3. Anomaly detection in cloud big database metric
Souvik Dutta Chowdhury, Shibakali Gupta · 2019
After cloudification of various big data sources or big databases, there is a need to monitor health and security metrics of these big databases.Now there is already a monitoring setup provided by various monitoring suites.The monitoring software collects various metrics with the help of custom codes, plugins, and so on.Here we are proposing a novel approach of modifying the normal metric thresholding to anomaly detection.Every system administrator has a common problem to deal with some intelligent alarm methods, which can produce predictive warnings, that is, the system can detect any anomalies or problem before it occurs.Here we are proposing an approach, which is basically a modification on standard monitoring where it will detect any anomalies by analyzing previous metric data and indicate any problem.We are planning to harness the power exponential moving average and exponential moving standard deviation method to implement the solution.