Optimizing Continuous Integration and Continuous Deployment (CI/CD) Pipelines: Strategies, Tools, and Performance Metrics
DOI:
https://doi.org/10.63282/3050-9416.IJAIBDCMS-V2I4P112Keywords:
Continuous Integration (CI), Continuous Deployment (CD), CI/CD pipelines, DevOps, DevSecOps, Pipeline optimization, Build automation, Deployment automation, Automated testing, Test automation frameworks, Infrastructure as Code (IaC), Configuration management, Version control systems, Git workflows, Branching strategies, Trunk-based development, Microservices architecture, Containerization, Docker, KubernetesAbstract
Continuous Integration and Continuous Deployment (CI/CD) have become central practices in modern software engineering, enhancing development velocity, reliability, and scalability. However, optimizing CI/CD pipelines to minimize latency, reduce resource usage, and improve deployment stability remains a critical research challenge. This study examines optimization techniques, tools, and architectural patterns for CI/CD systems, drawing upon literature from 2015–2021. Through comparative analysis of major CI/CD tools (Jenkins, GitLab CI, Travis CI, CircleCI), the paper explores methods to improve build efficiency, testing automation, and deployment workflows. Results suggest that pipeline optimization depends on three core factors: automation maturity, infrastructure scalability, and feedback loop efficiency. The paper concludes with recommendations for performance tuning and integrating machine learning-based optimization within CI/CD environments.
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