Evaluación del Impacto de la Configuración Regional de Instancias en Azure sobre la Latencia y el Tiempo de Carga en una Plataforma Web de Gestión de Citas Psicológicas Basada en la Arquitectura Cliente-Servidor usando Spring

This thesis, titled "Evaluation of the Impact of Regional Configuration of Instances in Azure on Latency and Load Time in a Web Platform for Managing Psychological Appointments Based on Client-Server Architecture Using Spring," has as its main objective to develop a web application prototype for managing psychological appointments. Utilizing client-server architecture and Spring technology on the Azure platform, the aim is to optimize the user experience concerning response times and latency when accessing mental health services. The first specific objective focuses on the development of the prototype, which was carried out using an agile development model with the Scrum framework. This methodology allowed for more efficient planning and execution, resulting in an application that meets the necessary functional and non-functional requirements. The implementation of the client-server architecture ensures smooth and secure interaction between users and the application, which is essential in the context of mental health. The second objective analyzes the relationship between three regional configurations of Azure instances in the Americas and the performance indicators of the prototype, particularly latency and load time. For this analysis, a study was conducted using Pearson's correlation coefficient, yielding a value close to 0.97, indicating a strong positive correlation. This result highlights the influence of geographical proximity to the instances on user experience, where lower latency translates into more efficient load times. Finally, it is concluded that the appropriate selection of regional configurations is crucial for optimizing the performance of applications in general and especially for applications related to mental health. Further research is suggested to consider other variables that may impact system efficiency.

• Hoofdauteur: Jaya Jaramillo, José Leonardo (author)
• Formaat: masterThesis
• Taal: spa
• Gepubliceerd in: 2025
• Onderwerpen: AZURE; LATENCIA
• Online toegang: https://dspace.unl.edu.ec/jspui/handle/123456789/31974