Splunk Inc.

Ross Andrew Lazerowitz

Tristan Antonio Fletcher

Vineetha Bettaiah

Hemendra Singh Choudhary

Alok Anant Bhide

Adam Jamison Oliner

Kristal Curtis

Eric Nathaniel Tschetter

William Marcum

Michael Margulis

Amy Katherine Hunnel Bianchi

Alexandros Nikolaos Kompotis

Caleb Eugene Hanson

Sean David McBride

Daniel Blake Partain

Dipti Prabhakar Siddamsettiwar

Daniel M Jones

Iman Makaremi

Alan Vincent Hardin

Anupadmaja Raghavan

Chakravarthy Sridhar

George Daloukov

Network connected devices are controlled via the transmission of action messages to prevent or correct conditions that impair the operation of the networked information technology (IT) assets. The service monitoring system (SMS) monitoring the IT environment groups together related notable events that are received during system operation. Automatic processes dynamically determine grouping operations that automatically correlate the events without requiring, for example, a set of declarative grouping rules. Event grouping may be performed on a by-service basis to facilitate the complex processing of predicting undesirable system conditions that may be prevented or reduced by transmission of the action messages to the appropriate assets. Event grouping operations may be directed with control information maintained via user interface.

Managing event group definitions in service monitoring systems

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.

Providing a user interface reflecting service monitoring adaptation for maintenance downtime

Machine data of an operating environment is conveyed by a network to a data intake and query system (DIQS) which reflects the machine data as timestamped entries of a field-searchable datastore. Monitoring functionality may search the machine data to identify notable event instances. A notable event processing system correlates the notable event instance to one or more triaging models which are executed against the notable event to produce a modeled result. Information of the received notable event and the modeled results are combined into an enhanced representation of a notable event instance. The enhanced representation conditions downstream processing to automatically perform or assist triaging of notable event instances to optimize application of computing resources to highest priority conditions in the operating environment.

Triage model in service monitoring system

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

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

An application executing on a mobile computing platform provides independent data channels over a mobile network to multiple separate computing systems that each maintain some data pertinent to problem determination and resolution when an incident arises in a monitored information technology (IT) environment. The application maintains and separately exercises the channels to provide timely information in a user interface that composites data to present a single interface with a multi-sourced contextual rendering. Some systems may include an IT monitoring system and a separate incident management system among its sources. Channels may include extended functionality to improve security or other aspects of communication with mobile platforms.

Composite display of multi-sourced IT incident related information

Automatic triage model execution in machine data driven monitoring automation apparatus

Service monitoring adaptation for maintenance downtime

Multi-source incident management and monitoring system

Service monitoring interface controlling by-service mode operation

Mobile device composite interface for dual-sourced incident management and monitoring system

Network connections are established between machines of an operating environment to be monitored and a server group of a data intake and query system (DIQS). Data reflecting machine and component operations of the environment is conveyed via the network to the DIQS where it is reflected as timestamped entries in a field-searchable datastore. Monitoring components may search the datastore and identify and record instances of notable events. Triaging models are selectively applied against the notable event instances to produce an enhanced notable event instance representation with modeled results effective to automatically perform or assist in triaging the notable events so they are dispatched in an optimal, effective, and efficient, manner.

Automatic triage model execution in machine data driven monitoring automation apparatus with visualization

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San Franscisco, CA, United States of America

Ross Andrew Lazerowitz