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Microservices: A Performance Tester's Dream or Nightmare? - Replication package

Simon Eismann; Cor-Paul Bezemer; Weiyi Shang; André van Hoorn; Dušan Okanović

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  <identifier identifierType="DOI">10.5281/zenodo.3611263</identifier>
      <creatorName>Simon Eismann</creatorName>
      <affiliation>University of Würzburg</affiliation>
      <creatorName>Cor-Paul	 Bezemer</creatorName>
      <affiliation>Queen's University</affiliation>
      <creatorName>Weiyi Shang</creatorName>
      <affiliation>Concordia University</affiliation>
      <creatorName>André van Hoorn</creatorName>
      <affiliation>University of Stuttgart</affiliation>
      <creatorName>Dušan Okanović</creatorName>
      <affiliation>University of Stuttgart</affiliation>
    <title>Microservices: A Performance Tester's Dream or Nightmare? - Replication package</title>
    <date dateType="Issued">2019-12-19</date>
  <resourceType resourceTypeGeneral="Software"/>
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    <relatedIdentifier relatedIdentifierType="DOI" relationType="IsVersionOf">10.5281/zenodo.3582707</relatedIdentifier>
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    <rights rightsURI="">Creative Commons Attribution 4.0 International</rights>
    <rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
    <description descriptionType="Abstract">&lt;p&gt;In recent years, there has been a shift in software development towards microservice-based architectures. In this paper, we discuss the benefits and challenges of microservices from a performance tester&amp;#39;s point of view. Through a series of experiments on the TeaStore application, we demonstrate how microservices affect the performance testing process, and we demonstrate that it is not straightforward to achieve reliable performance testing results for a microservice application.&lt;/p&gt;

&lt;p&gt;Reproducing the results from this paper consists of two parts, reproducing the performance measurements using TeaStore in the Google Kubernetes Engine and reproducing the analysis conducted in the paper based on the collected measurement data. In order to enable quick reproduction of the experiments, we packaged the scripts for the experiment automation as a docker container. The measurement data collected in this study and the scripts to reproduce the analysis presented in the paper are available in form of a CodeOcean capsule.&lt;/p&gt;</description>
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