The investment in computing infrastructure to attend seasonal demand or processing peak can generate financial waste, because the most of the time these resources are idle. In addition, in many solutions the response time are critical to attend business requirements, which often, turn the solution economically unviable. In this scenario it is essential intelligent allocation of computing resources according to the demand for processing, allocation and cost of business requirements. The Monte Carlo Simulation is a statistical method widely used to solve a wide range of scientific and engineering problems. When applied to real problems usually have the challenges mentioned. Cloud Computing is an alternative to providing on-demand computing resources, generating economies of scale unprecedented and almost infinite scalability. Aligning a modern architecture to the cloud is possible to encapsulate functionality and offer a range of services that would previously have been restricted to specific areas. In this paper we are interested in building a generic framework, that may provide a range of services based on Monte Carlo, make rational use of the elasticity provided by the cloud in order to achieve better levels of efficiency and reuse.