An Online Fault Detection Approachfor Web Applications

When the user interface of a web application reacts sluggish, or simple tasks suchas signing forms or saving data take unnecessary long time, the user experienceis diminished. Hence, one needs to monitor the working of this application,and undertake suitable action if such behavior is detected. This...

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Main Author: Åholm, Niklas
Format: Others
Language:English
Published: Uppsala universitet, Institutionen för informationsteknologi 2017
Subjects:
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-330459
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spelling ndltd-UPSALLA1-oai-DiVA.org-uu-3304592017-09-30T05:26:34ZAn Online Fault Detection Approachfor Web ApplicationsengÅholm, NiklasUppsala universitet, Institutionen för informationsteknologi2017Engineering and TechnologyTeknik och teknologierWhen the user interface of a web application reacts sluggish, or simple tasks suchas signing forms or saving data take unnecessary long time, the user experienceis diminished. Hence, one needs to monitor the working of this application,and undertake suitable action if such behavior is detected. This report exploreshow a method of Online Fault Detection (FADO) can be used to monitor thecondition of a web application. After reviewing the algorithm, results of thecase study are presented. The key insight is that the system is not so much interested in identifyingindividual request with an abnormally large response time, but in detectingsituations where such long response times are consistently present. That is,individual requests are aggregated into blocks which are evaluated together.We explore how to do this, and how this scheme interacts with the FADOalgorithm. The resulting system is compared to the existing system consistingof static thresholds, and it is indicated how the solution adapts to changingsituations. Finally this report presents some of the challenges and the di erentchoices one could make when deploying the FADO algorithm. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-330459UPTEC IT, 1401-5749 ; 17017application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Others
sources NDLTD
topic Engineering and Technology
Teknik och teknologier
spellingShingle Engineering and Technology
Teknik och teknologier
Åholm, Niklas
An Online Fault Detection Approachfor Web Applications
description When the user interface of a web application reacts sluggish, or simple tasks suchas signing forms or saving data take unnecessary long time, the user experienceis diminished. Hence, one needs to monitor the working of this application,and undertake suitable action if such behavior is detected. This report exploreshow a method of Online Fault Detection (FADO) can be used to monitor thecondition of a web application. After reviewing the algorithm, results of thecase study are presented. The key insight is that the system is not so much interested in identifyingindividual request with an abnormally large response time, but in detectingsituations where such long response times are consistently present. That is,individual requests are aggregated into blocks which are evaluated together.We explore how to do this, and how this scheme interacts with the FADOalgorithm. The resulting system is compared to the existing system consistingof static thresholds, and it is indicated how the solution adapts to changingsituations. Finally this report presents some of the challenges and the di erentchoices one could make when deploying the FADO algorithm.
author Åholm, Niklas
author_facet Åholm, Niklas
author_sort Åholm, Niklas
title An Online Fault Detection Approachfor Web Applications
title_short An Online Fault Detection Approachfor Web Applications
title_full An Online Fault Detection Approachfor Web Applications
title_fullStr An Online Fault Detection Approachfor Web Applications
title_full_unstemmed An Online Fault Detection Approachfor Web Applications
title_sort online fault detection approachfor web applications
publisher Uppsala universitet, Institutionen för informationsteknologi
publishDate 2017
url http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-330459
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