To process big data in a cloud computing environment, a large scale of stream big data is one of the challenging issues. In particular, complex event processing is an emerging technology to handle massive events from multiple sources and process them in a near real time. In this paper, we analyze four performanceinfluencing factors on a virtualized event processing system: the number of query statements, garbage collection intervals, the quantity of virtual machine resources, and virtual CPU assignment types. In our experiments, we observe the performance effects of these performance parameters, by implementing and running an Esper-based event processing application on top of a Xen-based virtualized system. With experimental results, we analyze the memory consumption problem, and apply periodic garbage collection, to reduce unexpected memory consumption of JVM. Also, we analyze performance effects of the number of cores in a virtual machine (VM) and resource sharing among VMs. Under the virtualized environment in cloud computing infrastructure, one of the critical issues is the management of virtualized computing resources. Accordingly, we present the event processing performance on VMs as a function of virtual CPU assignment types and the number of VMs that share virtual CPUs.