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AI Ops: Much more than a buzzword

WWT's Jas Binning: Teams must manage more complex environments, higher risks, larger volumes of data, and with fewer resources.

April 17, 2020 50 second read

by Jas Binning for Data Centre Dynamics Ltd.
OPINIONS | AI & MACHINE LEARNING

The job of an ops team has never been more important - or more challenging - than it is today.

Firstly, operational settings are becoming more complex, as businesses seek to adopt new capabilities, and in many cases, work towards a digital transformation strategy. Intricate workflows for a growing number of applications are increasingly sprawled across disparate cloud and on-premises environments.

A new consumer application, for example, may reside in the public cloud, but the data it needs to function could be stored in multiple places across a mixed and hybrid cloud environment. These increasingly expansive settings also create unprecedented levels of operational data, often leading to opaque alert storms that can make it harder still to pinpoint the source of a problem if and when it arises.

Secondly, pressures to resolve operational issues are greater than ever before. Gone are the days of overnight upgrades and downtime as standard.

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