Towards low cost and smart load testing as a service using containers

Name: Towards low cost and smart load testing as a service using containers
Author: Baransel, Berrak Alara, Peker, Alper, Balkıs, Hilmi Ömer, Arı, İsmail

İsim	Towards low cost and smart load testing as a service using containers
Yazar	Baransel, Berrak Alara, Peker, Alper, Balkıs, Hilmi Ömer, Arı, İsmail
Basım Tarihi:	2021
Basım Yeri	- Springer
Konu	Cloud, Container, Django, Docker, Jmeter, Kubernetes, Load testing
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	978-303071710-0
Kayıt Numarası	a0f8391b-63e4-4c05-85cf-ab1f6abf966c
Lokasyon	Computer Science
Tarih	2021
Notlar	Ozyegin University ; Saha Information Technologies
Örnek Metin	Providing end-users with high quality e-commerce, online communication, education services requires careful performance monitoring, tuning and prediction under heavy traffic loads. To address this issue, we propose and evaluate a novel methodology using Docker containers for load testing. Our experience over several benchmarks, local machines vs. Cloud, and web servers suggest that load testing as a service requires a multi-dimensional optimization over slave counts, network latencies, bandwidth, and traffic patterns and there are opportunities for learning these parameters that can later be modelled into a smart load testing algorithm, with machine learning at the driver seat. Beyond the ease and speed of deployment, containers and cloud also provide a low cost alternative to load testing; we completed our cloud experiments by spending only $10. The only disadvantage of public clouds can be their centralized nature and distance to real customer bases.
DOI	10.1007/978-3-030-71711-7_24
Cilt	1382

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Towards low cost and smart load testing as a service using containers

Yazar Baransel, Berrak Alara, Peker, Alper, Balkıs, Hilmi Ömer, Arı, İsmail

Basım Tarihi 2021

Basım Yeri - Springer

Konu Cloud, Container, Django, Docker, Jmeter, Kubernetes, Load testing

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 978-303071710-0

Kayıt Numarası a0f8391b-63e4-4c05-85cf-ab1f6abf966c

Lokasyon Computer Science

Tarih 2021

Notlar Ozyegin University ; Saha Information Technologies

Örnek Metin Providing end-users with high quality e-commerce, online communication, education services requires careful performance monitoring, tuning and prediction under heavy traffic loads. To address this issue, we propose and evaluate a novel methodology using Docker containers for load testing. Our experience over several benchmarks, local machines vs. Cloud, and web servers suggest that load testing as a service requires a multi-dimensional optimization over slave counts, network latencies, bandwidth, and traffic patterns and there are opportunities for learning these parameters that can later be modelled into a smart load testing algorithm, with machine learning at the driver seat. Beyond the ease and speed of deployment, containers and cloud also provide a low cost alternative to load testing; we completed our cloud experiments by spending only $10. The only disadvantage of public clouds can be their centralized nature and distance to real customer bases.

DOI 10.1007/978-3-030-71711-7_24

Cilt 1382