Vancouver, BC
May 21-24, 2018

Event Details

Please note: All times listed below are in Central Time Zone


Machine Learning for CI Results Analysis

Over the past few year we've increasingly been relying on data analytics and automation to keep on track of our increasing number of CI job results. With things like elastic recheck, subunit2sql, openstack-health, and grafana we've got an increasing number of tools to track results and provide insights into what's happening in the gate. But, even with all this data capture a great deal of the analysis has to happen by hand in these systems. Either by identifying things to track or combing through the data to find points of interest. It would be great if we could automate as much of that as possible, which is an a good application for machine learning.

This session is about bootstraping a community effort to build tooling to apply machine learning techniques to our CI results analysis to provide useful insights in an automated manner.

Monday, May 21, 3:10pm-3:50pm (10:10pm - 10:50pm UTC)
Difficulty Level: N/A
Open Source Software Engineer
Matthew has been working on and contributing to Open Source software for most of his career. He has been primarily contributing to OpenStack since 2012 and is a former member of the OpenStack TC (Technical Committee) and was previously the PTL (project technical lead) of the OpenStack community's QA program from OpenStack's Juno development cycle in 2014  through the Mitaka development... FULL PROFILE