Scalable Infrastructure Monitoring and Alerting for Continuous Operation in Large-Scale IoT Software Platforms
Abstract
The increasing deployment of large-scale Internet of Things (IoT) services necessitates robust infrastructure monitoring and alerting systems to ensure continuous operation and high availability. This research paper presents a comprehensive study on scalable infrastructure monitoring and alerting frameworks specifically tailored for IoT software platforms. We explore the challenges associated with monitoring vast, distributed IoT networks and propose a methodology to detect and address anomalies in real-time. Our approach leverages advanced data analytics and machine learning techniques to enhance fault detection accuracy and reduce response times. We demonstrate the effectiveness of our solution through a case study of a large-scale IoT deployment, showcasing significant improvements in system uptime and reliability. The findings provide valuable insights for the development of resilient IoT infrastructures, enabling them to maintain seamless operations even in the face of unforeseen issues.
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