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US 2019/0102240 A1Published application
Plato anomaly detection
AssigneeAirMagnet, Inc.
InventorsDaniel Zarrini, Peter Reilly, Michael Faughan Sleevi
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Abstract
A method for continuous data anomaly detection includes identifying a period of time covered by metrics data stored in a repository. The stored metrics data is categorized into a plurality of non-overlapping time segments. Statistical analysis of the stored metrics data is performed based on the identified period of time. A range of acceptable metric values is dynamically generated based on the performed statistical analysis.
Claims20
A method for continuous data anomaly detection, the method comprising steps of:
- identifying, by a processor, a period of time covered by metrics data stored in a repository;
- categorizing, by a processor, the stored metrics data into a plurality of non-overlapping time segments;
- performing, by a processor, statistical analysis of the stored metrics data based on the identified period of time;
- and
- dynamically generating, by a processor, a range of acceptable metric values based on the performed statistical analysis.
2 more elements
A system for continuous data anomaly detection, the system comprising:
- a repository configured to store metrics data;
- and
- an information processing system comprising a processor and a memory device coupled to the processor in communication with the repository, the memory device containing a set of instructions that, when executed by the processor, cause the processor to:
- identify a period of time covered by the metrics data stored in the repository;
- categorize the stored metrics data into a plurality of non-overlapping time segments;
- perform statistical analysis of the stored metrics data based on the identified period of time;
- and
- dynamically generate a range of acceptable metric values based on the performed statistical analysis.
5 more elements
Dependencies are inferred from the claim text.