Pure Storage, Inc.

Apoorva Bansal

Lei Zhou

Farhan Abrol

Yi-Chin Wu

Chadd Kenney

Christopher Golden

Sergey Zhuravlev

Weizhong Hua

Loïc Magnin

Olivia Watkins

Jonathan Hayase

Nikita Bhargava

Migrating workloads between a plurality of execution environments, including: identifying, in dependence upon on characteristics of a workload, one or more execution environments that can support the workload; determining, for each execution environment, costs associated with supporting the workload on the execution environment; selecting, in dependence upon the costs associated with supporting the workload on each the execution environments, a target execution environment for supporting the workload; and executing the workload on the target execution environment.

Cost optimized workload placement

An exemplary security threat monitoring system receives performance metric data representative of a performance metric for a storage system, applies the performance metric data as an input to an unsupervised machine learning model, and identifies, based on an output of the unsupervised machine learning model, an anomaly in the performance metric data.

Security threat monitoring for a storage system

Presenting workload performance in a storage system, including: receiving, via a user interface, information describing a potential change to an execution environment of the storage system; and displaying, via the user interface and in dependence upon a load model and predicted characteristics of one or more workloads executing on the storage system, predicted performance load on the storage system that would result from implementing the potential change.

Presenting workload performance in a storage system

Migrating workloads between a plurality of execution environments

Growing community of inventors

Mountain View, CA, United States of America

Apoorva Bansal