Comparative Analysis of Jenkins, GitLab CI, and GitHub Actions: Performance Evaluation in CI/CD Pipelines
Gajera, Aradhana Jr (2025)
2025
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-202505038792
https://urn.fi/URN:NBN:fi:amk-202505038792
Tiivistelmä
Continuous integration and continuous deployment (CI/CD) pipelines are essential parts of modern software engineering. They offer a systematic approach to build testing and deployment environments of applications along with error reduction as well as improved software quality with accelerated development cycles. There are not many studies that have been conducted on the evaluation of these CI/CD tools.
This study provides a comprehensive evaluation of the three widely used CI/CD tools: Jenkins, GitLab CI and Github Actions on different use case scenarios by examining quantitative metrics such as build times, resource utilization and error rates. The study also addresses practical consideration for tool selection making it easier for developers to select the tools according to their needs.
Keywords: CI/CD Pipelines, GitHub Actions, Jenkins, GitLab CI, Build Time Optimization, Continuous Integration, Continuous Deployment, Docker, AWS EC2, DevOps Performance, Automation in Software Development, Resource Utilization, Error Rate Analysis, Software Engineering
The originality of this thesis has been checked using Turnitin Originality Check service
This study provides a comprehensive evaluation of the three widely used CI/CD tools: Jenkins, GitLab CI and Github Actions on different use case scenarios by examining quantitative metrics such as build times, resource utilization and error rates. The study also addresses practical consideration for tool selection making it easier for developers to select the tools according to their needs.
Keywords: CI/CD Pipelines, GitHub Actions, Jenkins, GitLab CI, Build Time Optimization, Continuous Integration, Continuous Deployment, Docker, AWS EC2, DevOps Performance, Automation in Software Development, Resource Utilization, Error Rate Analysis, Software Engineering
The originality of this thesis has been checked using Turnitin Originality Check service