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Update: This tool is no longer maintained and supported.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:
- A system analysis evaluates the load processing capabilities of the benchmarked platform at different scaling stages.
- The benchmark calibration uses the system analysis results and adjusts a given load intensity profile in a system specific manner.
- The measurement activity exposes the platform to a varying load according to the adjusted intensity profile.
- The elasticity evaluation measures the quality of the observed elastic behavior using a set of elasticity metrics.
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:
- Download
- License
- Quick Start Guide (.pdf)
For more information, please contact Nikolas Herbst
The BUNGEE presentation at SEAMS2015 is available here.
Mailing List
Publications
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Systematic Search for Optimal Resource Configurations of Distributed Applications in 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W) (2019). 120–125.
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Methoden und Messverfahren für Automatisches Skalieren in Elastischen Cloud Umgebungen (2019, Juni).
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Chameleon: A Hybrid, Proactive Auto-Scaling Mechanism on a Level-Playing Field in IEEE Transactions on Parallel and Distributed Systems (2019). 30(4) 800–813.
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Chameleon: A Hybrid, Proactive Auto-Scaling Mechanism on a Level-Playing Field (2019, Juni).
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On the Value of Service Demand Estimation for Auto-Scaling in Proceedings of 19th International GI/ITG Conference on Measurement, Modelling and Evaluation of Computing Systems (MMB 2018) (2018). (Bd. 10740) 142–156.
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FOX: Cost-Awareness for Autonomic Resource Management in Public Clouds in Proceedings of the 9th ACM/SPEC International Conference on Performance Engineering (ICPE 2018) (2018).
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Quantifying Cloud Performance and Dependability: Taxonomy, Metric Design, and Emerging Challenges in ACM Transactions on Modeling and Performance Evaluation of Computing Systems (ToMPECS) (2018). 3(4) 19:1–19:36.
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Elasticity Measurement in CaaS Environments - Extending the Existing BUNGEE Elasticity Benchmark to AWS’s Elastic Container Service Thesis; Dublin Institute of Technology; Kevin Street, Dublin 2, D08 X622, Ireland. (2018, Juni).
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Methods and Benchmarks for Auto-Scaling Mechanisms in Elastic Cloud Environments Thesis; University of Würzburg, Germany. (2018, Juli).
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Integrating Docker into the BUNGEE cloud elasticity benchmark Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2018, September).
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Extending BUNGEE Elasticity Benchmark for Multi-Tier Cloud Applications (2018, April).
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Modeling and Extracting Load Intensity Profiles in ACM Transactions on Autonomous and Adaptive Systems (TAAS) (2017). 11(4) 23:1–23:28.
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Design and Evaluation of a Proactive, Application-Aware Auto-Scaler in Proceedings of the 8th ACM/SPEC International Conference on Performance Engineering (ICPE 2017) (2017).
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Elasticity Benchmarking for Multi-Tier Cloud Applications Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2017, Juni).
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Scalability Analysis of Cloud Software Services in Companion Proceedings of the 14th IEEE International Conference on Autonomic Computing (ICAC 2017), Self Organizing Self Managing Clouds Workshop (SOSeMC 2017) (2017).
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Metrics and Benchmarks for Self-Aware Computing Systems in Self-Aware Computing Systems, S. Kounev, J. O. Kephart, A. Milenkoski, X. Zhu (Hrsg.) (2017).
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Self-Aware Multidimensional Auto-Scaling Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2017, September).
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An Experimental Performance Evaluation of Autoscaling Policies for Complex Workflows in Proceedings of the 8th ACM/SPEC International Conference on Performance Engineering (ICPE 2017) (2017).
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Design and Evaluation of a Proactive, Application-Aware Elasticity Mechanism Thesis; University of Würzburg; Am Hubland, Informatikgebäude, 97074 Würzburg, Germany. (2016).
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Ready for Rain? A View from SPEC Research on the Future of Cloud Metrics (2016).
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Design and Evaluation of a Proactive, Application-Aware Elasticity Mechanism (2016, November).
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BUNGEE: An Elasticity Benchmark for Self-Adaptive IaaS Cloud Environments in Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2015) (2015).
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Load Testing Elasticity and Performance Isolation in Shared Execution Environments 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).
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Resource Elasticity Benchmarking in Cloud Environments Thesis; Karlsruhe Institute of Technology (KIT); Am Fasanengarten 5, 76131 Karlsruhe, Germany. (2014, August).
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Quantitative Evaluation of Service Dependability in Shared Execution Environments (Extended Abstract of Keynote Talk) in Proceedings of the 11th International Conference on Quantitative Evaluation of SysTems (QEST 2014), Florence, Italy (2014).
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Towards a Resource Elasticity Benchmark for Cloud Environments 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.
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Elasticity in Cloud Computing: What it is, and What it is Not in Proceedings of the 10th International Conference on Autonomic Computing (ICAC 2013) (2013).