Splunk Inc.

Cisco Technology, Inc.

Siegfried Puchbauer

Nicholas John Filippi

Ruyuan Ge

Nathaniel Gerard McKervey

Antoine Toulme

Ryan Russell Moore

Vishal Patel

Amritpal Singh Bath

Samat Jain

Stephen Robert Luedtke

Ryan O'Connor

Tingjin Xu

Isabelle Park

Min Zhang

Paul Jean André Bernier

Nusair Haq

Christopher Cordi

A computing device receives an ingest preview request to preview events to be stored by at least one indexer. Responsive to the ingest preview request, the computing device sends a subscription request to the forwarders. The forwarders receive the subscription request and intercept the events that are being sent to at least one of the indexers. The forwarders then clone matching events to the subscription request and responds to the computing device with the matching events. When the computing device receives the matching events, the computing device adds the matching events to a dispatch directory. The user interface is then populated with events in the dispatch directory.

Ingest preview of events in a network computing environment

A machine data validation system can track and validate the integrity of machine data generated by machines. The system can generate hashes for the items and batch hashes that can be validated using an immutable data store, such one or more blockchains in a tiered blockchain structure. The system can store machine data and additional associated data in a first lightweight blockchain, and store grouped sets of the data in a second robust blockchain. The system can implement the tiered blockchain structure to efficiently store and reference the hashes to validate the machine data at different times or upon request from an end-user.

Data stream integrity in a tiered blockchain structure

Systems and methods are disclosed for generating one or more files to visualize query results. The systems and methods can include parsing one or more files that include one or more queries and computer-executable instructions for displaying results of the one or more queries. The one or more queries can identify a set of data to be processed and a manner of processing the set of data. The systems and methods can further include generating one or more files that include the results of the queries and computer-executable instructions for displaying one or more visualizations of the results.

Generating files for visualizing query results

A graphical user interface (GUI) includes multiple data visualizations and an adjustable graphical user control. The data underlying the data visualizations are timestamped, and the graphical user control enables a user to select a time interval. When a time interval is selected or modified via the graphical user control, the multiple data visualizations update automatically in real time to reflect data that correspond to the currently selected time interval.

Graphical user interface for time-based data visualization

Systems and methods are disclosed for associating summarizations of visualizations of a data set based on affinities between the summarizations. For a data set, a number of summarizations may be created that summarizes the data set in different ways. The summarizations may be linked, such that selecting a data element of a first summarization causes display of a second summarization. To assist in linking of summarizations, suggested linkings between summarizations can be determined based on affinities of the two summarizations. Affinities can reflect similarities in the data content of the two summarizations, such as an output of a first summarization being a valid input to the second summarization.

Determining affinities for data set summarizations

Systems and methods for decoding distributed ledger transactions by data intake and query systems. An example method includes: receiving a transaction of a distributed ledger, wherein the transaction includes transaction data and an identifier of an account of the distributed ledger; receiving a bytecode module, wherein the bytecode module is associated with the account of the distributed ledger; computing a bytecode digital fingerprint associated with the bytecode module; identifying, among a plurality of stored application binary interface (ABI) definitions, an ABI definition having an ABI digital fingerprint that matches the bytecode digital fingerprint; and producing decoded transaction data by decoding, using the identified ABI definition, the transaction data.

Decoding distributed ledger transaction records

A blockchain consortium network can be implemented in which nodes of one or more blockchains generate data for pipeline-based processing by a consortium pipeline system. The generated data can include private blockchain data, public blockchain data, and machine data, such as logs or operational metrics from the nodes. The data is collected from different network levels and can be transformed via pipeline processes of the consortium pipeline system to securely share data in the blockchain consortium network.

Securely sharing public and private blockchain data

A machine data validation system can track and validate the integrity of machine data generated by machines. The system can generate hashes for the items and batch hashes that can be validated using an immutable data store, such as a blockchain. The system can implement a tiered blockchain structure to efficiently store and reference the hashes to validate the machine data at different times or upon request from an end-user.

Data stream integrity using blockchain

Self-contained files for generating a visualization of query results

Systems and methods are disclosed involving user interface (UI) search tools for visualizing or summarizing a data set. A number of summarizations may be created that summarizes the data set in different ways. The summarizations may be linked, such that selecting a data element of a first summarization causes display of a second summarization. To assist in linking of summarizations, a user interface is further provided to display suggested linkings between summarizations based on affinities of the two summarizations. Affinities can reflect similarities in the data content of the two summarizations, such as an output of a first summarization being a valid input to the second summarization.

Growing community of inventors

San Francisco, CA, United States of America

Siegfried Puchbauer