%0 Conference Paper %1 KiEiScBaGrKo2018-MASCOTS-TeaStore %A von Kistowski, Jóakim %A Eismann, Simon %A Schmitt, Norbert %A Bauer, André %A Grohmann, Johannes %A Kounev, Samuel %B Proceedings of the 26th IEEE International Symposium on the Modelling, Analysis, and Simulation of Computer and Telecommunication Systems %D 2018 %I IEEE Computer Society %K Design_of_software_and_systems Cloud Prediction t_full DML Metrics_and_benchmarking_methodologies Resource_management Elasticity Tool Power Performance myown select descartes %P 223--236 %R 10.1109/MASCOTS.2018.00030 %T TeaStore: A Micro-Service Reference Application for Benchmarking, Modeling and Resource Management Research %U https://doi.org/10.1109/MASCOTS.2018.00030 %X Modern distributed applications offer complex performance behavior and many degrees of freedom regarding deployment and configuration. Researchers employ various methods of analysis, modeling, and management that leverage these degrees of freedom to predict or improve non-functional properties of the software under consideration. In order to demonstrate and evaluate their applicability in the real world, methods resulting from such research areas require test and reference applications that offer a range of different behaviors, as well as the necessary degrees of freedom. Existing production software is often inaccessible for researchers or closed off to instrumentation. Existing testing and benchmarking frameworks, on the other hand, are either designed for specific testing scenarios, or they do not offer the necessary degrees of freedom. Further, most test applications are difficult to deploy and run, or are outdated. In this paper, we introduce the TeaStore, a state-of-the-art micro-service-based test and reference application. TeaStore offers services with different performance characteristics and many degrees of freedom regarding deployment and configuration to be used as a benchmarking framework for researchers. The TeaStore allows evaluating performance modeling and resource management techniques; it also offers instrumented variants to enable extensive run-time analysis. We demonstrate TeaStore's use in three contexts: performance modeling, cloud resource management, and energy efficiency analysis. Our experiments show that TeaStore can be used for evaluating novel approaches in these contexts and also motivates further research in the areas of performance modeling and resource management.

@inproceedings{KiEiScBaGrKo2018-MASCOTS-TeaStore, abstract = {Modern distributed applications offer complex performance behavior and many degrees of freedom regarding deployment and configuration. Researchers employ various methods of analysis, modeling, and management that leverage these degrees of freedom to predict or improve non-functional properties of the software under consideration. In order to demonstrate and evaluate their applicability in the real world, methods resulting from such research areas require test and reference applications that offer a range of different behaviors, as well as the necessary degrees of freedom. Existing production software is often inaccessible for researchers or closed off to instrumentation. Existing testing and benchmarking frameworks, on the other hand, are either designed for specific testing scenarios, or they do not offer the necessary degrees of freedom. Further, most test applications are difficult to deploy and run, or are outdated. In this paper, we introduce the TeaStore, a state-of-the-art micro-service-based test and reference application. TeaStore offers services with different performance characteristics and many degrees of freedom regarding deployment and configuration to be used as a benchmarking framework for researchers. The TeaStore allows evaluating performance modeling and resource management techniques; it also offers instrumented variants to enable extensive run-time analysis. We demonstrate TeaStore's use in three contexts: performance modeling, cloud resource management, and energy efficiency analysis. Our experiments show that TeaStore can be used for evaluating novel approaches in these contexts and also motivates further research in the areas of performance modeling and resource management.}, added-at = {2020-04-05T23:19:17.000+0200}, author = {von Kistowski, J{\'o}akim and Eismann, Simon and Schmitt, Norbert and Bauer, Andr{\'e} and Grohmann, Johannes and Kounev, Samuel}, biburl = {https://www.bibsonomy.org/bibtex/244cf2b8f9263b1d350826db8d0f1233f/andre.bauer}, booktitle = {Proceedings of the 26th IEEE International Symposium on the Modelling, Analysis, and Simulation of Computer and Telecommunication Systems}, doi = {10.1109/MASCOTS.2018.00030}, interhash = {68e6e9ea7e01092c4ad038cfc4ad7e0a}, intrahash = {44cf2b8f9263b1d350826db8d0f1233f}, keywords = {Design_of_software_and_systems Cloud Prediction t_full DML Metrics_and_benchmarking_methodologies Resource_management Elasticity Tool Power Performance myown select descartes}, month = {September}, note = {{Acceptance Rate: 29.5\% (23/78)}}, pages = {223--236}, publisher = {IEEE Computer Society}, series = {MASCOTS '18}, timestamp = {2022-11-16T09:10:53.000+0100}, title = {{TeaStore: A Micro-Service Reference Application for Benchmarking, Modeling and Resource Management Research}}, url = {https://doi.org/10.1109/MASCOTS.2018.00030}, venue = {Milwaukee, WI, USA}, year = 2018 }