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Closing the Feedback Loop in DevOps Through Autonomous Monitors in Operations

Hrusto, Adha LU orcid ; Runeson, Per LU orcid and Engström, Emelie LU orcid (2021) In SN Computer Science 2(6).
Abstract
DevOps represent the tight connection between development and operations. To address challenges that arise on the bor- derline between development and operations, we conducted a study in collaboration with a Swedish company responsible for ticket management and sales in public transportation. The aim of our study was to explore and describe the existing DevOps environment, as well as to identify how the feedback from operations can be improved, specifically with respect to the alerts sent from system operations. Our study complies with the basic principles of the design science paradigm, such as understanding and improving design solutions in the specific areas of practice. Our diagnosis, based on qualitative data collected through... (More)
DevOps represent the tight connection between development and operations. To address challenges that arise on the bor- derline between development and operations, we conducted a study in collaboration with a Swedish company responsible for ticket management and sales in public transportation. The aim of our study was to explore and describe the existing DevOps environment, as well as to identify how the feedback from operations can be improved, specifically with respect to the alerts sent from system operations. Our study complies with the basic principles of the design science paradigm, such as understanding and improving design solutions in the specific areas of practice. Our diagnosis, based on qualitative data collected through interviews and observations, shows that alert flooding is a challenge in the feedback loop, i.e. too much signals from operations create noise in the feedback loop. Therefore, we design a solution to improve the alert management by optimizing when to raise alerts and accordingly introducing a new element in the feedback loop, a smart filter. Moreover, we implemented a prototype of the proposed solution design and showed that a tighter relation between operations and development can be achieved, using a hybrid method which combines rule-based and unsupervised machine learning for operations data analysis. (Less)
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
DevOps, Development, Operations, Design science
in
SN Computer Science
volume
2
issue
6
article number
447
publisher
Springer Nature
external identifiers
  • scopus:85131822603
ISSN
2662-995X
DOI
10.1007/s42979-021-00826-y
project
WASP: Wallenberg AI, Autonomous Systems and Software Program at Lund University
Continuous Software Engineering
Continuous system testing using autonomous monitors
language
English
LU publication?
yes
id
dc0084af-fbd2-4d25-92ad-fa38fec816aa
date added to LUP
2021-09-15 15:50:48
date last changed
2024-05-02 05:38:12
@article{dc0084af-fbd2-4d25-92ad-fa38fec816aa,
  abstract     = {{DevOps represent the tight connection between development and operations. To address challenges that arise on the bor- derline between development and operations, we conducted a study in collaboration with a Swedish company responsible for ticket management and sales in public transportation. The aim of our study was to explore and describe the existing DevOps environment, as well as to identify how the feedback from operations can be improved, specifically with respect to the alerts sent from system operations. Our study complies with the basic principles of the design science paradigm, such as understanding and improving design solutions in the specific areas of practice. Our diagnosis, based on qualitative data collected through interviews and observations, shows that alert flooding is a challenge in the feedback loop, i.e. too much signals from operations create noise in the feedback loop. Therefore, we design a solution to improve the alert management by optimizing when to raise alerts and accordingly introducing a new element in the feedback loop, a smart filter. Moreover, we implemented a prototype of the proposed solution design and showed that a tighter relation between operations and development can be achieved, using a hybrid method which combines rule-based and unsupervised machine learning for operations data analysis.}},
  author       = {{Hrusto, Adha and Runeson, Per and Engström, Emelie}},
  issn         = {{2662-995X}},
  keywords     = {{DevOps; Development; Operations; Design science}},
  language     = {{eng}},
  month        = {{11}},
  number       = {{6}},
  publisher    = {{Springer Nature}},
  series       = {{SN Computer Science}},
  title        = {{Closing the Feedback Loop in DevOps Through Autonomous Monitors in Operations}},
  url          = {{http://dx.doi.org/10.1007/s42979-021-00826-y}},
  doi          = {{10.1007/s42979-021-00826-y}},
  volume       = {{2}},
  year         = {{2021}},
}