An Assessment Model to Establish the Use of Services Resources in a Cloud Computing Scenario L. Davila Nicanor, H. R. Orozco Aguirre, and V. M. Landassuri Moreno Abstract When a system or application is designed to run on the Cloud, the scope on storage, users, infrastructure needs, are set by the use, based on the practical environment. It is necessary to replace practices based on experiences and take into account the measurement practices offered by Quality of Service. The main goal of this chapter is to present an assessment model of the availability and efficiency of the existing applications in Cloud Computing to establish their priority of use through statistical simulation and graph models. This requires an analysis of the concerns of the applications available in the Cloud Services. This model is projected as a guide that provides predictive parameters for its evaluation and availability based on the operation of applications from the point of view of user. To create this model, it is necessary to take into account an analysis of the potential risks during the execution of the application and the data analysis query provided to users, in order to efficiently manage resources in an organization. 1 Introduction Nowadays, everything is moving toward the use of the Cloud, because it is much more productive for any company, that the supplier makes sure of its website, its connec- tivity, storage capacity, and the availability of the service. Cloud Computing (CC) refers to one set of attributes that any Information Technology (IT) infrastructure implements, which is a feasible alternative for business owners, where information is the basis of the business. Sharing resources represent the biggest benefit of Cloud L. Davila Nicanor (B ) · H. R. Orozco Aguirre · V. M. Landassuri Moreno University Center UAEM Valley of Mexico, Autonomous University of Mexico State, Boulevard University, Predio San Javier, Atizapan de Zaragoza, Mexico State, Mexico e-mail: ldavilan@uaemex.mx H. R. Orozco Aguirre e-mail: hrorozcoa@uaemex.mx V. M. Landassuri Moreno e-mail: vmlandassurim@uaemex.mx © Springer Nature Singapore Pte Ltd. 2020 A. Nanda and N. Chaurasia (eds.), High Performance Vision Intelligence, Studies in Computational Intelligence 913, https://doi.org/10.1007/978-981-15-6844-2_7 83