In this paper we present the case study of an application of a parallel simulation optimization deployed on a private Cloud. The compute-intensive application uses a Master/Worker model, supporting communication over both Java RMI and Globus Grid Services between the nodes. The Master deploys Workers over a Eucalyptus Cloud using the Nimbus Context Broker for just-in-time configuration and runtime Worker discovery. The computational performance of the Workers under different communication mechanisms and deployment scenarios is presented in an attempt to evaluate the use of Virtual Machines in a Cloud as a tool to achieve application scaling. The deployment of this particular application was crafted to support on-the-fly addition of working nodes. The case study suggests a deployment pattern that shapes some requirements and considerations of a scalable Globus-driven Platform as a Service Cloud. Copyright © 2011 John Wiley & Sons, Ltd.