Implementing Effective SLO Monitoring in High-Volume Data Processing Systems

Authors

  • Swethasri Kavuri  Independent Researcher, USA
  • Suman Narne  Independent Researcher, USA

DOI:

https://doi.org//10.32628/CSEIT206479

Keywords:

Service Level Objectives (SLOs), High-Volume Data Processing, Distributed Systems, Monitoring, Metrics, Instrumentation, Statistical Analysis, Machine Learning, Scalability, Real-Time Monitoring

Abstract

In the development of high-volume data processing systems, effective monitoring of Service Level Objective (SLO) turns out to be a crucial topic. The needs and importance of critical operations require large-scale data processing. Large-scale data processing necessitates maintaining the performance, reliability, and efficiency of such organizations. This research work focuses on the foundational principles of SLO monitoring, architectural considerations for high-volume data processing systems, and advanced techniques for implementing and scaling SLO monitoring solutions. The research includes areas like metric selection, instrumentation techniques, data collection strategies, statistical analysis, and emerging trends in the field. It is a synthesis of current literature and industry practices that presents an organized guide for organizations that want to implement robust SLO monitoring in their data processing infrastructure.

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2020-03-01

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Volume 6, Issue 2, March-April-2020

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[1]
Swethasri Kavuri, Suman Narne, " Implementing Effective SLO Monitoring in High-Volume Data Processing Systems, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 2, pp.558-578, March-April-2020. Available at doi : https://doi.org/10.32628/CSEIT206479