Kernel-Level Tracing at Fleet Scale: Why Host Agents Don't Add Up

Traditional observability agents running on each host consume significant resources at scale—at 2,000 GPU hosts, this translates to hundreds of GB of RAM and dozens of CPU cores dedicated to observability overhead alone. eBPF offers a kernel-level alternative that instruments once per host and serves all processes without modification, fundamentally changing the economics of AI infrastructure. As AI workloads scale, this efficiency advantage becomes critical to operational viability and cost management.