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An ever increasing number of configuration parameters are provided to systemusers. But many users have used one configuration setting across differentworkloads, leaving untapped the performance potential of systems. A goodconfiguration setting can greatly improve the performance of a deployed systemunder certain workloads. But with tens or hundreds of parameters, it becomes ahighly costly task to decide which configuration setting leads to the bestperformance. While such task requires the strong expertise in both the systemand the application, users commonly lack such expertise.  To help users tap the performance potential of systems, we presentBestConfig, a system for automatically finding a best configuration settingwithin a resource limit for a deployed system under a given applicationworkload. BestConfig is designed with an extensible architecture to automatethe configuration tuning for general systems. To tune system configurationswithin a resource limit, we propose the divide-and-diverge sampling method andthe recursive bound-and-search algorithm. BestConfig can improve the throughputof Tomcat by 75%, that of Cassandra by 63%, that of MySQL by 430%, and reducethe running time of Hive join job by about 50% and that of Spark join job byabout 80%, solely by configuration adjustment.

BestConfig: Tapping the Performance Potential of Systems via Automatic Configuration Tuning