@inproceedings{yaseen2021towards,
author = {Yaseen, Nofel and Arzani, Behnaz and Chintalapudi, Krishna and Ranganathan, Vaishnavi and Vieira Frujeri, Felipe and Hsieh, Kevin and Berger, Daniel S. and Liu, Vincent and Kandula, Srikanth},
title = {Towards a Cost vs. Quality Sweet Spot for Monitoring Networks},
booktitle = {HotNets 2021},
year = {2021},
month = {November},
abstract = {Continuously monitoring a wide variety of performance and fault metrics has become a crucial part of operating large-scale datacenter networks. In this work, we ask whether we can reduce the costs to monitor -- in terms of collection, storage and analysis -- by judiciously controlling how much and which measurements we collect. By positing that we can treat almost all measured signals as sampled time-series, we show that we can use signal processing techniques such as the Nyquist-Shannon theorem to avoid wasteful data collection. We show that large savings appear possible by analyzing tens of popular measurements from a production datacenter network. We also discuss the technical challenges that must be solved when applying these techniques in practice.},
url = {http://approjects.co.za/?big=en-us/research/publication/towards-a-cost-vs-quality-sweet-spot-for-monitoring-networks/},
}