1. A system for training a modeler for a storage system providing service to a plurality of workloads comprising a foreground workload and a first set of at least two background workloads, the system comprising: computer hardware configured for: receiving a plurality of data sets, each data set comprising values for a plurality of input metrics of the foreground workload, values for the plurality of input metrics of the first set of background workloads, and a value for an output metric of the foreground workload; for each data set, summarizing the values received for each input metric of the first set of background workloads to produce a representative value for each input metric of the first set of background workloads; producing a plurality of tuple sets, each tuple set representing a data set, each tuple set comprising values for the plurality of input metrics of the foreground workload, the representative values for the plurality of input metrics of the first set of background workloads, and a value for the output metric of the foreground workload; and processing the plurality of tuple sets using machine learning to produce a function that maps the plurality of input metrics of the foreground workload and the first set of background workloads to the output metric of the foreground workload.