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WWT Research • Applied Research Report
• November 15, 2022 • 20 minute read

A Modular Approach to AIOps

Artificial Intelligence for IT Operations (AIOps) continues to become more mainstream. Learn how a modular approach to AIOps allows organizations to better leverage data to drive efficiency.

IT monitoring in the digital age

The Facebook outage in 2021, which lasted over seven hours, resulted in nearly $100 million in revenue loss for the company. As the world gets more connected, customer expectations have risen exponentially for quick, 24x7 seamless service across different touchpoints. This in turn is driving digital business transformation across the market resulting in large volumes of data (gigabytes per minute) across different domains. In this competitive environment, IT teams play a crucial role in ensuring that outages and other issues are predicted and resolved quickly. The growing volume of data presents huge challenges, but also opportunities to apply AI/ML to inform and automate IT system maintenance.

What is AIOps?  

AIOps is a discipline that involves people, process, culture and tools. There is no one tool or ecosystem of tools that is AIOps. AIOps enables the integration, correlation and automation to provide actionable insights to proactively identify and isolate potential business disruptions (fault-domain isolation to get the right teams engaged as early as possible to remediate issues).  A mature AIOps practice will be able to anticipate and invoke prescriptive self-healing measures via automation.  

Quite simply, AIOps translates to Artificial Intelligence for IT Operations with the eventual aim of achieving zero outages, zero downtime and fully automated resource allocation and event remediation.  

 

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