Impact of Cloud-Native CI/CD Pipelines on Deployment Efficiency in Enterprise Software

Abstract

Software Development Life Cycle (SDLC) is the fundamental concept which underlies the systematic development of a software product. It consists of requirements gathering, design of the application, development, testing, deployment & maintenance phases. Due to the increase in software complexity and the demand for fast delivery and continuous improvements, automation has become a key player in developing high-quality applications and maintaining them efficiently. On the other hand, with immense and continuous advancements happening in the Generative AI space, GenAI tools are emerging to be a powerful asset to automate repetitive tasks, enhance accuracy, and accelerate processes.

Combining the above, this paper describes the use of GenAI tools in automating different phases of SDLC, the issues and shortcomings associated with the traditional automation approach by depending on a single tool and emphasize the need for using specialized tools for effectively handling various phases of SDLC. We have explored and analyzed a tool named CrewAI, a robust orchestration framework, which has the capability of integrating several AI-powered tools across the different phases of SDLC, while ensuring smooth transition between all the SDLC life cycle phases, maintaining flexibility and efficiency. We have proposed a high-level design towards SDLC automation using CrewAI, along with the challenges that arise with respect to regulatory compliance, data security, and ethical considerations when using GenAI.