Usage-banded anomaly detection and remediation utilizing analysis of system metrics

A method comprising:

• collecting a set of data from an information processing system, wherein the set of data represents one or more system metrics associated with the information processing system;
• tagging data values in the collected set of data with usage bands selected from a plurality of predefined usage bands, wherein each usage band in the plurality of predefined usage bands represents a unique range of values within which data values in the set of data can be categorized;
• detecting one or more usage band anomalies associated with the one or more system metrics of the set of data and the tagged data values;
• segregating the tagged data values into at least a first set and a second set based on the usage bands, the first set containing data associated with the detected one or more usage band anomalies, and the second set containing data which does not belong to the first set;
• applying a first anomaly detection algorithm to the first set and a second anomaly detection algorithm to the second set to generate anomaly data sets;
• and
• mapping the anomaly data sets back to the collected set of data to identify one or more specific anomalies in the set of data;
• wherein the first anomaly detection algorithm searches for first data concentrations for at least the first set, and the second anomaly detection algorithm searches for second data concentrations for at least the second set;
• and
• wherein the steps are performed by at least one processing device, comprising a processor coupled to a memory, executing program code.

A computer program product comprising a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device cause the at least one processing device to:

• collect a set of data from an information processing system, wherein the set of data represents one or more system metrics associated with the information processing system;
• tag data values in the collected set of data with usage bands selected from a plurality of predefined usage bands, wherein each usage band in the plurality of predefined usage bands represents a unique range of values within which data values in the set of data can be categorized;
• detect one or more usage band anomalies associated with the one or more system metrics of the set of data and the tagged data values;
• segregate the tagged data values into at least a first set and a second set based on the usage bands, the first set containing data associated with the detected one or more usage band anomalies, and the second set containing data which does not belong to the first set;
• apply a first anomaly detection algorithm to the first set and a second anomaly detection algorithm to the second set to generate anomaly data sets;
• and
• map the anomaly data sets back to the collected set of data to identify one or more specific anomalies in the set of data;
• wherein the first anomaly detection algorithm searches for first data concentrations for at least the first set, and the second anomaly detection algorithm searches for second data concentrations for at least the second set.