Deployio – AI-Powered Devops Automation Platform

Authors

  • Dr R Guru Professor, Dept. of CSE, JSS Science and Technology University, Mysuru, Karnataka, India Author
  • Dr Anusuya M A Professor, Dept. of CSE, JSS Science and Technology University, Mysuru, Karnataka, India Author
  • Chaithanya S UG Student, Dept. of CSE, JSS Science and Technology University, Mysuru, Karnataka, India Author
  • Vasudev D M UG Student, Dept. of CSE, JSS Science and Technology University, Mysuru, Karnataka, India Author
  • Varsha M Vandaganoor UG Student, Dept. of CSE, JSS Science and Technology University, Mysuru, Karnataka, India Author
  • Pavan Gowda N UG Student, Dept. of CSE, JSS Science and Technology University, Mysuru, Karnataka, India Author

DOI:

https://doi.org/10.47392/IRJAEH.2026.0538

Keywords:

AI-assisted systems, CI/CD, cloud deployment, DevOps automation, Docker

Abstract

In the era of cloud-native applications and continuous delivery, DevOps automation has become a crucial part of the development process. However, the process of establishing deployment workflows, which encompasses environment setup, dependency management, CI/CD pipeline setup, and cloud provisioning, can be complex and prone to errors, especially for students and early-stage developers. In this paper, we introduce Deployio, a DevOps automation AI-powered system that aims to simplify the deployment of applications by providing an integrated and transparent approach. It automatically scans GitHub repositories to detect the technology stack, creates CI/CD pipelines, builds container images, and deploys applications to the cloud with minimal configuration. Our initial evaluation suggests that Deployio reduces configuration complexity, standardizes deployment workflows, and detects configuration problems early. The findings indicate that Deployio offers a good balance between automation and transparency, making it suitable for both deployment and educational purposes.

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Published

2026-06-10

How to Cite

Deployio – AI-Powered Devops Automation Platform. (2026). International Research Journal on Advanced Engineering Hub (IRJAEH), 4(06), 4165-4170. https://doi.org/10.47392/IRJAEH.2026.0538