Utilizing machine learning to streamline telemetry processing of storage media
AssigneePure Storage, Inc.
InventorsPrakash Darji, Andrew R. Bernat
Life of this patent
Estimating the term…
Abstract
Data associated with storage media utilized by one or more storage systems is received. The data is provided as an input to a machine learning model executed by a processing device. The machine learning model identifies one or more deterministic characteristics from the data. The one or more deterministic characteristics associated with the storage media are received from the machine learning model. A data structure comprising the one or more deterministic characteristics is generated for use in a telemetry process to qualify types of storage media.
Claims20
A system comprising:
- a memory;
- and
- a processing device, operatively coupled to the memory, to:
- receive data associated with storage media utilized by one or more storage systems;
- provide the data as an input to a machine learning model executed by the processing device, wherein the machine learning model identifies one or more deterministic characteristics of the storage media from the data;
- receive, from the machine learning model, the one or more deterministic characteristics associated with the storage media;
- and
- generate a data structure comprising the one or more deterministic characteristics for use in a telemetry process to qualify types of storage media.
A method, comprising:
- providing data associated with storage media utilized by one or more storage systems as an input to a machine learning model executed by a processing device;
- receiving, from the machine learning model, one or more deterministic characteristics associated with the storage media, wherein the one or more deterministic characteristics are determined by the machine learning model based on the data associated with the storage media;
- and
- generating, by the processing device, a data structure comprising the one or more deterministic characteristics for use in a telemetry process to qualify types of storage media.
A non-transitory computer readable storage medium storing instructions, which when executed, cause a processing device to:
- provide data associated with storage media utilized by one or more storage systems as an input to a machine learning model executed by the processing device;
- receive, from the machine learning model, one or more deterministic characteristics associated with the storage media, wherein the one or more deterministic characteristics are determined by the machine learning model based on the data associated with the storage media;
- and
- generate, by the processing device, a data structure comprising the one or more deterministic characteristics for use in a telemetry process to qualify types of storage media.
Dependencies are inferred from the claim text.