An Experimental Evaluation of Relations Between Architectural and Runtime Metrics in Microservices Systems

The decisions made about the architecture of a microservices system at design time influence the runtime behavior of the resulting system and can be hard to change later. But predicting or evaluating how excatly architecture decisions impact runtime behavior is difficult and in practice mostly based on previous experience. Architectural metrics that are measurable at design time and have a traceable impact on runtime metrics could support architectural decision making to improve quality and prevent costly redevelopments. To investigate traceable relations between architectural metrics and runtime metrics, this paper presents a model-driven generation system for microservice architectures. The system can be used to benchmark different architecture alternatives of a Java-based application without manually changing application code. Using this system, we performed experiments to examine relations between architectural metrics and throughput as a runtime metric.