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Efficient Monitoring of Time Series Data Using Dynamic Alerting

Girish L.*, Deepthi T. K.**

*Assistant Professor, Department of Computer Science and Engineering, Channabasaveshwara Institute of Technology, Gubbi, Karnataka, India.

**PG Student, Department of Computer Science and Engineering, Channabasaveshwara Institute of Technology, Gubbi, Karnataka, India.

Periodicity:June - August'2018
DOI : https://doi.org/10.26634/jcom.6.2.14870

Abstract

Network and Cloud Data Centers generate a lot of data every second, this data can be collected as a time series data. A time series is a sequence taken at successive equally spaced points in time, that means at a particular time interval to a specific time, the values of specific data that was taken is known as a data of a time series. This time series data can be collected using system metrics like CPU, Memory, and Disk utilization. The TICK Stack is an acronym for a platform of open source tools built to make collection, storage, graphing, and alerting on time series data incredibly easy. As a data collector, the authors are using both Telegraf and Collectd, for storing and analyzing data and the time series database InfluxDB. For plotting and visualizing, they use Chronograf along with Grafana. Kapacitor is used for alert refinement and once system metrics usage exceeds the specified threshold, the alert is generated and sends it to the system admin.

Keywords

Time Series Data, Influxdb, Alerts, Thersholding

How to Cite this Article?

Girish, L., & Deepthi ,T. K.(2018). Efficient Monitoring Of Time Series Data Using Dynamic Alerting. i-manager’s Journal on Computer Science, 6(2), 1-6. https://doi.org/10.26634/jcom.6.2.14870

References

[1]. Assfalg, J., Kriegel, H. P., Kroger, P., Kunath, P., Pryakhin, A., & Renz, M. (2006, July). Time series analysis using the concept of adaptable threshold similarity. In Scientific and Statistical Database Management, 2006. 18^th International Conference on (pp. 251-260). IEEE.

[2]. Bezerra, F. D. L., & Wainer, J. (2012). A dynamic threshold algorithm for anomaly detection in logs of process aware systems. Journal of Information and Data Management, 3(3), 316-331.

[3]. Chhetri, M. B., Vo, Q. B., & Kowalczyk, R. (2016, December). CL-SLAM: Cross-layer SLA monitoring framework for cloud service-based applications. In Utility and Cloud Computing (UCC), 2016 IEEE/ACM 9^th International Conference on (pp. 30-36). IEEE

[4]. Collectd. (n.d.). In OPNFV. Retrieved from https://wiki. opnfv.org/display/fastpath/Collectd+101

[5]. Girish, L., & Rao, S. K. (2016, December). Mathematical tools and methods for analysis of SDN: A comprehensive survey. In Contemporary Computing and Informatics (IC3I), 2016 2^nd International Conference on (pp. 718-724). IEEE.

[6]. Grafana. (n.d.). In Archlinux. Retrieved from https://wiki.archlinux.org/index.php/Grafana

[7]. Khanum, S., & Girish, L. (May 2015). Meta heuristic approach for task scheduling in cloud datacenter for optimum performance. International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), 4(5), 2070-2074.

[8]. Nayana, Y., Gopinath, J., & Girish, L. (2015). DDoS mitigation using Software Defined Network. International Journal of Engineering Trends and Technology (IJETT), 24(5), 258-264.

[9]. Rashmi, T. V., Prasanna, M. K., & Girish, L. (2015). Load balancing as a service in Openstack-Liberty. International Journal of Scientific & Technology Research, 4(8), 70-73.

[10]. Time Series. (n.d.). In Wikipedia. Retrieved from https://en.wikipedia.org/wiki/Time_series

[11]. The Time Series Database in the TICK Stack. (n.d.). In InfluxDB. Retrieved from https://www.influxdata. com/time- series-platform/influxdb/

[12]. TICK-stack. (n.d.). In Codeship. Retrieved from https://blog.codeship.com/infrastructure-monitoring with- tick-stack/

[13]. Thara, D. K., Premasudha, B. G., Ram, V. R., & Suma, R. (2016, December). Impact of big data in healthcare: A survey. In Contemporary Computing and Informatics (IC3I), 2016 2^nd International Conference on (pp. 729- 735). IEEE

[14]. Thara, D. K., & Girish, L. (May, 2015). Efficient virtual machine memory transfer in datacenter with optimal downtime. International Journal of Engineering Trends and Technology, 23(9), 454-458.

[15]. What is Telegraph. (n.d.). In Influxdata. Retrieved from https://support.influxdb.com/hc/en-us/articles/ 212832517

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