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Using Predictive Monitoring Models in Cloud Computing Systems

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Distributed Computer and Communication Networks (DCCN 2018)

Abstract

Predictive modeling is an important part of the monitoring process in cloud computing systems that helps to improve the service availability for the customers. This paper describes two industrial examples of predictive monitoring models for database disk space utilization and Java memory leaks. Practical recommendations are given to improve the forecast accuracy, which can also be used in the other similar cases. The results of this work are validated in the open source monitoring system and are implemented in three big International telecommunications companies.

K. Kucherova—The publication has been prepared with the partial support of Genesys [4] and RingCentral [7] Telecommunications Companies, USA.

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References

  1. What We Learnt Talking to 60 Companies about Monitoring. Dataloop.IO. https://dataloopio.wordpress.com/2014/01/30/what-we-learnt-talking-to-60-companies-about-monitoring/

  2. Distillery LLC. https://www.distillery.com/

  3. Predictive trigger functions. In: Documentation Zabbix 3.0. https://www.zabbix.com/documentation/3.0/manual/config/triggers/prediction

  4. Genesys Telecommunications Laboratories. http://www.genesys.com/

  5. Kucherova, K., Mescheryakov, S., Shchemelinin, D.: Prediction experience and new model. In: The 7th Annual International Zabbix Conference, Riga, Latvia (2017). http://www.zabbix.com/conf2017_agenda.php

  6. Ardulov, Y., Shchemelinin, D., Mescheryakov, S.: Monitoring and remediation of cloud services based on 4R approach. In: Proceedings of the 41st International IT Capacity and Performance Conference by Computer Measurement Group (CMG 2015), San Antonio, TX, USA (2015). http://www.cmg.org/publications/conference-proceedings/conference-proceedings2015/

  7. RingCentral Inc. https://www.ringcentral.com/

  8. Kucherova, K.N., Mescheryakov, S.V., Shchemelinin, D.A.: Prediction Modeling and Visualization in Cloud Monitoring System. In: Distributed Computer and Communication Networks: Control, Computation, Communications (DCCN-2016): Proceedings of the 19th International Scientific Conference, Moscow, Russian University of People’s Friendship, vol. 1, pp. 222–230 (2016). https://www.dccn.ru/

  9. 86 Percent of Predictive Analytics Users Report Tangible Gains to Their Bottom Line. https://www.forbes.com/sites/forbespr/2015/10/27/86-percent-of-predictive-analytics-users-report-tangible-gains-to-their-bottom-line

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Acknowledgments

The results of this research are based on real production statistical data collected by Zabbix monitoring system [3] at big International IT companies – Distillery LLC [2], Genesys Telecommunications Laboratories [4], and RingCentral Inc. [7].

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Correspondence to Serg Mescheryakov .

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Kucherova, K., Mescheryakov, S., Shchemelinin, D. (2018). Using Predictive Monitoring Models in Cloud Computing Systems. In: Vishnevskiy, V., Kozyrev, D. (eds) Distributed Computer and Communication Networks. DCCN 2018. Communications in Computer and Information Science, vol 919. Springer, Cham. https://doi.org/10.1007/978-3-319-99447-5_29

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  • DOI: https://doi.org/10.1007/978-3-319-99447-5_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-99446-8

  • Online ISBN: 978-3-319-99447-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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