Reinventing Observability: AI-Driven Insights with Digital Twins and Large Language Models
Cloud-based microservices are increasingly complex, challenging human reasoning in diagnosing and resolving issues. This session demonstrates how integrating Digital Twins and Large Language Models enables teams to simulate scenarios and mitigate risks. We’ll examine how to harness Generative AI to transform different data streams from real and virtual environments into meaningful insights, reducing cognitive overload. You’ll learn how LLMs synthesize knowledge from graphs of historical states by highlighting critical patterns and accelerating root cause analysis and error propagation mitigation. Join us to discover how these advances deliver deeper system understanding, streamline decision-making, and foster smarter innovation amid operational uncertainty.
Wed 12 NovDisplayed time zone: Eastern Time (US & Canada) change
13:00 - 14:30 | |||
13:00 90mOther | WKS-69: 3rd Workshop on Continuous Operations using Generative AI (Part 1) COGAI | ||
13:00 15mTalk | Workshop Introduction COGAI | ||
13:15 25mTalk | State of the Art Gen AI Remediation in CP4AIOps for Cloud-Native Applications COGAI | ||
13:40 25mTalk | Reinventing Observability: AI-Driven Insights with Digital Twins and Large Language Models COGAI | ||
14:05 25mTalk | TBD COGAI Gabriel Tamura Universidad Icesi | ||