Data Observability and Reliability in Modern Web Platforms: A Review of Instrumentation, Monitoring, and Automated Quality Pipelines
Keywords:
Data observability, web platform reliability, distributed tracing, monitoring automation, instrumentation frameworks, anomaly detection, site reliability engineering, quality pipelines, metrics collection, observability-driven developmentAbstract
This review discusses how web platforms maintain their reliability, speed, and ease of use. It brings togetherfifteen peer-reviewed papers from 2018-2022 on data observability and the reliability engineering of webplatforms. It discusses instrumentation, monitoring construction, automated quality pipelines, and observability tools supporting large systems.
References
Gan, Y., Liang, M., Dev, S., Lo, D., & Delimitrou, C. (2021). Sage: Leveraging ML to Diagnose Unpredictable Performance in Cloud Microservices. arXiv (Cornell University). https://doi.org/10.48550/arxiv.2112.06263
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Published
2023-05-20
How to Cite
Divyanshu Abhichandani, Prateik Mahendra. (2023). Data Observability and Reliability in Modern Web Platforms: A Review of Instrumentation, Monitoring, and Automated Quality Pipelines . Journal of Computational Analysis and Applications (JoCAAA), 31(4), 2374–2382. Retrieved from https://eudoxuspress.com/index.php/pub/article/view/4578
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