CI-CD-Pipeline-Optimization-using-Jenkins-and-MLflow

Description

This project optimizes CI/CD pipelines using Jenkins and MLflow by using machine learning to predict build times based on historical data. By analyzing build trends, automating predictions, and implementing optimizations like parallel and incremental builds, it enhances deployment efficiency and reduces delays.

Languages and Utilities Used

• Python & Java
• Jenkins
• MLflow
• NumPy & Scikit-Learn
• Docker
• AWS
• Ubuntu

Project Walk-through

Set Up CI/CD with Jenkins


Gather and Log Build Data


Train a Predictive Model


Compare Predicted vs. Actual Build Times and Refine the Model