Beyond Reactive Security: Next-Gen Kubernetes Threat Hunting Powered by GenAI and eBPF

Unlock the future of Kubernetes security with GenAI and eBPF. Learn to predict, detect, and neutralize threats in real-time. This session reveals how AI and monitoring transform security strategies for engineers and platforms in fast-paced environments.

The need for proactive and predictive security measures has never been more urgent at a time when cyber threats are evolving faster than ever. This session will explore the state of Kubernetes security and present a new paradigm for detecting threats beyond traditional reactive approaches. We’ll look at how security engineers, DevSecs and Platform Engineers can radically change their safety posture by integrating Observability with new GenAI Artificial Intelligence based capabilities.

We’ll start by analyzing the complexity of the Kubernetes architecture and the unique security challenges it presents. Later in the session, attendees will gain insight into how eBPF (extended Berkeley Packet Filter) serves as the cornerstone for real-time kernel-level data collection and monitoring, providing unparalleled visibility into system calls and network traffic.

By leveraging GenAI’s adaptive algorithms, we will demonstrate how to anticipate, identify and neutralize advanced threats before they evolve into breaches. Attendees will learn how to harness GenAI’s machine learning prowess to automate threat detection, streamline incident response, and promote a security-first culture within their Kubernetes environments.