Adopting DevOps practices in a software project
Karjalainen, Risto (2021)
2021
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2021121325563
https://urn.fi/URN:NBN:fi:amk-2021121325563
Tiivistelmä
Bittium Wireless Ltd., the client of this thesis project, has a software project with multiple variants and target platforms. The project did not have a DevOps toolchain, and its development workflow relied heavily on manual processes and lacked visibility into code quality and build status. The goals of this thesis were to identify problems in the old workflow, to implement a new tool-based workflow in order to address the problems, and finally to evaluate the efficacy of the new workflow both quantitatively and qualitatively.
To evaluate the success of the new toolchain, build success rates were examined of commits from before and after the adoption of the new toolchain. The study found that mainline builds were inconsistent for commits that were created before the adoption of the new toolchain, and 100% successful for commits that were created after the adoption of the new toolchain.
Semi-structured interviews were conducted for project members who experienced both workflows. All interviewees were satisfied with the new toolchain, seeing it as a positive factor for code and software quality. Especially code review and continuous integration were seen as beneficial, while SonarQube's code analysis gained less adoption.
To evaluate the success of the new toolchain, build success rates were examined of commits from before and after the adoption of the new toolchain. The study found that mainline builds were inconsistent for commits that were created before the adoption of the new toolchain, and 100% successful for commits that were created after the adoption of the new toolchain.
Semi-structured interviews were conducted for project members who experienced both workflows. All interviewees were satisfied with the new toolchain, seeing it as a positive factor for code and software quality. Especially code review and continuous integration were seen as beneficial, while SonarQube's code analysis gained less adoption.