Today, most organizations are transitioning from a traditional infrastructure of separate, static physical systems to a dynamic mix of on-premises, managed cloud, private cloud, and public cloud environments, running on virtualized or software-defined resources that scale and reconfigure constantly.
Applications and systems across these environments generate a tsunami of data that keeps growing. In fact, Gartner estimates that the average enterprise IT infrastructure generates two to three times more IT operations data every year.
Enter AIOps, which provides visibility into performance data and dependencies across all environments, analyzes the data to extract significant events related to slow-downs or outages, and automatically alerts IT staff to problems, their root causes, and recommended solutions.
Join us to discuss how IBM Watson AIOps brings transformative AI driven insights from structured and unstructured data across IT data sources delivered and market-leading real-time cross domain dynamic event, topology and metric analytics capabilities into one powerful AIOps solution.
Blair Lanier is an Offering Manager on the Watson AIOps team. Since joining IBM, she has focused on bringing AI capabilities to market to unlock human language and machine data to transform the ways people work. Blair previously worked in ag-tech, government-led economic development, and as the executive director of an education non-profit. She brings policy analysis and multi-stakeholder problem solving to the complex work of transforming business with AI.
Blair received a dual MBA and Masters of Public Policy from Duke University and a BA from Yale University. She and her husband run a small produce farm in Cincinnati, OH (and she enjoys talking about plants and bugs as much as AI for enterprise!).