TY - JOUR
T1 - Experience report on applying software analytics in incident management of online service
AU - Lou, Jian Guang
AU - Lin, Qingwei
AU - Ding, Rui
AU - Fu, Qiang
AU - Zhang, Dongmei
AU - Xie, Tao
N1 - Publisher Copyright:
© 2017, Springer Science+Business Media, LLC.
PY - 2017/12/1
Y1 - 2017/12/1
N2 - 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.
AB - 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.
KW - Incident management
KW - Online service
KW - Service incident diagnosis
KW - Software analytics
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U2 - 10.1007/s10515-017-0218-1
DO - 10.1007/s10515-017-0218-1
M3 - Article
AN - SCOPUS:85021716287
VL - 24
SP - 905
EP - 941
JO - Automated Software Engineering
JF - Automated Software Engineering
SN - 0928-8910
IS - 4
ER -