Historically, high energy physics computing has been performed on large
purpose-built computing systems. These began as single-site compute facilities,
but have evolved into the distributed computing grids used today. Recently,
there has been an exponential increase in the capacity and capability of
commercial clouds. Cloud resources are highly virtualized and intended to be
able to be flexibly deployed for a variety of computing tasks. There is a
growing nterest among the cloud providers to demonstrate the capability to
perform large-scale scientific computing. In this paper, we discuss results
from the CMS experiment using the Fermilab HEPCloud facility, which utilized
both local Fermilab resources and virtual machines in the Amazon Web Services
Elastic Compute Cloud. We discuss the planning, technical challenges, and
lessons learned involved in performing physics workflows on a large-scale set
of virtualized resources. In addition, we will discuss the economics and
operational efficiencies when executing workflows both in the cloud and on
dedicated resources.Comment: 15 pages, 9 figure