Using ML to Automate Dynamic Error Categorization

Wednesday, June 12, 2019 - 3:00 pm3:30 pm

Antonio Davoli, Facebook

Abstract: 

Logs analysis and information extraction in highly dynamic production environments is a complicated task. This talk will present how we designed a platform that, by leveraging unsupervised machine learning techniques, is able to dynamically categorize errors on logs generated by several micro services in our provisioning pipeline. It will focus not only on how is it important to select the most appropriate clustering algorithm, but equally on how is fundamental to invest in production services with well defined logging.

Antonio Davoli, Facebook

Antonio Davoli is a Production Engineer at Facebook, where he is leading the usage of machine learning and data analytics techniques in the provisioning space. He has worked on distributed caching systems at Amazon AWS and on data mining solutions for the maritime and telecommunications industries.

BibTeX
@conference {233227,
author = {Antonio Davoli},
title = {Using {ML} to Automate Dynamic Error Categorization},
year = {2019},
address = {Singapore},
publisher = {{USENIX} Association},
}