Resource contention-aware Virtual Machine management for enterprise applications

Consolidating Virtual Machines (VMs) in data centers is desirable as it reduces hardware and power costs. However the performances of VMs on shared physical servers are not isolated from each other as they contend for the same server resources. This contention degrades the performance of delay sensitive applications and can increase response times by three orders of magnitude at high contention levels. In order to achieve Service Level Agreements (SLAs) under VM consolidation, resources must be allocated by considering the performance effects of contention. We therefore present VARACO, a contention-aware VM management system to achieve Quality-of-Service (QoS) targets for multi-tier web applications. VARACO models applications´ performances online using 13 server resource utilization and contention metrics. Resources are dynamically allocated using these models to achieve QoS targets. Our results show that application- level performance can be modeled 130% more accurately when resource contention is considered. We demonstrate VARACO by achieving a 90^th percentile response time target of a sample application under VM consolidation.