Emc IP Holding Company LLC

Sujan Kumar Shetty

Shelesh Chopra

Jaishree Balasubramanian

Rahul Deo Vishwakarma

Gopal Singh

Prasanth Balasubramanian

Sushanth Shet

Methods, apparatus, and processor-readable storage media for analyzing time series data for sets of devices using machine learning techniques are provided herein. An example computer-implemented method includes processing time series data from multiple devices; generating at least one data forecast by applying, in response to a request from at least one user, one or more machine learning techniques to at least a portion of the processed time series data; computing one or more qualifying values attributable to the at least one generated data forecast by providing the at least one generated data forecast and the at least a portion of the processed time series data to a conformal prediction framework; and performing one or more automated actions based at least in part on the at least one generated data forecast and the one or more computed qualifying values.

Analyzing time series data for sets of devices using machine learning techniques

A production host includes storage for storing backup priorities of entities and backup windows during which a system, of which the production host is a member, is predicted to have sufficient computing resources to generate a backup for an entity of the entities and a backup manager that identifies a backup generation event for the entity; in response to identifying the backup generation event: identifying an earliest potential backup window of the backup windows; making a determination that the earliest potential backup window of the backup windows is reserved for a second entity of the entities; in response to making the determination: identifying that a backup priority of the backup priorities that is associated with the entity is greater than a second backup priority of the backup priorities that is associated with the second entity; and providing the backup services to the entity during the earliest potential backup window.

System and method for prioritizing backup generation

A backup manager for providing backup services includes storage and a backup orchestrator. The persistent storage stores prediction models. The backup orchestrator obtains a computing resource availability for a client; generates a prediction model of the prediction models using the computing resource availability for the client; predicts, using the prediction model and live data, a future computing resource availability for the client; and initiates generation of a backup for the client at an unscheduled time that is based, at least in part, on the future computing resource availability.

System and method for backup scheduling using prediction models

A backup orchestrator for providing backup services to entities includes storage for storing backup windows during which backup storages are predicted to be able to service backup storage workloads; and a backup manager that identifies an occurrence of a backup generation event for an entity of the entities; in response to identifying the backup generation event: matches workload characteristics for generating a backup of the entity to a backup window of the backup windows that is associated with a backup storage of the backup storages; and generates the backup for the entity during the backup window and store the backup in the backup storage.

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Udupi, India

Sujan Kumar Shetty