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@article{200946,
        author = {Dr.A.Jagan and Manikandan.N and Ganesh Kumar.S and Sanjay.T and Anush.D},
        title = {An Intelligent Cloud-Based Analytics System for Detecting Silent Failures in DevOps Pipelines},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {no},
        pages = {100-102},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=200946},
        abstract = {DevOps pipelines form the backbone of modern cloud-native software delivery by enabling continuous integration and continuous deployment (CI/CD). While DevOps significantly improves automation and deployment velocity, maintaining system reliability in dynamic cloud environments
remains a critical challenge. Existing monitoring solutions primarily rely on threshold-based alerting mechanisms, which are effective in detecting visible failures such as system crashes, service outages, and abrupt resource exhaustion. However, a large class of failures occur silently, where systems continue to function without triggering alerts while gradually degrading in performance. Such
silent failures often remain undetected until they severely impact user experience or cause complete system failure.
This project presents an intelligent cloudbased analytics system for detecting silent failures in DevOps pipelines through systematic analysis of cloud infrastructure metrics. The proposed system collects realtime performance metrics from cloud environments, preprocesses and structures the data, and applies time-series analytical techniques to identify long-term performance trends. Visualization is used as a primary mechanism to reveal gradual deviations and hidden anomalies that are not captured by traditional monitoring tools. Experimental evaluation using real cloud metrics obtained from AWS CloudWatch demonstrates that the proposed system enables early detection of silent failures, supports proactive maintenance strategies, improves system reliability, and operates effectively within cloud free-tier resource constraints.},
        keywords = {DevOps Pipelines, Silent Failures, Cloud Computing, Cloud Monitoring, Data Analytics, Time-Series Analysis, Performance Degradation, Visualization, AWS CloudWatch},
        month = {May},
        }