1. A method for storage traffic modeling in a Software Defined Storage (SDS), comprising the steps of: collecting observed values of at least one performance parameter in a period of time from a storage node; learning a trend structure of the at least one performance parameter varying with time from the observed values; and providing a predicted value of one performance parameter in a particular point in time in the future, wherein the storage node is operated by SDS software, the trend structure is adjusted based on observed values collected after the period of time and the predicted value is an output of the trend structure which has been adjusted.