Conference paper Open Access

Contextual linking between workflow provenance and system performance logs

Ahanach, Elias el Khaldi; Koulouzis, Spiros; Zhao, Zhiming


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    <subfield code="a">&lt;p&gt;When executing scientific workflows, anomalies of&lt;/p&gt;

&lt;p&gt;the workflow behavior are often caused by different issues such&lt;/p&gt;

&lt;p&gt;as resource failures at the underlying infrastructure. The provenance&lt;/p&gt;

&lt;p&gt;information collected by workflow management systems&lt;/p&gt;

&lt;p&gt;only captures the transformation of data at the workflow level.&lt;/p&gt;

&lt;p&gt;Analyzing provenance information and apposite system metrics&lt;/p&gt;

&lt;p&gt;requires expertise and manual effort. Moreover, it is often timeconsuming&lt;/p&gt;

&lt;p&gt;to aggregate this information and correlate events&lt;/p&gt;

&lt;p&gt;occurring at different levels of the infrastructure. In this paper,&lt;/p&gt;

&lt;p&gt;we propose an architecture to automate the integration among&lt;/p&gt;

&lt;p&gt;workflow provenance information and performance information&lt;/p&gt;

&lt;p&gt;from the infrastructure level. Our architecture enables workflow&lt;/p&gt;

&lt;p&gt;developers or domain scientists to effectively browse workflow&lt;/p&gt;

&lt;p&gt;execution information together with the system metrics, and&lt;/p&gt;

&lt;p&gt;analyze contextual information for possible anomalies.&lt;/p&gt;</subfield>
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    <subfield code="a">10.1109/eScience.2019.00093</subfield>
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