Abstract: Provided are techniques for model generation for determining optimal components of a storage subsystem based on measurements and models. Data for a storage subsystem having a plurality of components is collected, where the data comprises data for application resources, data for workload measurements, metadata, tags, and policies, and wherein the data comprises volume specific characteristics and storage functions. A plurality of models are generated based on the collected data, where each of the models includes a subset of the plurality of components of the storage subsystem. Characteristics for a new storage subsystem are received. The characteristics are matched to a model of the plurality of models. A recommendation of components of the matching model is created to create the new storage subsystem.

Abstract: In one general embodiment, a computer-implemented method includes detecting individual sequential input/output (I/O) workloads in a stream of superimposed I/O workloads accessing a same physical volume. The detecting is based on a time dependency corresponding to accesses of blocks of the volume. In another general embodiment, a computer-implemented method includes detecting a plurality of sequential input/output (I/O) workloads in an I/O stream of superimposed workloads accessing a same volume, the detecting being based on a time dependency corresponding to accesses of blocks of the volume. A sequentiality factor is calculated for each of the sequential I/O workloads.