Abstract: One or more processing devices create one or more entity definitions that each associate an entity with machine data pertaining to that entity and create a service definition for a service provided by one or more entities. The service definition includes an entity definition for each of the one or more entities. The one or more processing devices create one or more key performance indicators (KPIs). Each KPI is defined by a search query that produces a value derived from the machine data identified in one or more of the entity definitions included in the service definition. Each value is indicative of how the service is performing at a point in time or during a period of time.

Abstract: One or more processing devices access a service definition for a service provided by one or more entities that each produce machine data or about which machine data is generated. The service definition identifies the entities that provide the service and, for each entity, identifying information for locating machine data pertaining to that entity. The processing devices access a key performance indicator (KPI) for the service that is defined by a search query that produces a value derived from the machine data pertaining to the entities identified in the service definition. The value indicates how the service is performing at a point in time or during a period of time and indicates a state of the KPI. A graphical interface is displayed and an indication of at least one threshold, which defines an end of a range of values representing a state of the KPI, for the KPI is received.

Abstract: A service monitoring system receives a selection of key performance indicators (KPIs) that each indicate a different aspect of how a service provided by one or more entities is performing. Each entity of the one or more entities produces machine data or wherein each entity has its operation reflected in machine data not produced by the entity. Each KPI is defined by a different search query that derives one or more values from the machine data pertaining to the one or more entities providing the service, where each of the one or more values is associated with a point in time and representing the aspect of how the service is performing at the associated point in time. For each of the selected KPIs, the service monitoring system derives the one or more values and causes display of a graphical visualization of the derived one or more values for the KPI along a time-based graph lane.

Abstract: Raw machine data are captured and may be organized as events. Entity definitions representing machine entities that perform a service identify the machine data pertaining to respective entities. KPI search queries each define a KPI. Each KPI search query derives one or more values for the KPI from machine data identified in the entity definitions. The derivation may be performed on a per-entity basis and on the aggregate. The derived values may then be translated into a state value domain using per-entity thresholds, aggregate thresholds, or a combination.

Abstract: 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 a services summary region and a services aspects region. The summary region displays interactive summary tiles that each correspond to a service and present information about an aggregate KPI that characterizes the service. The aspects region 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.

Abstract: A service monitoring system receives a selection of key performance indicators (KPIs) that each indicate a different aspect of how a service provided by one or more entities is performing. Each entity of the one or more entities produces machine data or wherein each entity has its operation reflected in machine data not produced by the entity. Each KPI is defined by a different search query that derives one or more values from the machine data pertaining to the one or more entities providing the service, where each of the one or more values is associated with a point in time and representing the aspect of how the service is performing at the associated point in time. For each of the selected KPIs, the service monitoring system derives the one or more values and causes display of a graphical visualization of the derived one or more values for the KPI along a time-based graph lane.

Abstract: 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 a services summary region and a services aspects region. The summary region displays interactive summary tiles that each correspond to a service and present information about an aggregate KPI that characterizes the service. The aspects region 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.

Abstract: One or more processing devices derive a value for each of a plurality of key performance indicators (KPIs). Each KPI indicates a different aspect of how the same service provided by one or more entities is performing at a point in time. Each KPI is defined by a search query that derives the value for that KPI from machine data associated with the one or more entities that provide the same service. The one or more processing devices calculate a value for an aggregate KPI for the same service from the values for each of the plurality of KPIs.

Abstract: An automatic service monitor in an information technology environment is equipped to automatically identify and group recognized events based on user-defined criteria, and to automatically perform user-defined operations against the group and its members at the detection of user-specified conditions.

Abstract: An automatic service monitor in an information technology environment is equipped to automatically identify and group recognized events based on user-defined criteria, and to automatically perform user-defined operations against the group and its members at the detection of user-specified conditions. A related user interface is taught.

Abstract: One or more processing devices derive values indicative of various aspects of how a particular service in an information technology (IT) environment is 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.

Abstract: An automatic service monitor in an information technology environment has its operation controlled by information that, in part, defines entities that perform services and defines key performance indicators (KPIs) that indicate measures of performance of the services. Additional information controls the operation of the service monitor with respect to identifying and adapting for KPIs based on the non-normal data caused by maintenance work or other causes. Such adaptation may include changes in how reported information appears to the user.

Abstract: Raw machine data are captured and may be organized as events. Entity definitions representing machine entities that perform a service identify the machine data pertaining to respective entities. KPI search queries each define a KPI. Each KPI search query derives one or more values for the KPI from machine data identified in the entity definitions. The derivation may be performed on a per-entity basis and on the aggregate. The derived values may then be translated into a state value domain using per-entity thresholds, aggregate thresholds, or a combination.

Abstract: Techniques are disclosed for providing a topology navigator that may enable a user to view performance information for multiple IT services associated with a user's IT environment. The topology navigator may include multiple display components for displaying information about the services. A first display component may display multiple services as a graph of interdependent service nodes and a second display component may display information about one or more of the service nodes. The topology navigator may enable a user to visually inspect the aggregate KPI (e.g., health score) of multiple services to identify dependent services that are of interest (e.g., low performance) and navigate through the services to identify dependent services that may adversely affect a service of interest to the user.

Abstract: An automatic service monitor in an information technology environment has its operation controlled by information that, in part, define entities that perform services and define key performance indicators (KPIs) that indicate measures of performance of the services. KPIs are defined in terms of search queries applied against machine data by or about the entities that perform the services. The search query aspects of multiple KPI definitions may be tied to a shared base search. Implementation of the shared base search may permit improved performance of the service monitor and may permit a reduction in administrative burden.

Abstract: Raw machine data are captured and may be organized as events. Entity definitions representing machine entities that perform a service identify the machine data pertaining to respective entities. KPI search queries each define a KPI. Each KPI search query derives one or more values for the KPI from machine data identified in the entity definitions. The derivation may be performed on a per-entity basis and on the aggregate. The derived values may then be translated into a state value domain using per-entity thresholds, aggregate thresholds, or a combination.

Abstract: 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.

Abstract: A services monitoring system causes display of time-based graphical visualizations that each correspond to a different key performance indicator (KPI) reflecting how a service provided by one or more entities is performing. The graphical visualizations are all calibrated to a same time scale. Each KPI is defined by a search query that derives one or more values reflected in the graphical visualization for that KPI from machine data pertaining to the one or more entities that provide the service corresponding to the KPI.

Abstract: Techniques are disclosed for providing an aggregate key performance indicator (KPI) that spans multiple services and for receiving user adjustment to KPI factors to configure an aggregate KPI (e.g., heath score). 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.

Abstract: Techniques are disclosed for providing an aggregate key performance indicator (KPI) that spans multiple services and for providing user adjustment to KPI factors via a GUI that enables a user to configure an aggregate KPI with feedback that better characterizes the performance of the services. The GUI 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 (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 user adjusts the weights.