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A tool automatically improving the performance of large-scale systems by finding better configuration settings

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Better Configurations for Large-Scale Systems (BestConfig)

Documentation | QuickStart | Use cases | FAQ

BestConfig is a system for automatically finding a best configuration setting within a resource limit for a deployed system under a given application workload. BestConfig is designed with an extensible architecture to automate the configuration tuning for general systems.

Currently, Bestconfig has been tested on the following systems. It has also been applied to the Huawei Cloud+ applications.

1. Spark (large-scale data processing engine)

2. Hadoop (distributed processing framework for big data)

3. Hive (big data warehouse)

4. MySQL (database)

5. Cassandra (NoSQL DB)

6. Tomcat (Web Server)

What’s New

Tutorial: Tuning Spark with BestConfig

Tutorial: Automatic Configuration Setting for Systems(in Chinese)

Results: Tuning Spark, Hadoop+Hive, MySQL, Cassandra, Tomcat+JVM

Ask a Question

Please use the bestconf/issues page; or

please contact us at: [email protected] or [email protected]

Related Publications

[1] Yuqing ZHU, Jianxun Liu, Mengying Guo, Yungang Bao, Wenlong Ma, Zhuoyue Liu, Kunpeng Song, Yingchun Yang. BestConfig: Tapping the Performance Potential of Systems via Automatic Configuration Tuning. Proceedings of the ACM Symposium on Cloud Computing 2017 (SoCC’17) (pdf, slides)

[2] Yuqing ZHU, Jianxun Liu, Mengying Guo, Yungang Bao. ACTS in Need: Automatic Configuration Tuning with Scalability. Proceedings of the 8th ACM SIGOPS Asia-Pacific Workshop on Systems (APSys’17) (pdf)

Acknowledgements

We thank Huawei for supporting this work. This work is also supported in part by the State Key Development Program for Basic Research of China (Grant No. 2014CB340402) and the National Natural Science Foundation of China (Grant No. 61303054).

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