ONUG will demonstrate a multi-domain data virtualization framework at its conference later this week in New York City.
The framework, which was developed by ONUG's AIOps for Hybrid Multi-Cloud Working Group, addresses the fundamental challenge of gathering disparate state data spread across multiple domains and providing unified access to normalized data by machine learning and AI tools.
The idea is to apply AI to automate performance monitoring to aggregate, normalize and enrich select state data that is sourced from many points across multiple independent domains.
“Just like a great wine starts with great grapes, great AIOps starts with great data,” says Nick Lippis, ONUG Co-Chair and Co-Founder. “The ONUG AIOps Working Group is addressing the fundamental challenge of gathering disparate state data spread across multiple domains and providing unified access to normalized data by machine learning and AI tools.”
“The growing adoption of Agile & DevOps is putting pressure on IT operations teams to quickly sort through the critical metrics, logs and traces generated by multiple monitoring systems that are tracking the performance of different applications, services, systems and networks on premises and in the cloud,” said Tsvi Gal, ONUG Board Member and Managing Director of Enterprise Infrastructure for Morgan Stanley. “Collecting all the raw telemetry data and storing it in a massive data lake without filtering and analytics is costly, slow and inefficient. ONUG’s AIOps initiative is a promising approach to selectively preparing and providing access and synthesis of the right datasets for automated AI-driven analysis and operations tools.”
The ONUG AIOps Working Group will discuss and demonstrate the progress of the framework on Thursday, October 17, 9:40am at the Metropolitan Pavilion in New York City.
https://www.onug.net/
