Collecting high-throughput telemetry and sensor events at the Kubernetes edge breaks when hitting real-world constraints: volatile WAN backhauls, intermittent network partitions, and strict hardware limits on remote gateways. Running heavy Java or Go-based logging agents on resource-constrained x86/ARM edge nodes eats up the exact memory needed for core workloads. When the uplink drops, unbuffered events are lost, while unchecked local disk buffering risks media wear and node panic.

This session delivers a pragmatic, production-ready architecture for edge data collection that survives network drops without exhausting local hardware limits. We break away from typical cloud-centric logging setups to build a rugged, asynchronous event pipeline tailored explicitly for disconnected edge nodes.

Attendees will learn:

Lightweight Kernel Hooks

Bounded Local Spillover

Backpressure-Aware Backhaul