Abstract
DevOps represent the tight connection between development and operations. To address challenges that arise on the borderline 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.
Highlights
The software industry has gone through several revolutionary changes over the last decades
We explore and describe the existing DevOps environment and identify main challenges on the borderline between operations and development, using qualitative data collected through interviews and observations
We adhere to their proposed definition that “Continuous deployment is an operations practice where release candidates evaluated in continuous delivery are frequently and rapidly placed in a production environment”
Summary
The software industry has gone through several revolutionary changes over the last decades. We conducted a study in collaboration with a Swedish company responsible for ticket management and sales in public transportation Their main product is the back-end system for ticketing and payments, developed and operated in a DevOps environment using Microsoft services and tools. We explore and describe the existing DevOps environment and identify main challenges on the borderline between operations and development, using qualitative data collected through interviews and observations. To address the identified challenges, we design a solution for more effective processing of data available through the monitoring system in operations by introducing a smart filter in the feedback loop. We present a prototype implementation and validation of the proposed design It includes a description of the labeling process of unlabeled operations data, using unsupervised anomaly detection and considering the service vulnerabilities, as well as learning new advanced alert rules using a supervised, decision tree-based Python module.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
