AI/ML-Integrated MLOps Framework for Autonomous DevOps Pipeline Optimization: A Technical Disclosure & Validation
Year: 2025
Type: article
Abstract: Traditional DevOps Pipelines Rely on Static Rules and Reactive Processes, Limiting Scalability & Reliability.This Work Proposes an AI/ML-Integrated MLOps Framework That Transforms Delivery Pipelines into Adaptive, Self-Optimizing Systems, By Learning from Code Changes, Infrastructure Signals and Operational Patterns, The Framework Predicts Deployment Risks, Detects Anomalies and Automates Decision-Making, The Result is a Proactive, Autonomous Pipeline Capable of Reducing Failures, Minimizing Manual Intervention and Accelerating Continuous Delivery.
Author: Ramzy, Mostafa
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7106497834
FWCI:
Cites:
Cited by:
Related to: