Splunk Inc.

Hemendra Singh Choudhary

Tristan Antonio Fletcher

Fang I Hsiao

Brian John Bingham

Ross Andrew Lazerowitz

Vineetha Bettaiah

Alok Anant Bhide

Brian C Reyes

Cary Glen Noel

Clint Sharp

Chakravarthy Sridhar

An example method of identification of related event groups for a service monitoring system includes: receiving a sample set of events from a service monitoring system; choosing, based the sample set of events, a set of fieldnames for defining factors; generating a plurality of event group definitions, wherein each event group definition of the plurality of event group definitions comprises a plurality of factors, wherein each factor of the plurality of factors is represented by a respective fieldname-value pair of an event of the sample set of events, wherein a fieldname of the respective fieldname-value pair is selected from the set of fieldnames; and determining, based on the plurality of event group definitions, one or more event groups for a plurality of events.

Identification of related event groups for IT service monitoring system

A service monitoring system executing on one or more processors may have operations that are determined by control information. Control over the operation of the service monitoring system can be exerted through the use of a graphical interface. The graphical interface may present the control information of a new or existing correlation search definition for user interaction. The service monitoring system may maintain a data store of key performance indicator (KPI) data, where a KPI value in the data store is produced by a KPI-defining search query that derives the value from machine data associated with one or more entities that perform a monitored service. A correlation search definition of the service monitoring system determines how a search of the KPI data is conducted, how its data is evaluated to determine whether a triggering condition has been met, and, if so, determines what triggered action is to be initiated.

Performance monitoring using correlation search with triggering conditions

The operation of an automatic service monitoring system (SMS) is directed by stored control information. Methods and mechanisms are provided to create control information that directs operations of the SMS regarding the grouping together of related notable events for unified display and processing. The control information directs grouping operations that automatically correlate the events without requiring, for example, a set of declarative grouping rules.

Automatic creation of related event groups for an IT service monitoring system

A computing machine performs a correlation search against KPI data for one or more services using a selection criteria and a triggering condition. When the triggering condition is satisfied a notable event or incident is created and information about the notable event is presented using a user interface that may have interactive elements.

Incident review interface for a service monitoring system

A method is disclosed that includes receiving a request to display a service-monitoring user interface that illustrates performance of one or more services that are each provided by one or more entities. Each service is associated with a stored service definition that identifies the one or more entities, and each entity is associated with stored entity definition information that identifies machine data produced by or about the entity from one or more sources. The method further includes causing display of the service-monitoring user interface illustrating performance of each service via an aggregate key performance indicator (KPI) that characterizes a respective service as a whole, and a plurality of aspect KPIs that each characterize an aspect of an associated service. Each KPI is defined by a search query that produces a value derived from the machine data identified by the entity definition information, the value indicative of a measure of the service at a point in time or during a period of time. The machine data is produced by one or more components within an information technology environment and reflects activity within the information technology environment.

Service monitoring interface with an aggregate key performance indicator of a service and aspect key performance indicators of aspects of the service

Monitoring I.T. service-level performance using a machine data key performance indicator (KPI) correlation search

Techniques are disclosed for providing an aggregate key performance indicator (KPI) that spans multiple services and is based on a priority value. The techniques may enable a user to select KPIs and to adjust weights (e.g., importance) associated with the KPIs. The weight of a KPI may affect the influence a value of the KPI has on the calculation of an aggregate KPI value. The techniques may also include the ability to create a correlation search using the selected KPIs and weights so that a notification may be generated when the aggregate KPI value exceeds a threshold.

Aggregate key performance indicator spanning multiple services and based on a priority value

Services in an operating environment are represented by stored service definitions that identify entities that perform the service. Entity definitions identify machine data pertaining to the entity. A key performance indicator (KPI) of the service characterizes the service on the whole or some aspect of it. Each KPI is defined by a search query that derives a value from machine data identified in the entity definitions. Processing devices cause display of a service-monitoring page having services summary information and services aspects information. The summary information displays interactive summary tiles that each correspond to a service and present information about an aggregate KPI that characterizes the service. The aspects information displays interactive aspect tiles that each correspond to a KPI characterizing some aspect of an associated service. Additional information may be included in the service-monitoring page and interaction features enable a user to navigate to enhanced information displays.

Service monitoring interface with aspect and summary components

One or more processing devices derive values indicative of various aspects or characteristics of how a particular service in an information technology (IT) environment is existing or performing at a point in time or for a period of time. The values are derived by a search query over machine data associated with the one or more entities that provide the service. The one or more processing devices determine a value for an aggregate key performance indicator (KPI) for the service to indicate or characterize the service overall from values for each of the various aspects.

Monitoring an IT service at an overall level from machine data

Techniques are disclosed for providing an aggregate key performance indicator (KPI) that spans multiple services and for providing adjustment to KPI factors via a GUI that enables an aggregate KPI to be configured with feedback that better characterizes the performance of the services. The GUI may enable selection of KPIs and adjustment to weights (e.g., importance) associated with the KPIs. The weight of a KPI may affect the influence a value of the KPI has on the calculation of an aggregate KPI value (e.g., score). The GUI may provide near real-time feedback concerning the effect the weights have on the aggregate KPI value by displaying the aggregate KPI value (e.g., score) and updating the aggregate KPI value as the weights are adjusted.

Adjusting weights for aggregated key performance indicators that include a graphical control element of a graphical user interface

The operation of an automatic service monitoring system (SMS) is directed by stored control information. Methods and mechanisms are provided to create control information that directs operations of the SMS regarding the grouping together of related notable events for unified display and processing. The methods and mechanisms include interfacing with a user for selection of similarity scoring regimes for association with a particular field that are engaged for event grouping. The control information directs grouping operations that automatically correlate the events without requiring, for example, a set of declarative grouping rules.

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Sunnyvale, CA, United States of America

Hemendra Singh Choudhary