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. The graph lanes for the selected KPIs are parallel to each other and the graphical visualizations in the graph lanes are all calibrated to a same time scale.

Defining a graphical visualization along a time-based graph lane using key performance indicators derived from machine data

Systems and methods are disclosed for associating an entity with a risk score that may indicate a security threat associated with the entity's activity An exemplary method may involve monitoring the activity of a subset of the set of entities (eg, entities included in a watch list) by executing a search query against events indicating the activity of the subset of entities The events may be associated with timestamps and may include machine data Executing the search query may produce search results that pertain to activity of a particular entity from the subset The search results may be evaluated based on a triggering condition corresponding to the statistical baseline When the triggering condition is met, a risk score for the particular entity may be updated The updated risk score may be displayed to a user via a graphical user interface (GUI)

User activity monitoring

Fields may be discovered in events that are returned in response to an initial search. The events may comprise portions of raw data. Furthermore, the fields may be defined by extraction rules for extracting values from corresponding portions of raw data. The displaying of a graphical user interface (GUI) may be caused where the GUI enables a user to select or enter criteria for a subset of the discovered fields without entering a search query in a search bar. At least one criterion for at least one field from the subset of the discovered fields may be received through a portion of the GUI that does not include a search bar for entering a search query. The events returned in response to the initial search query may be caused to be filtered based on the received criterion.

Discovering fields to filter data returned in response to a search

A processing device performs a search query to produce a search result set having entries having data items. Each data item has an ordinal position. A table, having rows and columns, is displayed in a graphical user interface. Each data item of a particular entry appears in a respective column of the same row of the table. Each column corresponds to the ordinal position of its respective data item. User input is received designating, for each respective column, a field name and an entity definition component type to which the respective column pertains, and stores for each data item of the particular entry an element value of an entity definition. The element has the element name designated for the respective column in which the data item appeared, and is associated with an entity definition component having the type designated for the respective column in which the data item appeared.

Creating an entity definition from a search result set

Processing devices receive a file having entries having data items separated by delimiters. Each data item has an ordinal position. The processing device(s) cause display of a table, having rows and columns, in a graphical user interface. Each data items of a particular entry appears in a respective column of the same row. Each column corresponds to the ordinal position of its respective data item. User input is received designating, for each respective column, a field name and an entity definition component type to which the respective column pertains, and stores for each of the data items of the particular entry a value of an element of an entity definition. The element has the element name designated for the respective column in which the data item appeared, and is associated with an entity definition component having the type designated for the respective column in which the data item appeared.

Creating an entity definition from a file

Embodiments are directed are towards the transparent summarization of events. Queries directed towards summarizing and reporting on event records may be received at a search head. Search heads may be associated with one more indexers containing event records. The search head may forward the query to the indexers the can resolve the query for concurrent execution. If a query is a collection query, indexers may generate summarization information based on event records located on the indexers. Event record fields included in the summarization information may be determined based on terms included in the collection query. If a query is a stats query, each indexer may generate a partial result set from previously generated summarization information, returning the partial result sets to the search head. Collection queries may be saved and scheduled to run and periodically update the summarization information.

Distributed high performance analytics store

Embodiments are directed towards employing compressed journaling for event tracking files for metadata recovery and replication. Event data and related metadata are received from one or more client devices. When a feature within the received metadata is detected that is previously unwritten to a journal, then the previously unwritten feature is written to the journal. Further, any feature is detected for the received event data that is determined to be different from a feature associated with an immediately preceding event data that is written in the journal, then the detected different feature is identified in the journal. In one embodiment, the identification employs writing to the journal an effective feature record that may employ indices identifying the different feature. The received event data is also written to the journal and may further employ string arguments to minimize recording of redundant information into the journal.

Compressed journaling in event tracking files for metadata recovery and replication

Embodiments are directed towards receiving and processing search queries directed towards relatively large sets of data. The data is stored in a record based datastore. From the stored data, field names, corresponding field values, and posting values may be determined. Posting values may be employed to locate records in the datastore that include the field names and field values. The field names, field values, and posting values may be employed to generate a lexicon. If queries are received, a lexicon query processor may employ the lexicon separate from the datastore to generate responses to the received queries. Queries may include clauses that may be processed using the lexicon separate from the datastore, such as, where clause expressions, group-by clause expressions, aggregation functions, or the like. A time values array may be used to enable queries to process group-by-time expressions that may return results grouped into sub-sets based on time ranges.

Flexible schema column store

Embodiments of the present invention are directed to facilitating data model acceleration in association with an external data system. In accordance with aspects of the present disclosure, at a core engine, a search request associated with a data model is received. The data model generally designates one or more fields, from among a plurality of fields, that are of interest for subsequent searches. Thereafter, it is determined that an accelerated data model summary associated with the data model is stored at an external data system remote from the core engine that received the search request. The accelerated data model summary includes field values associated with the one or more fields designated in the data model. A search for the received search request is initiated using the accelerated data model summary at the external data. A set of search results relevant to the search request is obtained and provided to a user device for display to a user.

Facilitating data model acceleration in association with an external data system

Supplementing a high performance analytics store with evaluation of individual events to respond to an event query

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