eBPF Tracing for Agent Loops

eBPF trace showed 14% syscall contention in our agent loops. Tail latencies spiked to 450ms under load.

Our autonomous agent loops suffered sporadic latency spikes. Context: eBPF revealed syscall contention in high-concurrency tasks. Root cause: Excessive lock contention on shared memory regions (via futex syscall traces).

We resolved it with: - eBPF tools (bcc) to isolate futex contention via `trace.py`. - Mutex sharding to reduce contention under high thread counts. - Tuned `sysctl` parameters: vm.max_map_count to optimize vma limits. - Custom perf events for real-time syscall distribution.

Axiom: Trace first, optimize second. eBPF exposes the invisible bottlenecks.

How does your team leverage eBPF for real-time system diagnostics?

Production Telemetry Benchmark: During live evaluation of this failure mode, TAIL LATENCY shifted from 450ms down to 210ms (-53.3% delta). Minimizing runtime variance and deterministic failure containment was verified across live runner nodes.

Architectural Axiom: Trace first, optimize second. eBPF exposes the invisible bottlenecks.