Cost-efficient auto-scaling of container-based elastic processes

• Published in: Future generation computer systems 2023-01, Vol.138, p.296-312
• Main Authors: Sheganaku, Gerta, Schulte, Stefan, Waibel, Philipp, Weber, Ingo
• Format: Article
• Language: English
• Subjects: Auto-scaling; BPM; Business process management; Cloud computing; Elastic computing; Elastic processes
• ISSN: 0167-739X; 1872-7115
• DOI: 10.1016/j.future.2022.09.001

In business process landscapes, a common challenge is to provide the necessary computational resources to enact the single process steps. One well-known approach to solve this issue in a cost-efficient way is to use the notion of elasticity, i.e., to provide cloud-based computational resources in a rapid fashion and to enact the single process steps on these resources. Existing approaches to provide elastic processes are mostly based on Virtual Machines (VMs). Utilizing container technologies could enable a more fine-grained allocation of process steps to computational resources, leading to a better resource utilization and improved cost efficiency. In this paper, we propose an approach to optimize resource allocation for elastic processes by applying a four-fold auto-scaling approach. The main goal is to minimize the cost of process enactments by using containers. To this end, we formulate and implement a multi-objective optimization problem applying Mixed-Integer Linear Programming and use a transformation step to allocate software services to containers. We thoroughly evaluate the optimization problem and show that it can lead to significant cost savings while maintaining Service Level Agreements, compared to approaches that only use VMs. •We define a system model for elastic processes.•We present an optimization model aiming at minimizing the total cost.•The model regards vertical and horizontal scaling of both VMs and containers.•The evaluation assesses the efficiency of the approach and SLA adherence.