Národní úložiště šedé literatury Nalezeno 2 záznamů.  Hledání trvalo 0.01 vteřin. 
Infrastructure for Testing and Deployment in the Field of Containers
Ormandy, Adam ; Lengál, Ondřej (oponent) ; Turoňová, Lenka (vedoucí práce)
Efficiency loss caused by repetitive manual tasks is a common problem throughout the IT sector. Developers often test, build, and deploy their software manually. That is not only time-consuming, but also dull and prone to errors and mistakes. This thesis tries to solve that in the context of one DevOps team, by unifying the development and testing tools, and by applying the principles of continuous integration and continuous deployment in the production environment. It is focused on Python, Jenkins, and container-based software and workflows. The main tools used in the thesis are GitLab CI, OpenShift and Tox. Thanks to work in described in the thesis, the number of projects with CI/CD pipelines increased from 7 to 50 percent, the amount of Python style violations started to decrease, containers have proper metadata, the container build process is automated, time and effort are saved by not doing repetitive tasks, and more.
Infrastructure for Testing and Deployment in the Field of Containers
Ormandy, Adam ; Lengál, Ondřej (oponent) ; Turoňová, Lenka (vedoucí práce)
Efficiency loss caused by repetitive manual tasks is a common problem throughout the IT sector. Developers often test, build, and deploy their software manually. That is not only time-consuming, but also dull and prone to errors and mistakes. This thesis tries to solve that in the context of one DevOps team, by unifying the development and testing tools, and by applying the principles of continuous integration and continuous deployment in the production environment. It is focused on Python, Jenkins, and container-based software and workflows. The main tools used in the thesis are GitLab CI, OpenShift and Tox. Thanks to work in described in the thesis, the number of projects with CI/CD pipelines increased from 7 to 50 percent, the amount of Python style violations started to decrease, containers have proper metadata, the container build process is automated, time and effort are saved by not doing repetitive tasks, and more.

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