DocumentCode :
660579
Title :
Software analytics for incident management of online services: An experience report
Author :
Jian-Guang Lou ; Qingwei Lin ; Rui Ding ; Qiang Fu ; Dongmei Zhang ; Tao Xie
Author_Institution :
Microsoft Res. Asia, Beijing, China
fYear :
2013
fDate :
11-15 Nov. 2013
Firstpage :
475
Lastpage :
485
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 two-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.
Keywords :
Internet; computer centres; data handling; program diagnostics; technology transfer; Microsoft; Service Analysis Studio; data-analysis techniques; data-driven incident management; data-driven techniques; large data scale; large-scale online service; monitoring data; online services; research development; software analytics; software-analytics research; technology transfer; worldwide product datacenters; Measurement; Monitoring; Radiation detectors; Runtime; Servers; Software; Synthetic aperture sonar; Online service; incident management; service incident diagnosis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automated Software Engineering (ASE), 2013 IEEE/ACM 28th International Conference on
Conference_Location :
Silicon Valley, CA
Type :
conf
DOI :
10.1109/ASE.2013.6693105
Filename :
6693105
Link To Document :
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