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 language | English (US) |
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Pages (from-to) | 905-941 |
Number of pages | 37 |
Journal | Automated Software Engineering |
Volume | 24 |
Issue number | 4 |
DOIs | |
State | Published - Dec 1 2017 |
Keywords
- Incident management
- Online service
- Service incident diagnosis
- Software analytics
ASJC Scopus subject areas
- Software