Publication: Towards low cost and smart load testing as a service using containers
dc.contributor.author | Baransel, Berrak Alara | |
dc.contributor.author | Peker, Alper | |
dc.contributor.author | Balkıs, Hilmi Ömer | |
dc.contributor.author | Arı, İsmail | |
dc.contributor.department | Computer Science | |
dc.contributor.ozuauthor | ARI, Ismail | |
dc.contributor.ozugradstudent | Baransel, Berrak Alara | |
dc.contributor.ozugradstudent | Peker, Alper | |
dc.contributor.ozugradstudent | Balkıs, Hilmi Ömer | |
dc.date.accessioned | 2023-05-25T11:46:15Z | |
dc.date.available | 2023-05-25T11:46:15Z | |
dc.date.issued | 2021 | |
dc.description.abstract | 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. | en_US |
dc.description.sponsorship | Ozyegin University ; Saha Information Technologies | |
dc.identifier.doi | 10.1007/978-3-030-71711-7_24 | en_US |
dc.identifier.endpage | 302 | en_US |
dc.identifier.isbn | 978-303071710-0 | |
dc.identifier.issn | 1865-0929 | en_US |
dc.identifier.scopus | 2-s2.0-85103500692 | |
dc.identifier.startpage | 292 | en_US |
dc.identifier.uri | http://hdl.handle.net/10679/8338 | |
dc.identifier.uri | https://doi.org/10.1007/978-3-030-71711-7_24 | |
dc.identifier.volume | 1382 | en_US |
dc.language.iso | eng | en_US |
dc.publicationstatus | Published | en_US |
dc.publisher | Springer | en_US |
dc.relation.ispartof | Communications in Computer and Information Science | |
dc.relation.publicationcategory | International | |
dc.rights | restrictedAccess | |
dc.subject.keywords | Cloud | en_US |
dc.subject.keywords | Container | en_US |
dc.subject.keywords | Django | en_US |
dc.subject.keywords | Docker | en_US |
dc.subject.keywords | Jmeter | en_US |
dc.subject.keywords | Kubernetes | en_US |
dc.subject.keywords | Load testing | en_US |
dc.title | Towards low cost and smart load testing as a service using containers | en_US |
dc.type | conferenceObject | en_US |
dc.type.subtype | Conference paper | |
dspace.entity.type | Publication | |
relation.isOrgUnitOfPublication | 85662e71-2a61-492a-b407-df4d38ab90d7 | |
relation.isOrgUnitOfPublication.latestForDiscovery | 85662e71-2a61-492a-b407-df4d38ab90d7 |
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