Proactive-Reactive Global Scaling, with Analytics

In this work, we focus on by-design global scaling, a technique that, given a functional specification of a microservice architecture, orchestrates the scaling of all its components, avoiding cascading slowdowns typical of uncoordinated, mainstream autoscaling. State-of-the-art by-design global scaling adopts a reactive approach to traffic fluctuations, undergoing inefficiencies due to the reaction overhead. Here, we tackle this problem by proposing a proactive version of by-design global scaling able to anticipate future scaling actions. We provide four contributions in this direction: i) a platform able to host both reactive and proactive global scaling; ii) a proactive implementation based on data analytics; iii) a hybrid solution that mixes reactive and proactive scaling; iv) use cases and empirical benchmarks, obtained through our platform, that compare reactive, proactive, and hybrid global scaling performance. From our comparison, proactive global scaling consistently outperforms reactive, while the hybrid solution is the best-performing one.