Abstract
The microservices architectural style is picking up more and more momentum in IT industry for the development of systems as loosely coupled, collaborating services. Companies that undergo the migration of their own applications have aspirations such as increasing maintainability and the scale of operation. Such a process is worthwhile but not easy, since it should ensure atomic improvements to the overall architecture for each migration step. Furthermore, the systematic evaluation of migration steps becomes cumbersome without sensible optimization metrics that take into account performance and scalability under expected operational conditions. Recent lines of research recognize this task as challenging, especially in data-intensive applications where known approaches based, for instance, on Domain Driven Design may not be adequate. In this paper, we introduce an approach to evaluate a migration in an iterative way and recognize whether it represents an improvement in terms of performance and scalability. The approach leverages a Domain Metric-based analysis to quantitatively evaluate alternative architectures. We exemplified the envisioned approach on a data-intensive application case study in the domain of smart mobility. Preliminary results from our controlled experiments show the effectiveness of our approach to support systematic and automated evaluation of migration processes.