Anomaly detection
First Claim
1. A method comprising:
- executing a search query over a period of time to produce values for a key performance indicator (KPI), the KPI associated with the search query that derives a value indicative of the performance of a service at a point in time or during a period of time, the value derived from machine data pertaining to one or more entities that provide the service;
causing for display a graphical user interface (GUI) comprising a first user-selectable interface element that enables a user to indicate a sensitivity setting and a second user-selectable interface element that enables the user to indicate a training window comprising an interval of time;
receiving, via the first and second user-selectable interface elements of the GUI, user input indicating the sensitivity setting and the training window;
identifying one or more of the values as anomalies based on the sensitivity setting and the training window indicated by the user input, the sensitivity setting establishing a threshold by which the one or more values are considered as the anomalies with respect to a deviation from historical values for the KPI, the historical values corresponding to the training window, wherein identifying one or more of the values as anomalies comprises comparing one of the values against a predicted value, the comparing including determining an error value and determining the position of the error value in a range of error values; and
causing for display, via an update to a graph in the GUI, information related to the values identified as anomalies to visually represent anomaly points in the graph, wherein the graph in the GUI is updated in real-time to visually represent new anomaly points corresponding to updated values identified based on received adjustments of the first and second user-selectable interface elements;
wherein the method is performed by a computer system comprising one or more processors.
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Abstract
Techniques are disclosed for anomaly detection. A search query can be executed over a period of time to produce values for a key performance indicator (KPI), the search query defining the KPI and deriving a value indicative of the performance of a service at a point in time or during a period of time, the value derived from machine data pertaining to one or more entities that provide the service. A graphical user interface (GUI) enabling a user to indicate a sensitivity setting can be displayed. A user input indicating the sensitivity setting can be received via the GUI. Zero or more of the values as anomalies can be identified in consideration of the sensitivity setting indicated by the user input. A GUI including information related to the values identified as anomalies can be caused to be displayed.
89 Citations
29 Claims
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1. A method comprising:
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executing a search query over a period of time to produce values for a key performance indicator (KPI), the KPI associated with the search query that derives a value indicative of the performance of a service at a point in time or during a period of time, the value derived from machine data pertaining to one or more entities that provide the service; causing for display a graphical user interface (GUI) comprising a first user-selectable interface element that enables a user to indicate a sensitivity setting and a second user-selectable interface element that enables the user to indicate a training window comprising an interval of time; receiving, via the first and second user-selectable interface elements of the GUI, user input indicating the sensitivity setting and the training window; identifying one or more of the values as anomalies based on the sensitivity setting and the training window indicated by the user input, the sensitivity setting establishing a threshold by which the one or more values are considered as the anomalies with respect to a deviation from historical values for the KPI, the historical values corresponding to the training window, wherein identifying one or more of the values as anomalies comprises comparing one of the values against a predicted value, the comparing including determining an error value and determining the position of the error value in a range of error values; and causing for display, via an update to a graph in the GUI, information related to the values identified as anomalies to visually represent anomaly points in the graph, wherein the graph in the GUI is updated in real-time to visually represent new anomaly points corresponding to updated values identified based on received adjustments of the first and second user-selectable interface elements; wherein the method is performed by a computer system comprising one or more processors. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27)
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28. A system comprising:
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a memory; and a processing device, operatively coupled to the memory, to; execute a search query over a period of time to produce values for a key performance indicator (KPI), the KPI associated with the search query that derives a value indicative of the performance of a service at a point in time or during a period of time, the value derived from machine data pertaining to one or more entities that provide the service; cause for display a graphical user interface (GUI) comprising a first user-selectable interface element that enables a user to indicate a sensitivity setting and a second user-selectable interface element that enables the user to indicate a training window comprising an interval of time; receive, via the first and second user-selectable interface elements of the GUI, user input indicating the sensitivity setting and the training window; identify one or more of the values as anomalies based on the sensitivity setting and the training window indicated by the user input, the sensitivity setting establishing a threshold by which the one or more values are considered as the anomalies with respect to a deviation from historical values for the KPI, the historical values corresponding to the training window, wherein identifying one or more of the values as anomalies comprises comparing one of the values against a predicted value, the comparing including determining an error value and determining the position of the error value in a range of error values; and cause for display, via an update to a graph in the GUI, information related to the values identified as anomalies to visually represent anomaly points in the graph, wherein the graph in the GUI is updated in real-time to visually represent new anomaly points corresponding to updated values identified based on received adjustments of the first and second user-selectable interface elements.
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29. A non-transitory computer readable medium having instructions encoded thereon that, when executed by a processing device, cause the processing device to:
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execute a search query over a period of time to produce values for a key performance indicator (KPI), the KPI associated with the search query that derives a value indicative of the performance of a service at a point in time or during a period of time, the value derived from machine data pertaining to one or more entities that provide the service; cause for display a graphical user interface (GUI) comprising a first user-selectable interface element that enables a user to indicate a sensitivity setting and a second user-selectable interface element that enables the user to indicate a training window comprising an interval of time; receive, via the first and second user-selectable interface elements of the GUI, user input indicating the sensitivity setting and the training window; identify one or more of the values as anomalies based on the sensitivity setting and the training window indicated by the user input, the sensitivity setting establishing a threshold by which the one or more values are considered as the anomalies with respect to a deviation from historical values for the KPI, the historical values corresponding to the training window, wherein identifying one or more of the values as anomalies comprises comparing one of the values against a predicted value, the comparing including determining an error value and determining the position of the error value in a range of error values; and cause for display, via an update to a graph in the GUI, information related to the values identified as anomalies to visually represent anomaly points in the graph, wherein the graph in the GUI is updated in real-time to visually represent new anomaly points corresponding to updated values identified based on received adjustments of the first and second user-selectable interface elements.
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Specification