Lightning Talk: Demystifying Kubernetes Observability with Generative AI and LLMs - Asaf Yigal

Achieving observability into Kubernetes is complex—far more than the early days of IT monitoring. K8s adds numerous layers of abstraction, mountains of data, and general confusion. Yet, even with this complexity, observability doesn’t have to be prohibitively complicated or expensive. The use of AI and LLMs provides significant promise in lending a hand to operators overwhelmed by K8s-related alerts. LLMs are adept at processing, learning and recognizing patterns in a large volume of repetitive textual data — precisely the nature of log data and other telemetry in highly distributed and dynamic systems. They can easily be applied to observability to provide meaningful recommendations. But LLMs are not a panacea. Let’s talk about the real value vs. inflated expectations. In this presentation we’ll explain how generative AI and LLMs represent an exciting opportunity for all organizations as they draft their K8s observability strategies and how you can get the most out of their tools.