A computer-implemented method of optimizing or improving parameters for grouping differently sized object input/outputs, IOs, for key-value solid state drives, the method performed by a system having a target device, a training circuit and an inferencing circuit, the method comprising: receiving, by the target device, differently sized object IOs for the target device; grouping, by the target device, the IOs using a first plurality of input parameters; associating, by the target device, a tracking parameter with the first plurality of input parameters and with a performance parameter corresponding to the first plurality of input parameters; storing, by the target device, a first data entry comprising the tracking parameter, the first plurality of input parameters, and the performance parameter in a database; extracting, by the training circuit, a plurality of data entries which include the first data entry from the database; training, by the training circuit, a training model using one or more of the plurality of data entries; cross-validating, by the training circuit, the training model to determine error reduction of the training model; performing, by the training circuit, a model check to compare the error reduction of the training model to error reduction of an inferencing model; if the error reduction of the training model is greater than the error reduction of the inferencing model, then updating, by the training circuit, the inferencing model based on the training model; using, by the inferencing circuit, the updated inferencing model to infer suitable input parameters as a response to the performance parameter being outside of an expected range; performing, by the inferencing circuit, a parameter check by comparing the inferred input parameters to the input parameters of the target device; and if the inferred input parameters are different from the input parameters of the target device, then updating, by the inferencing circuit, the input parameters of the target device. receiving, by the target device, differently sized object IOs for the target device; grouping, by the target device, the IOs using a first plurality of input parameters; associating, by the target device, a tracking parameter with the first plurality of input parameters and with a performance parameter corresponding to the first plurality of input parameters; storing, by the target device, a first data entry comprising the tracking parameter, the first plurality of input parameters, and the performance parameter in a database; extracting, by the training circuit, a plurality of data entries which include the first data entry from the database; training, by the training circuit, a training model using one or more of the plurality of data entries; cross-validating, by the training circuit, the training model to determine error reduction of the training model; performing, by the training circuit, a model check to compare the error reduction of the training model to error reduction of an inferencing model; if the error reduction of the training model is greater than the error reduction of the inferencing model, then updating, by the training circuit, the inferencing model based on the training model; using, by the inferencing circuit, the updated inferencing model to infer suitable input parameters as a response to the performance parameter being outside of an expected range; performing, by the inferencing circuit, a parameter check by comparing the inferred input parameters to the input parameters of the target device; and if the inferred input parameters are different from the input parameters of the target device, then updating, by the inferencing circuit, the input parameters of the target device.