"Engineering GitOps-Driven CI\/CD for DevOps and MLOps: Challenges, Toolchain, and a Proposed Framework"

"This research presents a GitOps-driven continuous integration and continuous deployment (CI\/CD) framework designed to unify DevOps and MLOps workflows in cloud-native environments. Traditional CI\/CD pipelines often struggle with configuration drift, limited automation, and lack of integration between application and machine learning lifecycles. To address these challenges, the proposed framework leverages a pull-based GitOps approach using tools such as GitHub Actions, Docker, Helm, ArgoCD, and Kubernetes, where Git acts as the single source of truth.The framework enables automated deployment, continuous reconciliation, and self-healing capabilities through declarative infrastructure management. A primary case study is conducted to evaluate the effectiveness of the framework, demonstrating significant improvements in deployment consistency, traceability, and operational efficiency. Experimental observations indicate a reduction in mean time to recovery (MTTR) by up to 85% compared to traditional manual deployment approaches.Furthermore, a comparative analysis with supporting studies highlights the advantages of the proposed approach in terms of scalability, automation, and reliability. The results confirm that integrating GitOps principles with DevOps and MLOps practices can effectively reduce deployment drift, enhance system resilience, and streamline end-to-end software and model delivery pipelines. This work provides a practical and scalable blueprint for modern cloud-native application and machine learning system deployment."