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A scalable platform for monitoring data intensive applications

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Arquitectura de Computadores, Comunicaciones y Sistemases
dc.contributor.authorDrăgan, Ioan
dc.contributor.authorIuhasz, Gabriel
dc.contributor.authorPetcu, Dana
dc.contributor.funderEuropean Commissionen
dc.date.accessioned2020-04-22T11:17:26Z
dc.date.available2020-09-01T23:00:04Z
dc.date.issued2019-09
dc.descriptionASPIDE: Exascale programIng models for extreme data processing
dc.description.abstractLatest advances in information technology and the widespread growth in different areas are producing large amounts of data. Consequently, in the past decade a large number of distributed platforms for storing and processing large datasets have been proposed. Whether in development or in production, monitoring the applications running on these platforms is not an easy task, dedicated tools and platforms were proposed for this task yet none are specially designed for Big Data frameworks. In this paper we present a distributed, scalable, highly available platform able to collect, store, query and process monitoring data obtained from multiple Big Data frameworks. Alongside the architecture we experimentally show that the solution proposed is scalable and can handle a substantial quantity of monitoring data.en
dc.description.sponsorshipThis work has received funding from the EC-funded project H2020 DICE (Agreement 644869), which aims at providing a toolchain that makes the task of developing Big Data applications less daunting and the H2020 ASPIDE project (Agreement 801091). This work was partially supported by grants from Romanian Ministry of Research and Innovation, grant Acronim (PNIII-P4-ID-PCE-2016-0842) and grant BID (PNIII-P1-PDI-PFE-2018-028).en
dc.format.extent26es
dc.identifier.bibliographicCitationJournal of grid computing 17(3), Pp. 503-528en
dc.identifier.doihttps://doi.org/10.1007/s10723-019-09483-1
dc.identifier.issn1570-7873
dc.identifier.issn1572-9184 (online)
dc.identifier.publicationfirstpage503es
dc.identifier.publicationissue3es
dc.identifier.publicationlastpage528es
dc.identifier.publicationtitleJournal of grid computingen
dc.identifier.publicationvolume17es
dc.identifier.urihttps://hdl.handle.net/10016/30175
dc.language.isoengen
dc.publisherSpringer Nature B.V.en
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/644869/DICEes
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/801091/ASPIDEes
dc.rights© Springer Nature B.V.en
dc.rights.accessRightsopen accessen
dc.subject.ecienciaInformáticaes
dc.subject.otherBig dataen
dc.subject.otherCloud computingen
dc.subject.otherMonitoringen
dc.subject.otherBig data applicationsen
dc.subject.otherScalable monitoringen
dc.titleA scalable platform for monitoring data intensive applicationsen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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