For Engineers, AI-Powered Observability Mesh Delivers ‘Clarity Through Connections'

The views and opinions expressed are those of Sai Krishna Cheemakurthi and do not reflect the views of any organization.

The biggest challenge in managing enterprise data is shifting from collection to interpretation. For years, organizations captured as much data as possible. But in large, complex systems, that approach often creates more confusion than clarity, leaving engineers to spend more time sorting through data than learning from it. Now, observability is transforming in response. Instead of seeing everything, the goal is recognizing what truly matters.

That’s the problem Sai Krishna Cheemakurthi, Vice President and Lead Infrastructure Architect at U.S. Bank, is working to solve. As an invitation-only member of the Forbes Technology Council and a Senior IEEE Member, Cheemakurthi is a technical architect and engineering leader specializing in AI and enterprise-scale observability, with over a decade of experience designing resilient platforms for global financial institutions. For Cheemakurthi, the solution is "observability mesh": an intelligent framework that actively interprets the meaning behind signals.

"The goal of the observability mesh is clarity through connections," Cheemakurthi said. In a recent Forbes Technology Council article, he explained how the mesh utilizes AI to unify an organization's data and identify hidden relationships—transforming millions of events into a handful of actionable insights with context.