Tunable parameter settings for a distributed application

A technology is described for generating and modifying tunable parameter settings for use with a distributed application. An example method may include providing a first set of tunable parameter settings for a distributed application, where the first set of tunable parameter settings may be selected based at least in part on historical data associated with similar distributed applications. Performance metrics and implementation attributes associated with the distributed application may then be collected during a time period. The performance metrics and the implementation attributes collected may be input to a machine learning model configured to output a second set of tunable parameter settings for the distributed application, and the second set of tunable parameter settings may be provided for use with the distributed application, where performance of the distributed application may be better as compared to a performance using the first set of tunable parameter settings.