Simulating and Evaluating a Real-World ElasticSearch System Using the RECAP DES Simulator

Malika Bendechache, Sergej Svorobej, Patricia Takako Endo, Adrian Mihai and Theo Lynn
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Malika Bendechache: School of Computing, Dublin City University, Dublin 9, Ireland
Sergej Svorobej: School of Computer Science and Statistics, Trinity College Dublin, Dublin 2, Ireland
Patricia Takako Endo: Caruaru Campus, Universidade de Pernambuco, Recife 50050-240, Pernambuco, Brazil
Adrian Mihai: Opening.io Company, Dublin 2, Ireland
Theo Lynn: Irish Institute of Digital Business, Dublin City University, Dublin 9, Ireland

Future Internet, 2021, vol. 13, issue 4, 1-12

Abstract: Simulation has become an indispensable technique for modelling and evaluating the performance of large-scale systems efficiently and at a relatively low cost. ElasticSearch (ES) is one of the most popular open source large-scale distributed data indexing systems worldwide. In this paper, we use the RECAP Discrete Event Simulator (DES) simulator, an extension of CloudSimPlus, to model and evaluate the performance of a real-world cloud-based ES deployment by an Irish small and medium-sized enterprise (SME), Opening.io. Following simulation experiments that explored how much query traffic the existing Opening.io architecture could cater for before performance degradation, a revised architecture was proposed, adding a new virtual machine in order to dissolve the bottleneck. The simulation results suggest that the proposed improved architecture can handle significantly larger query traffic (about 71% more) than the current architecture used by Opening.io. The results also suggest that the RECAP DES simulator is suitable for simulating ES systems and can help companies to understand their infrastructure bottlenecks under various traffic scenarios and inform optimisation and scalability decisions.

Keywords: simulation; modelling; ElasticSearch; DES; CloudSim; CloudSimPlus; query; workload; search engines (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2021
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