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PET: continuous performance evaluation tool

Authors:

Johannes Kroß,

Felix Willnecker,

Thomas Zwickl,

Helmut KrcmarAuthors Info & Claims

QUDOS 2016: Proceedings of the 2nd International Workshop on Quality-Aware DevOps

Pages 42 - 43

https://doi.org/10.1145/2945408.2945418

Published: 21 July 2016 Publication History

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Abstract

Performance measurements and simulations produce large amounts of data in a short period of time. Release cycles are getting shorter due to the DevOps movement and heavily rely on live data from production or test environments. In addition, performance simulations increasingly become accurate and close to exact predictions. Results from these simulations are reliable and can be compared with live data to detect deviations from expected behavior. In this work, we present a comprehensive tool that can process and analyze measurement as well as simulation data quickly utilizing big data technologies. Live measurement data and simulation results can be analyzed for detecting performance problems, deviations from expected behavior or to simply compare a performance model with real world applications.

References

[1]

A. Brunnert, A. van Hoorn, F. Willnecker, et al. Performance-oriented DevOps: A research agenda. Technical Report SPEC-RG-2015-01, SPEC Research Group — DevOps Performance Working Group, Standard Performance Evaluation Corporation, 2015.

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[2]

A. Brunnert, C. Vögele, A. Danciu, M. Pfaff, M. Mayer, and H. Krcmar. Performance management work. Business & Information Systems Engineering, 6(3):177–179, 2014.

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[3]

J. Humble and D. Farley. Continuous Delivery: Reliable Software Releases Through Build, Test, and Deployment Automation. Addison-Wesley Professional, 1st edition, 2010.

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[4]

5 http://pmw.fortiss.org/tools/pet/

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Cited By

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De Gyves Avila SCano PMejia AMoreno ILepe A(2019)A Data Driven Platform for Improving Performance Assessment of Software Defined Storage SolutionsTrends and Applications in Software Engineering10.1007/978-3-030-33547-2_20(266-275)Online publication date: 17-Oct-2019
https://doi.org/10.1007/978-3-030-33547-2_20
Willnecker FKrcmar H(2018)Multi-Objective Optimization of Deployment Topologies for Distributed ApplicationsACM Transactions on Internet Technology10.1145/310615818:2(1-21)Online publication date: 20-Jan-2018
https://dl.acm.org/doi/10.1145/3106158
Perez-Palacin DRidene YMerseguer JBinder WCortellessa VKoziolek ASmirni EPoess M(2017)Quality Assessment in DevOpsProceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion10.1145/3053600.3053632(133-138)Online publication date: 18-Apr-2017
https://dl.acm.org/doi/10.1145/3053600.3053632
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Index Terms

PET: continuous performance evaluation tool
1. Software and its engineering
  1. Software organization and properties
    1. Extra-functional properties
      1. Software performance

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Published In

QUDOS 2016: Proceedings of the 2nd International Workshop on Quality-Aware DevOps

July 2016

47 pages

ISBN:9781450344111

DOI:10.1145/2945408

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 21 July 2016

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ISSTA '16

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SIGSOFT

ISSTA '16: International Symposium on Software Testing and Analysis

July 21, 2016

Saarbrücken, Germany

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De Gyves Avila SCano PMejia AMoreno ILepe A(2019)A Data Driven Platform for Improving Performance Assessment of Software Defined Storage SolutionsTrends and Applications in Software Engineering10.1007/978-3-030-33547-2_20(266-275)Online publication date: 17-Oct-2019
https://doi.org/10.1007/978-3-030-33547-2_20
Willnecker FKrcmar H(2018)Multi-Objective Optimization of Deployment Topologies for Distributed ApplicationsACM Transactions on Internet Technology10.1145/310615818:2(1-21)Online publication date: 20-Jan-2018
https://dl.acm.org/doi/10.1145/3106158
Perez-Palacin DRidene YMerseguer JBinder WCortellessa VKoziolek ASmirni EPoess M(2017)Quality Assessment in DevOpsProceedings of the 8th ACM/SPEC on International Conference on Performance Engineering Companion10.1145/3053600.3053632(133-138)Online publication date: 18-Apr-2017
https://dl.acm.org/doi/10.1145/3053600.3053632
Stefan PHorky VBulej LTuma PBinder WCortellessa VKoziolek ASmirni EPoess M(2017)Unit Testing Performance in Java ProjectsProceedings of the 8th ACM/SPEC on International Conference on Performance Engineering10.1145/3030207.3030226(401-412)Online publication date: 17-Apr-2017
https://dl.acm.org/doi/10.1145/3030207.3030226

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Multi-layered Monitoring Framework with Indices Relationship Analysis for Distributed Service Performance Evaluation

Geo2Tag performance evaluation

Parallel Performance Visualization: From Practice to Theory

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