Modern CI/CD in Full-Stack Environments: Lessons from Source Control Migrations
Kiran Kumar Pappula · International Journal of Artificial Intelligence Data Science and Machine Learning · 2021
The paper will provide a detailed description of the case study of the designing, implementation and optimization of the unified Continuous Integration and Continuous Deployment (CI/CD) pipelines in the course of migration of the Microsoft Team Foundation Server (TFS) to the Azure DevOps on the full-stack development platform. The migration project aimed to update the source control infrastructure, automate deployment processes, and foster greater collaboration between cross-functional teams. The phased and incremental roll-out approach was used to maintain continuity of operations and reduce the risks associated with transitioning on a large scale. The technical solution involved secure builds, automation of quality gates, and a multi-stage orchestration of pipelines that could adapt to heterogeneous application stacks, providing consistency, reliability, and compliance across different environments. The evaluation step included a comparative analysis of the performance of the pipelines before and after migration through critical DevOps metrics, specifically decreasing build time, increasing deployment frequency, defect identification rate, and integration success. Migration paid off in terms of high performance as the average build time fell by up to 35 percent and deployment success rates increased by 28 percent. These technological improvements were followed by a more rigorous adherence to security and enhanced operational protection. Furthermore, the endeavour helped to align cultures and processes between development and operations teams, and foster a DevOps culture that focuses on collaboration, transparency, and iterative advancements. The results provide the takeaways and best practices that should apply to organizations that seek to modernize using CI/CD, including the necessity of a phased implementation, a security-oriented design, and evidence-based performance optimization in ensuring successful migration