Splunk Inc.

Salesforce, Inc.

Slack Technologies, Inc.

Alan Vincent Hardin

Alok Anant Bhide

Fang I Hsiao

Brian C Reyes

Brent Stephen Boe

Kan Wu

Tristan Antonio Fletcher

Adam Jamison Oliner

Jacob Barton Leverich

Leonid Alekseyev

Manish Sainani

Sonal Maheshwari

Asmita Puri

George Daloukov

Nicholas Matthew Tankersley

Ross Andrew Lazerowitz

Arun Ramani

Kevin Marshall

Colin Gibbs

Anupadmaja Raghavan

Max Baez

Jennifer Enrique

Rochit Gupta

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

One or more lower-tier system monitoring components are installed and operated prior to installing a higher-tier system monitoring component. A lower-tier system may be an individual server, network device, or local area network. A higher-tier system may include an enterprise or organization wide network or service that includes at least a part of the lower-tier system. Once the higher-tier system monitoring component is installed, the higher-tier and lower-tier system monitoring components use an interface to operate with one another to form a single larger instance of an organization wide monitoring system. The combination of the higher-tier system monitoring component and the one or more lower-tier system operating components performs monitoring aspects of the overall information technology environment based at least in part on machine data produced and made searchable to provide monitoring results.

Lower-tier application deployment for higher-tier system

Information technology environment monitoring systems, for example, perform analytics over machine data received from networked entities. Outputs of such a system may be useful to help a user identify a problem and resolve an incident. Inventive aspects enable user interactions to trigger automatic connection with network servers to establish communication channels for conveying analytics and other information related to the problem between and among network nodes participating in the resolution of the problem or incident.

Collaborative incident management for networked computing systems

An automatic service monitor in an information-technology environment performs regular search queries against generated machine data to derive performance measurements. The information technology environment is defined in terms of services provided by entities, and the performance measurements are defined as key performance indicators (KPIs) of the services. Generated machine data used by the search queries pertain to the entities performing the service. Definitional information for the services, entities, and KPIs is administered by a user to control the operation of the service monitor. Various aspects of such definitional information as well as related performance measurement information may be presented in a unified console display tailored to, and organized around, a particular service. The console display may serve as a central launch point by supporting user interaction to navigate to other specialized monitoring interfaces.

Service detail monitoring console

Implementing communication barriers in a group-based communication system is described. In an example, a privacy setting associated with a communication privilege for communicating with a user of a group-based communication system can be stored, wherein the privacy setting permits the user to transmit communications via the group-based communication and restricts another user of the group-based communication system from communicating with the user. The group-based communication system can deny a communication privilege of the other user based at least in part on the privacy setting, wherein denying the communication privilege prohibits the other user from at least one of initiating a message associated with a user identifier of the user or transmitting the message to a client device associated with the user identifier.

Differentiated privacy permissions for management of communication privileges

Service monitoring adaptation for maintenance downtime

Methods, apparatuses and computer program products for implementing at least one communication barrier in a group-based communication system are described herein. The apparatus is configured to at least receive a first group correlation between a first user identifier and a first group identifier, receive a second group correlation between a second user identifier and a second group identifier, retrieve a communication separation settings set associated with the first group identifier and the second group identifier, and cause rendering a first electronic indication on a group-based communication interface. In some examples, the first user identifier is associated with a first workspace identifier and a first group-based communication channel. In some examples, the first group-based communication channel is associated with the first workspace identifier and a second workspace identifier.

Methods, apparatuses and computer program products for implementing communication barriers in a group-based communication system

Lower-tier application deployment for higher-tier system data monitoring

Techniques are disclosed for providing adaptive thresholding technology for Key Performance Indicators (KPIs) that are updated using training data. Adaptive thresholding technology may automatically assign new values or adjust existing values for one or more thresholds of one or more time policies. Assigning threshold values using adaptive thresholding may involve identifying training data (e.g., historical data, simulated data, or example data) for the time frames and analyzing the training data to identify variations within the data (e.g., patterns, distributions, trends). A threshold value may be determined based on the variations and may be assigned to one or more of the thresholds without additional user intervention.

Adaptive key performance indicator thresholds updated using training data

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 reporting KPI data on system dashboards based on design templates. Data sources associated with one service that help populate a design template are automatically swapped for data sources associated with a different service to produce automatic dashboard variants.

Control interface for dynamic substitution of service monitoring dashboard source data

A processing device performs a search query to produce a search result set having entries having data items. A table, having rows and columns, is displayed in a user interface. Each data item of a particular entry appears in a respective column of the same row of the table. Each column may correspond 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

Techniques are disclosed for providing a graphical user interface (GUI) for displaying and configuring adaptive or static thresholds for Key Performance Indicators (KPIs). The GUI may include one or more presentation schedules that may display threshold information associated with time policies. Each presentation schedule may include multiple time slots and span a portion of one or more time cycles. Some of the time slots may be associated with a specific time policy and may have a unifying appearance that distinguishes the time slots from timeslots associated with other time policies. The presentation schedules may arrange the time slots in a time grid arrangement (e.g., calendar grid view) or a graph arrangement with depictions (e.g., points, lines) that may illustrate KPI values and threshold markers that may illustrate the threshold values.

Graphical user interface for static and adaptive thresholds

Techniques are disclosed for providing adaptive thresholding technology for Key Performance Indicators (KPIs). Adaptive thresholding technology may automatically assign new values or adjust existing values for one or more thresholds of one or more time policies. Assigning threshold values using adaptive thresholding may involve identifying training data (e.g., historical data, simulated data, or example data) for the time frames and analyzing the training data to identify variations within the data (e.g., patterns, distributions, trends). A threshold value may be determined based on the variations and may be assigned to one or more of the thresholds without additional user intervention.

Growing community of inventors

San Francisco, CA, United States of America

Alan Vincent Hardin