DevOps : automatic monitoring in public safety applications
Abstract
Nowadays, the software is being developed in a rapidly changing and unpredictable market. Technologies and tools have evolved fast, and companies are increasingly dependent on effective communication and information. The DevOps model has also been built on these needs. The DevOps model has its roots in software development models such as Agile and Lean thinking. Essential components in the DevOps model include automation and continuous practices.
Public safety is an essential part of a functioning society. Public safety systems and applications provide, for example, a reliable way for authorities, such as police or fire services, to communicate quickly and seamlessly in critical situations. TETRA’s transition to the broader use of consumer LTE networks has been rapid in the public safety sector.
This research examines the DevOps principles of automation and automatic monitoring and how these principles are reflected in the public safety framework. The research has been executed in collaboration with the client company. The research combines a literature review and an empirical semi- structured interview.
The study revealed that there is no unambiguous definition for the DevOps model. The DevOps model can be seen as a methodology that affects the entire organizational culture. The main idea of the model is to break barriers between development and operations teams. According to the model, cooperation can be improved by improving communication, utilizing continuous practices, automation, and tools to streamline processes and avoid waste.
There are many automation tools available on the market, but implementing them into the current situation of the client company was seen as challenging. In the interviews, several themes emerged, which were seen as a challenge for implementing automation and automatic monitoring. Challenges included customers’ private networks and a reluctance to release data outside the organization. Challenges also included platforms and storing data.
Main Author
Format
Theses
Master thesis
Published
2021
Subjects
The permanent address of the publication
https://urn.fi/URN:NBN:fi:jyu-202108194598Use this for linking
Language
English
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The material is available for reading at the archive workstation of the University of Jyväskylä Library.
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