# 007: Democratically Finding The Cause of Packet Drops

arXiv: https://arxiv.org/abs/1802.07222 · HTML: https://mlsanity.com/paper/1802.07222/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 20 Feb 2018.

## Built on by (most cited first, 4 of 4)

- [NTP-INT: Network Traffic Prediction-Driven In-band Network Telemetry for High-load Switches](https://mlsanity.com/paper/2502.12834/) (2025)
- [Collaborative AI Agents and Critics for Fault Detection and Cause Analysis in Network Telemetry](https://mlsanity.com/paper/2604.00319/) (2026)
- [The Abstention Protocol: RCA for Clos Fabrics](https://mlsanity.com/paper/2608.21412/) (2026)
- [Deploying RDMA for Distributed Inference and Training At Scale](https://mlsanity.com/paper/2610.12815/) (2026)

## Abstract (arXiv)

Network failures continue to plague datacenter operators as their symptoms may not have direct correlation with where or why they occur. We introduce 007, a lightweight, always-on diagnosis application that can find problematic links and also pinpoint problems for each TCP connection. 007 is completely contained within the end host. During its two month deployment in a tier-1 datacenter, it detected every problem found by previously deployed monitoring tools while also finding the sources of other problems previously undetected.