Experience report on applying software analytics in incident management of online service

Jian Guang Lou, Qingwei Lin, Rui Ding, Qiang Fu, Dongmei Zhang, Tao Xie

Research output: Contribution to journalArticle

Abstract

As online services become more and more popular, incident management has become a critical task that aims to minimize the service downtime and to ensure high quality of the provided services. In practice, incident management is conducted through analyzing a huge amount of monitoring data collected at runtime of a service. Such data-driven incident management faces several significant challenges such as the large data scale, complex problem space, and incomplete knowledge. To address these challenges, we carried out 2-year software-analytics research where we designed a set of novel data-driven techniques and developed an industrial system called the Service Analysis Studio (SAS) targeting real scenarios in a large-scale online service of Microsoft. SAS has been deployed to worldwide product datacenters and widely used by on-call engineers for incident management. This paper shares our experience about using software analytics to solve engineers pain points in incident management, the developed data-analysis techniques, and the lessons learned from the process of research development and technology transfer.

Original languageEnglish (US)
Pages (from-to)905-941
Number of pages37
JournalAutomated Software Engineering
Volume24
Issue number4
DOIs
StatePublished - Dec 1 2017

Keywords

  • Incident management
  • Online service
  • Service incident diagnosis
  • Software analytics

ASJC Scopus subject areas

  • Software

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