Software Engineering Dimensions: Empirical Frameworks on Microservices Architecture in Cloud Computing Domains

Microservices Architecture (MSA) has become a popular approach for developing scalable and adaptable cloud applications, offering enhanced flexibility, maintainability, and resilience compared to traditional monolithic systems. However, the practical application of MSA introduces operational complexities, particularly in optimizing performance, ensuring fault tolerance, and managing inter-service communication. Empirical research is essential to address these challenges and validate MSA’s performance. This involves employing methodologies such as case studies, performance testing, and profiling to provide actionable insights into key areas like scalability, latency, and system resilience. By evaluating system behavior under varying conditions, researchers can bridge the gap between the theoretical advantages of MSA and its real-world application in cloud environments. This research emphasizes the importance of empirical frameworks in guiding the implementation and evaluation of MSA. These frameworks offer structured methods for assessing performance, scalability, and reliability, thereby enabling organizations to make informed decisions about adopting and optimizing MSA. The findings contribute to a deeper understanding of the trade-offs and best practices associated with MSA, supporting its effective deployment in complex cloud-based systems. Keywords: Software Engineering, Microservices, Frameworks, Cloud Computing Domains