Virtualization provides enormous economic and ecological benefits by enabling server consolidation and supporting low-cost green data centers. A key component of the hypervisor in a virtualized system is the scheduler. A typical scheduler provides parameters to influence the hypervisor's behavior. Specifically, an application's performance on the popular open-source Xen virtualization platform can be influenced by tuning its scheduler behavior using the weight, cap, and processor pinning variables. However, determining which parameters to tune and how to do that is non-trivial. In this paper, we introduce XenTune, a monitoring tool for the credit scheduler in Xen that helps in understanding application behavior in scheduler terms and assists in determining scheduler parameters. We demonstrate how the tool is used with application domains - specifically a media application domain. We demonstrate experimental results using a real work-load that shows the considerable benefits of correct scheduler parameter choices. XenTune had helped in the design of a recently proposed scheduler S and in this paper we show how scheduler S interacts with the media application to optimize its performance.