HPE has launched InfoSight, a cloud-based AI recommendation engine for data centres, billed to boost business efficiency.

The analytics platform is designed to predict and prevent infrastructure issues before they occur. The technology’s basis in Machine Learning aims to make IT infrastructure autonomous, reducing staff time spent detecting and decoding problems.

In addition, Hewlett Packard Enterprise has also released InfoSight for HPE 3PAR, with the view to extending Machine Learning technology across their storage and server devices. The tech will be available for purchase in January 2018.Data centres

HPE claim InfoSight reduces time spent trouble-shooting by 85% and brings down storage IT OpEx by 79%. The recommendation engine uses “software-defined intelligence”, collecting data from thousands of embedded sensors, and auto-corrects potential infrastructure issues before they disrupt applications – in up to 86% of cases, according to HPE. Any particularly tricky issues encountered will be flagged to human IT staff along with suggested resolutions.

“HPE InfoSight marks the first time a major storage vendor has been able to predict issues and proactively resolve them before a customer is even aware of the problem,” said Bill Philbin, Senior Vice President at HPE GM Storage. “As applications increasingly drive today’s businesses, we need to help customers move toward a self-managing IT model. HPE InfoSight enables IT to spend more time on projects that add value to the business.”

 

The resulting increase in data speed delivery would theoretically quicken access to crucial business data. HPE is particularly proud of its 99.9999% guaranteed availability promise.

InfoSight is configured to work alongside 3PAR, as well as the existing HPE Nimble Storage is system, which boasts up to 20 TB, 2,045 TB effective capacity (assuming 5:1 data reduction from deduplication and compression) in its all-flash arrays.

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Data collected from individual data centres is fed to a novel cloud headquarters to feed a system of “global learning”, and improve AI functioning across its network of devices. Collated cross-stack analytics aid identification of issues between the storage and host virtual machines (VMs) and provide visibility to location “noisy neighbour” VMs.

Justin Giardina, CTO of iland Secure Cloud, said the tech makes “proactive decisions, showing us how we can improve our environment”, helping his firm provide 100% availability to customers.