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dc.contributor.authorWard, Jonathan Stuart
dc.contributor.authorBarker, Adam David
dc.date.accessioned2015-08-06T14:40:02Z
dc.date.available2015-08-06T14:40:02Z
dc.date.issued2015-07-14
dc.identifier207517766
dc.identifier6fd99f6d-c0cd-47bc-b191-6f16fd206615
dc.identifier85006233484
dc.identifier000215564300016
dc.identifier.citationWard , J S & Barker , A D 2015 , ' Cloud cover : monitoring large-scale clouds with Varanus ' , Journal of Cloud Computing: Advances, Systems and Applications , vol. 4 , 16 . https://doi.org/10.1186/s13677-015-0041-9en
dc.identifier.issn2192-113X
dc.identifier.urihttps://hdl.handle.net/10023/7140
dc.descriptionThis research was supported by a Royal Society Industry Fellowship and an Amazon Web Services (AWS) grant.en
dc.description.abstractCloud computing has quickly become the de facto means to deploy large scale systems in a robust and cost effective manner. Central to the maintenance of large scale systems is monitoring which allows for the detection of faults, errors and anomalies and the enacting of optimisation and corrective measures. Monitoring large scale systems is significant challenge requiring the low latency movement of large volumes of data and near real time analysis. This challenge is magnified by elasticity and other cloud properties which previous monitoring systems do not yet fully account for. In this paper we propose Varanus 1 a cloud aware monitoring tool that provides robust, fault tolerant monitoring at scale. We describe in detail the mechanisms which enable Varanus to function effectively and explore the performance of Varanus through a detailed evaluation.
dc.format.extent28
dc.format.extent4033507
dc.language.isoeng
dc.relation.ispartofJournal of Cloud Computing: Advances, Systems and Applicationsen
dc.subjectCloud computingen
dc.subjectMonitoringen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectNDASen
dc.subject.lccQA75en
dc.titleCloud cover : monitoring large-scale clouds with Varanusen
dc.typeJournal articleen
dc.contributor.sponsorThe Royal Societyen
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.identifier.doi10.1186/s13677-015-0041-9
dc.description.statusPeer revieweden
dc.identifier.grantnumberen


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