Abstract

Perhaps surprisingly, no practical performance models exist for popular (and complex) client applications such as Adobat’s Creative Suite, Microsoft’s Office and Visual Studio, Mozilla, Halo 3, etc. There is currently no tool that automatically answers program developers’, IT administrators’ and end-users’ simple what-if questions like “what happens to the performance of my favourite application X if I upgrade from Windows Vista to Windows 7? ”. This work describes our approach towards constructing practical, versatile performance models to address this problem. The goal is to have these models be useful for application developers to help expand application testing coverage and for IT administrators to assist with understanding the performance consequences of a software, hardware or configuration change. The models we are experimenting with are based on statistical techniques and they require no explicit a priori model on how an OS or application should behave. We are in the process of learning from models we have constructed for several Microsoft products, including the Office suite, Visual Studio and Media Player. This work presents preliminary findings from a large user deployment (several hundred thousand user sessions) of these applications that show the coverage and limitations of such models. (This is a Sigmetrics + TAB practice talk.)