We develop a novel approach for run-time global adaptation of microservice applications, based on synthesis of architecture-level reconfigurations. More precisely, we devise an algorithm for proactive–reactive automatic scaling that reaches a target system’s Maximum Computational Load by performing optimal deployment orchestrations. We evaluate our approach by developing a platform for the modeling and simulation of microservice architectures, and we use such a platform to compare local/global and reactive/proactive scaling. Empirical benchmarks, obtained through our platform, show that proactive global scaling consistently outperforms the reactive approach, but the best performances can be obtained by our original approach for mixing proactivity and reactivity. In particular, our approach surpasses the state-of-the-art when both performance and resource consumption are considered.
Bacchiani, L., Bravetti, M., Giallorenzo, S., Gabbrielli, M., Zavattaro, G., Zingaro, S.P. (2025). Proactive-reactive microservice architecture global scaling. THE JOURNAL OF SYSTEMS AND SOFTWARE, 220, 112262-112280 [10.1016/j.jss.2024.112262].
Proactive-reactive microservice architecture global scaling
Bacchiani, Lorenzo
;Bravetti, Mario;Giallorenzo, Saverio;Gabbrielli, Maurizio;Zavattaro, Gianluigi;Zingaro, Stefano Pio
2025
Abstract
We develop a novel approach for run-time global adaptation of microservice applications, based on synthesis of architecture-level reconfigurations. More precisely, we devise an algorithm for proactive–reactive automatic scaling that reaches a target system’s Maximum Computational Load by performing optimal deployment orchestrations. We evaluate our approach by developing a platform for the modeling and simulation of microservice architectures, and we use such a platform to compare local/global and reactive/proactive scaling. Empirical benchmarks, obtained through our platform, show that proactive global scaling consistently outperforms the reactive approach, but the best performances can be obtained by our original approach for mixing proactivity and reactivity. In particular, our approach surpasses the state-of-the-art when both performance and resource consumption are considered.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.