Enhancing Reliability in Distributed Systems: A Comprehensive Approach to Telemetry and Monitoring
DOI:
https://doi.org/10.32628/CSEIT241051051Keywords:
Distributed Systems Telemetry, Real-time Monitoring, Scalable Data Collection, driven Predictive Analytics, Automated Remediation TechniquesAbstract
This comprehensive article explores the implementation of telemetry and monitoring in distributed systems, addressing the challenges and opportunities in managing complex, scalable architectures. The article begins by examining the fundamental concepts of telemetry, including data collection methodologies, transmission protocols, and analysis techniques. It then provides an in-depth comparison of popular telemetry tools such as AWS CloudWatch and Prometheus, discussing their features, capabilities, and integration challenges. The article delves into effective monitoring strategies, emphasizing the importance of key performance indicators (KPIs) in distributed environments and the implementation of comprehensive solutions including real-time dashboards, proactive alert systems, and automated remediation techniques. Furthermore, the study investigates emerging trends in AI-driven monitoring and predictive analytics, highlighting their potential to revolutionize system observability. The article also addresses critical challenges facing the field, including scalability concerns in large-scale systems, privacy, and security considerations in telemetry data collection, and the need for balance between monitoring overhead and system performance. By synthesizing current practices with future directions, this article provides valuable insights for practitioners and researchers alike, contributing to the ongoing evolution of telemetry and monitoring practices in the rapidly advancing landscape of distributed computing.
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