Virtual Machines (VM) running on a single hardware platform share and compete for the hardware resources such as memory, disk and network IO to meet a certain Quality of Service (QoS) requirements. It is critical to characterize and understand how the different workloads running in the VMs interact and share such resources to be able to map them efficiently onto processor cores and server hosts for optimal performance. This is especially important for resources such as memory controllers or the on-chip or inter-socket networks for which there is currently no software control. In this paper, we present a measurement-based performance analysis of server virtualization workloads from a real system using virtual machines that are part of the popular industry standard VMmark benchmark, a server consolidation benchmark. First, we characterize the relative resource contention and interference impact of VMs when multiple virtual workloads are run together. Second, we study the effects of co-locating different types of VMs under various VM to core placement schemes and discover the best placement for performance. We observe performance variations from 25-65% for Database servers and from 7-40% for File servers when compared to standalone VM depending on the placement of these VMs onto cores and the degree of sharing of resources. Finally, we propose an interference metric and regression model for the worst set of co-located VMs in our study. Based on different VM placement schemes we show that the overall server consolidation performance in a virtualized host can be improved by 8% when the VMs are placed effectively.