Analysis of User-Support Tickets in the Lifetime of the Blue Waters System

Abstract

We present an analysis of the collection of user support tickets created during nearly nine years of operation of the Blue Waters supercomputer. The analysis is based on information obtained from the Jira ticketing system and its corresponding queues. The paper contains a set of statistics showing, in quantitative form, the distribution of tickets across system areas. It also shows the computed metrics related to management of tickets by our staff. Additionally, we present an analysis, based on Machine Learning and Sentiment Analysis techniques, conducted over the text entered in tickets, targeting detecting trends on users' views and perspectives about the Blue Waters system. This kind of study, which is uncommon in the literature, could provide guidance for operators of future large systems about the expected volume of user support demanded by each system area, and about how to allocate support staff such that users receive the best possible assistance.