The Maturity Model Framework for a Successful AI-Driven NOC
84% regularly learn about issues from end-users instead of their monitoring tools. While 95% say they don’t get ISP/Cloud data they need to effectively triage issues. An AI-driven NOC is only successful when it is fueled by intelligent data collected and analyzed from every hop in the client to cloud network path. In this session, learn how to mature your Network Observability practice so it intelligently feeds your AI-driven NOC-bot and provides the breadcrumbs you need to prove your innocence or pinpoint the root cause in seconds. So when you ask it “Where should I focus my attention this morning?”, it responds with, “Good morning, we seem to be getting help desk tickets from the Seattle office and according to the data, the edge Seattle office router is dropping packets above our 10% threshold.”
As the Chief Technical Evangelist for Network Observability by Broadcom, Jeremy is passionate about meeting with customers to identify their IT operational challenges and produce solutions that fit their business and network transformation goals. Prior to joining Broadcom, he spent over 15+ years working in IT, across both public and private sectors, managing data centers for startups, healthcare, financial and federal system integrators. His previous roles as a data center administrator, engineer, architect and manager provided him invaluable insights into the challenges and goals of IT consumers.
