Conference paper Open Access

Linking provenance with system logs: a context aware information integration and exploration framework for analyzing workflow execution

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


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  <identifier identifierType="DOI">10.5281/zenodo.3466766</identifier>
  <creators>
    <creator>
      <creatorName>el Khaldi Ahanach, Elias</creatorName>
      <givenName>Elias</givenName>
      <familyName>el Khaldi Ahanach</familyName>
      <affiliation>University of Amsterdam</affiliation>
    </creator>
    <creator>
      <creatorName>Koulouzis, Spiros</creatorName>
      <givenName>Spiros</givenName>
      <familyName>Koulouzis</familyName>
      <affiliation>University of Amsterdam</affiliation>
    </creator>
    <creator>
      <creatorName>Zhao, Zhiming</creatorName>
      <givenName>Zhiming</givenName>
      <familyName>Zhao</familyName>
      <nameIdentifier nameIdentifierScheme="ORCID" schemeURI="http://orcid.org/">0000-0002-6717-9418</nameIdentifier>
      <affiliation>University of Amsterdam</affiliation>
    </creator>
  </creators>
  <titles>
    <title>Linking provenance with system logs: a context aware information integration and exploration framework for analyzing workflow execution</title>
  </titles>
  <publisher>Zenodo</publisher>
  <publicationYear>2019</publicationYear>
  <dates>
    <date dateType="Issued">2019-10-01</date>
  </dates>
  <resourceType resourceTypeGeneral="Text">Conference paper</resourceType>
  <alternateIdentifiers>
    <alternateIdentifier alternateIdentifierType="url">https://zenodo.org/record/3466766</alternateIdentifier>
  </alternateIdentifiers>
  <relatedIdentifiers>
    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3466765</relatedIdentifier>
  </relatedIdentifiers>
  <version>Camera ready</version>
  <rightsList>
    <rights rightsURI="https://creativecommons.org/licenses/by/4.0/legalcode">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
  </rightsList>
  <descriptions>
    <description descriptionType="Abstract">&lt;p&gt;When executing scientific workflows in a distributed&lt;/p&gt;

&lt;p&gt;environment, anomalies of the workflow behavior are often&lt;/p&gt;

&lt;p&gt;caused by a mixture of different issues, e.g., careless design&lt;/p&gt;

&lt;p&gt;of the workflow logic, buggy workflow components, unexpected&lt;/p&gt;

&lt;p&gt;performance bottlenecks or resource failure at the underlying&lt;/p&gt;

&lt;p&gt;infrastructure. The provenance information only defines data&lt;/p&gt;

&lt;p&gt;evolution at the workflow level, which does not have an explicit&lt;/p&gt;

&lt;p&gt;connection with the system logs provided by the underlying&lt;/p&gt;

&lt;p&gt;infrastructure. Analyzing provenance information and apposite&lt;/p&gt;

&lt;p&gt;system metrics requires expertise and a considerable amount of&lt;/p&gt;

&lt;p&gt;manual effort. Moreover, it is often time-consuming to aggregate&lt;/p&gt;

&lt;p&gt;this information and correlate events occurring at different levels&lt;/p&gt;

&lt;p&gt;in the infrastructure. In this paper, we propose an architecture&lt;/p&gt;

&lt;p&gt;to automate the integration among the workflow provenance&lt;/p&gt;

&lt;p&gt;information with the performance information collected from&lt;/p&gt;

&lt;p&gt;infrastructure nodes running workflow tasks. Our architecture&lt;/p&gt;

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

&lt;p&gt;browse workflow execution information together with the system&lt;/p&gt;

&lt;p&gt;metrics, and analyze contextual information for possible anomalies.&lt;/p&gt;</description>
  </descriptions>
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      <funderName>European Commission</funderName>
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