Deutsch Intern
Chair of Computer Science II - Software Engineering

BUNGEE

Update: This tool is no longer maintained and supported.

BUNGEE Cloud Elasticity Benchmark

BUNGEE is a Java based framework for benchmarking elasticity of IaaS cloud platforms. The tool automates the following benchmarking activities:

  1. A system analysis evaluates the load processing capabilities of the benchmarked platform at different scaling stages.
  2. The benchmark calibration uses the system analysis results and adjusts a given load intensity profile in a system specific manner.
  3. The measurement activity exposes the platform to a varying load according to the adjusted intensity profile.
  4. The elasticity evaluation measures the quality of the observed elastic behavior using a set of elasticity metrics.

BungeeDiagram

At the moment, BUNGEE supports to analyse the elasticity of CloudStack and Amazon Web Service (AWS) based clouds that scale CPU-bound virtual machines horizontally.

Links:

For more information, please contact Nikolas Herbst

The BUNGEE presentation at SEAMS2015 is available here.


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Publications

2019[ to top ]
  • Methoden und Messverfahren für Automatisches Skalieren in Elastischen Cloud Umgebungen. N. Herbst; (2019, Juni).
  • Chameleon: A Hybrid, Proactive Auto-Scaling Mechanism on a Level-Playing Field. A. Bauer; (2019, Juni).
  • Chameleon: A Hybrid, Proactive Auto-Scaling Mechanism on a Level-Playing Field. A. Bauer; N. Herbst; S. Spinner; A. Ali-Eldin; S. Kounev; in IEEE Transactions on Parallel and Distributed Systems (2019). 30(4) 800–813.
  • Systematic Search for Optimal Resource Configurations of Distributed Applications. A. Bauer; S. Eismann; J. Grohmann; N. Herbst; S. Kounev; in 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W) (2019). 120–125.
2018[ to top ]
  • Integrating Docker into the BUNGEE cloud elasticity benchmark. F. Roos; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2018, September).
  • Quantifying Cloud Performance and Dependability: Taxonomy, Metric Design, and Emerging Challenges. N. Herbst; A. Bauer; S. Kounev; G. Oikonomou; E. van Eyk; G. Kousiouris; A. Evangelinou; R. Krebs; T. Brecht; C. L. Abad; A. Iosup; in ACM Transactions on Modeling and Performance Evaluation of Computing Systems (ToMPECS) (2018). 3(4) 19:1–19:36.
  • Methods and Benchmarks for Auto-Scaling Mechanisms in Elastic Cloud Environments. N. Herbst; Thesis; University of Würzburg, Germany. (2018, Juli).
  • Elasticity Measurement in CaaS Environments - Extending the Existing BUNGEE Elasticity Benchmark to AWS’s Elastic Container Service. N. Limbourg; Thesis; Dublin Institute of Technology; Kevin Street, Dublin 2, D08 X622, Ireland. (2018, Juni).
  • Extending BUNGEE Elasticity Benchmark for Multi-Tier Cloud Applications. A. Bauer; (2018, April).
  • FOX: Cost-Awareness for Autonomic Resource Management in Public Clouds. V. Lesch; A. Bauer; N. Herbst; S. Kounev; in Proceedings of the 9th ACM/SPEC International Conference on Performance Engineering (ICPE 2018) (2018).
  • On the Value of Service Demand Estimation for Auto-Scaling. A. Bauer; J. Grohmann; N. Herbst; S. Kounev; in Proceedings of 19th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems (MMB 2018) (2018). (Bd. 10740) 142–156.
2017[ to top ]
  • Design and Evaluation of a Proactive, Application-Aware Auto-Scaler. A. Bauer; N. Herbst; S. Kounev; in Proceedings of the 8th ACM/SPEC International Conference on Performance Engineering (ICPE 2017) (2017).
  • Metrics and Benchmarks for Self-Aware Computing Systems. N. Herbst; S. Becker; S. Kounev; H. Koziolek; M. Maggio; A. Milenkoski; E. Smirni; in Self-Aware Computing Systems, S. Kounev, J. O. Kephart, A. Milenkoski, X. Zhu (Hrsg.) (2017).
  • Modeling and Extracting Load Intensity Profiles. J. von Kistowski; N. Herbst; S. Kounev; H. Groenda; C. Stier; S. Lehrig; in ACM Transactions on Autonomous and Adaptive Systems (TAAS) (2017). 11(4) 23:1–23:28.
  • Elasticity Benchmarking for Multi-Tier Cloud Applications. M. Wilhelm; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2017, Juni).
  • An Experimental Performance Evaluation of Autoscaling Policies for Complex Workflows. A. Ilyushkin; A. Ali-Eldin; N. Herbst; A. V. Papadopoulos; B. Ghit; D. Epema; A. Iosup; in Proceedings of the 8th ACM/SPEC International Conference on Performance Engineering (ICPE 2017) (2017).
  • Scalability Analysis of Cloud Software Services. G. Brataas; N. Herbst; S. Ivansek; J. Polutnik; in Companion Proceedings of the 14th IEEE International Conference on Autonomic Computing (ICAC 2017), Self Organizing Self Managing Clouds Workshop (SOSeMC 2017) (2017).
  • Self-Aware Multidimensional Auto-Scaling. V. Lesch; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2017, September).
2016[ to top ]
  • Design and Evaluation of a Proactive, Application-Aware Elasticity Mechanism. A. Bauer; (2016, November).
  • Design and Evaluation of a Proactive, Application-Aware Elasticity Mechanism. A. Bauer; Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2016, September).
  • Ready for Rain? A View from SPEC Research on the Future of Cloud Metrics. (SPEC-RG-2016-01), N. Herbst; R. Krebs; G. Oikonomou; G. Kousiouris; A. Evangelinou; A. Iosup; S. Kounev; (2016).
2015[ to top ]
  • BUNGEE: An Elasticity Benchmark for Self-Adaptive IaaS Cloud Environments. N. R. Herbst; S. Kounev; A. Weber; H. Groenda; in Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2015) (2015).
  • Load Testing Elasticity and Performance Isolation in Shared Execution Environments. S. Kounev; in Proceedings of the 4th International Workshop on Large-Scale Testing (LT 2015), co-located with the 6th ACM/SPEC International Conference on Performance Engineering (ICPE 2015) (2015).
2014[ to top ]
  • Quantitative Evaluation of Service Dependability in Shared Execution Environments (Extended Abstract of Keynote Talk). S. Kounev; in Proceedings of the 11th International Conference on Quantitative Evaluation of SysTems (QEST 2014), Florence, Italy (2014).
  • Resource Elasticity Benchmarking in Cloud Environments. A. Weber; Thesis; Karlsruhe Institute of Technology (KIT); Am Fasanengarten 5, 76131 Karlsruhe, Germany. (2014, August).
  • Towards a Resource Elasticity Benchmark for Cloud Environments. A. Weber; N. R. Herbst; H. Groenda; S. Kounev; in Proceedings of the 2nd International Workshop on Hot Topics in Cloud Service Scalability (HotTopiCS 2014), co-located with the 5th ACM/SPEC International Conference on Performance Engineering (ICPE 2014) (2014). 5:1–5:8.
2013[ to top ]
  • Elasticity in Cloud Computing: What it is, and What it is Not. N. R. Herbst; S. Kounev; R. Reussner; in Proceedings of the 10th International Conference on Autonomic Computing (ICAC 2013) (2013).