Node.js scalability investigation in the cloud

Author: Zhu, Jiapeng; Patros, Panagiotis; Kent, Kenneth B.; Dawson, Michael

Date: 2018

Publisher: ACM

Type: Conference item

Link to this item using this URL: https://hdl.handle.net/10289/12862

University of Waikato

Abstract

Node.js has gained popularity in cloud development due to its asynchronous, non-blocking and event-driven nature. However, scalability issues can limit the number of concurrent requests while achieving an acceptable level of performance. To the best of our knowledge, no cloud-based benchmarks or metrics focusing on Node.js scalability exist. This paper presents the design and implementation of Ibenchjs, a scalability-oriented benchmarking framework, and a set of sample test applications. We deploy Ibenchjs in a local and isolated cloud to collect and report scalability-related measurements and issues of Node.js as well as performance bottlenecks. Our findings include: 1) the scaling performance of the tested Node.js test applications was sub-linear; 2) no improvements were measured when more CPUs were added without modifying the number of Node.js instances; and 3) leveraging cloud scaling solutions significantly outperformed Node.js-module-based scaling.

Subjects: computer science

Citation: ["Zhu, J., Patros, P., Kent, K. B., & Dawson, M. (2018). Node.js scalability investigation in the cloud. In A. Jaramillo, G.-V. Jourdan, D. Petriu, & W. Chen (Eds.), Proceeding of 28th Annual International Conference on Computer Science and Software Engineering (CASCON 2018) (pp. 201–212). New York, NY, USA: ACM."]

Copyright: © 2018 Copyright held by the author(s).