Abstract: An operational event processor receives information describing operational events arising in relation to a server cluster of a data intake and query system. Responsive actions are identified for the events that are actionable, and those responsive actions are automatically dispatched. Dispatching may include automatically causing the performance of the actions based on remembered preauthorizations, or automatically causing the performance of the actions based on obtaining real time user authorizations. The operational event processor may employ mechanisms to provide extensibility and a high degree of interoperability with other system components.

Abstract: Dynamic reassignment of search processes into workload pools includes receiving a search query to search at least one data store, assigning the search query to a first workload pool, and executing the search query using a first hardware resource in the first workload pool, the first hardware resource corresponding to a first portion of a hardware device. Dynamic reassignment further includes receiving, while executing the search query, an update command to move the search query to a second workload pool, moving, while executing the search query, the search query to the second workload pool; and continuing execution of the search query using a second hardware resource in the second workload pool. The second hardware resource corresponds to a second portion of the hardware device.

Abstract: A computer implemented system is described for assigning executable jobs to pipeline sets, whereby the jobs may be network based computer jobs. The assigning includes generating a weight for each pipeline set of multiple pipeline sets to obtain multiple weights. Generating a weight includes obtaining duty cycle metrics for pipeline software threads in the pipeline set. The duty cycle metrics include a measure of an amount of time that a corresponding pipeline thread is executing and actively processing data. Generating the weight further includes determining the weight for the pipeline set based at least in part on the duty cycle metrics. The method further includes assigning a job request to a target pipeline set selected from the pipeline sets according to a weighted random algorithm, wherein the weighted random algorithm uses the weights.

Abstract: Resegmenting chunks of data for load balancing is disclosed. A plurality of first chunks of data is received. The plurality of first chunks of data includes one or more entries that include raw data produced by a component of an information technology environment and that reflects activity in the information technology environment. The plurality of first chunks of data is resegmented into a plurality of second chunks of data based on entry boundaries in at least some of the plurality of first chunks of data. A first subset of the plurality of second chunks of data is distributed to a first indexer of a set of indexers. An occurrence of a trigger event is determined, and in response to the trigger event, a second subset of the plurality of second chunks of data is distributed to a second indexer of the set of indexers.

Abstract: Resegmenting chunks of data for load balancing is disclosed. A plurality of first chunks of data is received. The plurality of first chunks of data includes one or more entries that include raw data produced by a component of an information technology environment and that reflects activity in the information technology environment. The plurality of first chunks of data is resegmented into a plurality of second chunks of data based on entry boundaries in at least some of the plurality of first chunks of data. A first subset of the plurality of second chunks of data is distributed to a first indexer of a set of indexers. An occurrence of a trigger event is determined, and in response to the trigger event, a second subset of the plurality of second chunks of data is distributed to a second indexer of the set of indexers.

Abstract: Disclosed herein is a data estimation technique for a data intake and query system. The system receives user inputs indicative that a first data source is to be the subject of a storage related estimate. The system receives a first plurality of events generated by the first data source. The system indexes only a sample of the received first plurality of events, based on a sampling criterion, where the sample is fewer than all of the first plurality of events. The system generates the storage related estimate based on at least some of the first plurality of events, and causes an indication of the estimate to be output to a user.

Abstract: Disclosed herein is a data estimation technique for a data intake and query system. The system receives user inputs indicative that a first data source is to be the subject of a storage related estimate. The system receives a first plurality of events generated by the first data source. The system indexes only a sample of the received first plurality of events, based on a sampling criterion, where the sample is fewer than all of the first plurality of events. The system generates the storage related estimate based on at least some of the first plurality of events, and causes an indication of the estimate to be output to a user.

Abstract: Resegmenting chunks of data for load balancing is disclosed. A plurality of first chunks of data is received. The plurality of first chunks of data includes one or more entries that include raw data produced by a component of an information technology environment and that reflects activity in the information technology environment. The plurality of first chunks of data is resegmented into a plurality of second chunks of data based on entry boundaries in at least some of the plurality of first chunks of data. A first subset of the plurality of second chunks of data is distributed to a first indexer of a set of indexers. An occurrence of a trigger event is determined, and in response to the trigger event, a second subset of the plurality of second chunks of data is distributed to a second indexer of the set of indexers.