Proactive-Reactive Auto-Scaling Mechanism for Unpredictable Load Change
Yoko Hirashima, Yamasaki Kenta, Masataka Nagura · 2016
The Elastic resource scaling for cloud service is widely studied to maintain service performance. Some studies proposed adjusting resource based on predicted workload in advance. However, real workload can grow regardless of the history. So we focus on a challenge to adopt such unpredictable load change. We proposed a new auto-scaling mechanism which changes the scale of target system based on predicted workload, moreover it instantly adds resource as remedy if unpredictable workload fluctuation detected. In this paper, we present the design and implementation, and then we evaluated effect of the mechanism using real workload history. Finally we confirmed it can improve service performance.