A Quantitative Approach for the Assessment of Microservice Architecture Deployment Alternatives by Automated Performance Testing

Microservices have emerged as an architectural style for developing distributed applications. 
Assessing the performance of architectural deployment alternatives is challenging and must be aligned with the system usage in the production environment. 
In this paper, we introduce an approach for using operational profiles to generate load tests to automatically assess scalability pass/fail criteria of several microservices deployment alternatives, using a baseline computation of performance requirements. 
We have evaluated our approach with different architecture deployment alternatives using extensive lab studies in a large bare metal host environment and a virtualized environment.
We have found that in auto-scaling cloud environments careful performance engineering activities shall be executed before additional resources are added to the architecture deployment configuration.