Network X-Ray Vision: Harnessing eBPF for Cloud-Native Observability Superpowers

Abstract

As Kubernetes clusters proliferate across enterprises, the invisible mesh of network communications has become a critical blind spot for operations teams. This presentation unveils how extended Berkeley Packet Filter (eBPF) technology fundamentally transforms network observability in cloud-native environments. Unlike conventional monitoring approaches that sample or aggregate data, eBPF delivers surgical precision by safely embedding observability directly into the Linux kernel, providing unprecedented visibility without performance penalties.

Through real-world implementation stories, you’ll discover how organizations have slashed their mean time to resolution (MTTR) by over 70% for complex networking issues. We’ll explore how eBPF enables teams to visualize previously invisible service-to-service dependencies, detect anomalous network behavior in real-time without costly packet captures, implement automated remediation workflows triggered by microsecond-level events, and optimize networking costs by identifying inefficient communication patterns.

This session bridges theory and practice, translating low-level kernel technology into actionable patterns that SREs and platform engineers can implement immediately. You’ll leave with practical strategies for deploying eBPF-based observability in your environment, regardless of your kernel expertise level.