3462820
doi
10.1109/eScience.2019.00093
oai:zenodo.org:3462820
user-envri
user-eu
Koulouzis, Spiros
University of Amsterdam
Zhao, Zhiming
University of Amsterdam
Contextual linking between workflow provenance and system performance logs
Ahanach, Elias el Khaldi
University of Amsterdam
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
scientific workflow
provenance
system logs
<p>When executing scientific workflows, anomalies of</p>
<p>the workflow behavior are often caused by different issues such</p>
<p>as resource failures at the underlying infrastructure. The provenance</p>
<p>information collected by workflow management systems</p>
<p>only captures the transformation of data at the workflow level.</p>
<p>Analyzing provenance information and apposite system metrics</p>
<p>requires expertise and manual effort. Moreover, it is often timeconsuming</p>
<p>to aggregate this information and correlate events</p>
<p>occurring at different levels of the infrastructure. In this paper,</p>
<p>we propose an architecture to automate the integration among</p>
<p>workflow provenance information and performance information</p>
<p>from the infrastructure level. Our architecture enables workflow</p>
<p>developers or domain scientists to effectively browse workflow</p>
<p>execution information together with the system metrics, and</p>
<p>analyze contextual information for possible anomalies.</p>
Zenodo
2019-09-26
info:eu-repo/semantics/conferencePaper
3462819
user-envri
user-eu
Camera ready
award_title=Environmental Research Infrastructures Providing Shared Solutions for Science and Society; award_number=654182; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/654182; funder_id=00k4n6c32; funder_name=European Commission;
award_title=smART socIal media eCOsytstem in a blockchaiN Federated environment; award_number=825134; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/825134; funder_id=00k4n6c32; funder_name=European Commission;
1579540894.63345
306924
md5:5e14919da7f87d0d9755217f44efebfe
https://zenodo.org/records/3462820/files/2019.conference.escience-poster-1.provenance.camera.pdf
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