International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | AI-Driven CI/CD Platform Reliability: A Framework for Intelligent Fault Detection, Predictive Maintenance, and Automated Recovery |
|---|---|
| ABSTRACT | Continuous Integration and Continuous Delivery (CI/CD) pipelines are the operational backbone of modern software delivery. As organizations scale these pipelines to support hundreds of microservices and thousands of daily deployments, ensuring platform reliability becomes a critical engineering challenge. This paper presents a framework for AI-Driven CI/CD Platform Reliability that integrates intelligent fault detection, predictive maintenance, and automated recovery mechanisms. The proposed system employs machine learning models trained on historical pipeline telemetry, build logs, and infrastructure metrics to identify anomalies before they cause service disruption. A predictive maintenance module anticipates component degradation and schedules preventive actions, while an automated recovery engine applies validated remediation playbooks in response to detected faults. Experimental evaluation on simulated and production-trace datasets demonstrates significant reductions in mean time to recovery (MTTR), pipeline failure rates, and manual operator interventions. The framework advances the state of intelligent DevOps by combining anomaly detection, time-series forecasting, and reinforcement-learning-based self-healing into a unified, extensible platform. |
| AUTHOR | SWAPNEEL G, SUJAN M A, SIDDARAJU H S, VISHWANATH B S, TALAKAL KRUSHNA, VINOD D, PROF. MANJULA P UG Students, Dept. of CSE, Jain Institute of Technology, Davangere, Karnataka, India Assistant Professor, Dept. of CSE, Jain Institute of Technology, Davangere, Karnataka, India |
| VOLUME | 184 |
| DOI | DOI: 10.15680/IJIRCCE.2026.1405063 |
| pdf/63_AI-Driven CI CD Platform Reliability A Framework for Intelligent Fault Detection, Predictive Maintenance, and Automated Recovery.pdf | |
| KEYWORDS | |
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