CI/CD Pipeline Optimization: Enhancing Deployment Speed and Reliability with AI and Github Actions

Authors: Ravi Chandra Thota

DOI: https://doi.org/10.37082/IJIRMPS.v8.i2.232185

Short DOI: https://doi.org/g86qjh

Country: USA

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Abstract: Modern software development follows CI/CD pipelines because they help deliver highly efficient and dependable software operations. Organizations losing their ability to fulfill market requirements through timely service delivery will become unsuccessful when they fail to solve deployment speed and reliability problems. The article highlights how GitHub Actions enhances CI/CD pipelines using Artificial Intelligence systems to create efficient workflows that automate deployment functions. AI-powered GitHub Actions allow efficient deployment results, reduce human errors, and minimize bottlenecks through flexible automation capabilities.
Systems using Artificial Intelligence in their Continuous Integration and Continuous Deployment pipelines perform automated decision execution after detecting anomalies and making predictive analyses. Teams rely on patterns from AI tool data processing to make strategic decisions that boost their CI/CD operational effectiveness. AI algorithms help organizations forecast code modification problems and notify developers of impending production failures. A proactive deployment method minimizes product failures while developing trustworthy software deployment systems, which leads to higher user satisfaction and software trust.
GitHub Actions functions independently to merge its AI optimization features with continuous development platforms, which allow developers to automate and control CI/CD operations in GitHub's environment. Inside programming, GitHub Actions enables developers to create automatic workflows that start upon particular events throughout the project, like code commits and pull requests. The success of automated workflows depends heavily on fast deployment processes and uninterrupted robotic deployment of integration operations. Organizations can benefit from an improved CI/CD pipeline using the strong AI-GitHub Actions connection, which delivers effective and dependable software releases that meet current user demands.

Keywords: CI/CD, Continuous Integration, Continuous Deployment, GitHub Actions, Automation, Deployment Speed, Reliability, Software Delivery, Version Control, Testing Automation, Code Quality, Anomaly Detection, Predictive Analytics, Workflow Management, Pull Requests, Integration Testing, Cloud Deployment, Efficiency, DevOps, Agile Development, Containerization, Monitoring, Notifications, Secrets Management, Infrastructure as Code, Performance Metrics, Collaboration, Error Reporting, Build Automation, Release Management

Paper Id: 232185

Published On: 2020-03-05

Published In: Volume 8, Issue 2, March-April 2020

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