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@article{169033,
        author = {Saravanakumar Baskaran},
        title = {Predictive Maintenance in Cloud Services: Analyzing Infrastructure Health Using AI},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {9},
        number = {6},
        pages = {830-837},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169033},
        abstract = {As cloud computing continues to grow, ensuring the reliability of cloud infrastructure is a top priority for organizations. Predictive maintenance, powered by Artificial Intelligence (AI), provides a proactive approach to managing cloud environments by identifying potential issues before they cause downtime. This article explores how AI-driven predictive maintenance helps analyze infrastructure health, reduces operational disruptions, and optimizes resource management. By leveraging real-time data and predictive analytics, cloud service providers can detect anomalies, predict failures, and take preventive actions, thus improving overall system reliability and reducing maintenance costs. This article provides an in-depth analysis of the key components of AI-driven predictive maintenance and its impact on cloud services.},
        keywords = {Predictive Maintenance, Cloud Services, AI, Infrastructure Health, Real-Time Data, Anomaly Detection, Downtime Reduction, Proactive Maintenance},
        month = {November},
        }