Patents by Inventor Günther Schwarzbauer

Günther Schwarzbauer has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Method and system for real-time, false positive resistant, load independent and self-learning anomaly detection of measured transaction execution parameters like response times
    Patent number: 10762110
    Abstract: A combined transaction execution monitoring, transaction classification and transaction execution performance anomaly detection system is disclosed. The system receives and analyzes transaction tracing data which may be provided by monitoring agents deployed to transaction executing entities like processes. In a first classification stage, parameters are extracted from received transaction tracing data, and the transaction tracing data is tagged with the extracted classification data. A subsequent measure extraction stage analyzes the classified transaction tracing data and creates corresponding measurements which are tagged with the transaction classifier. A following statistical analysis process maintains statistical data describing the long term statistical behavior of classified measures as a baseline, and also calculates corresponding statistical data describing the current statistical behavior of the classified measures.
    Type: Grant
    Filed: October 13, 2017
    Date of Patent: September 1, 2020
    Assignee: Dynatrace LLC
    Inventors: Bernd Greifeneder, Andreas Lehofer, Günther Schwarzbauer
  • Method And System For Real-Time, False Positive Resistant, Load Independent And Self-Learning Anomaly Detection Of Measured Transaction Execution Parameters Like Response Times
    Publication number: 20180052907
    Abstract: A combined transaction execution monitoring, transaction classification and transaction execution performance anomaly detection system is disclosed. The system receives and analyzes transaction tracing data which may be provided by monitoring agents deployed to transaction executing entities like processes. In a first classification stage, parameters are extracted from received transaction tracing data, and the transaction tracing data is tagged with the extracted classification data. A subsequent measure extraction stage analyzes the classified transaction tracing data and creates corresponding measurements which are tagged with the transaction classifier. A following statistical analysis process maintains statistical data describing the long term statistical behavior of classified measures as a baseline, and also calculates corresponding statistical data describing the current statistical behavior of the classified measures.
    Type: Application
    Filed: October 13, 2017
    Publication date: February 22, 2018
    Applicant: Dynatrace LLC
    Inventors: Bernd GREIFENEDER, Andreas LEHOFER, Günther SCHWARZBAUER
  • Method and system for real-time, false positive resistant, load independent and self-learning anomaly detection of measured transaction execution parameters like response times
    Patent number: 9817884
    Abstract: A combined transaction execution monitoring, transaction classification and transaction execution performance anomaly detection system is disclosed. The system receives and analyzes transaction tracing data which may be provided by monitoring agents deployed to transaction executing entities like processes. In a first classification stage, parameters are extracted from received transaction tracing data, and the transaction tracing data is tagged with the extracted classification data. A subsequent measure extraction stage analyzes the classified transaction tracing data and creates corresponding measurements which are tagged with the transaction classifier. A following statistical analysis process maintains statistical data describing the long term statistical behavior of classified measures as a baseline, and also calculates corresponding statistical data describing the current statistical behavior of the classified measures.
    Type: Grant
    Filed: July 23, 2014
    Date of Patent: November 14, 2017
    Assignee: Dynatrace LLC
    Inventors: Bernd Greifeneder, Andreas Lehofer, Günther Schwarzbauer
  • METHOD AND SYSTEM FOR REAL-TIME, FALSE POSITIVE RESISTANT, LOAD INDEPENDENT AND SELF-LEARNING ANOMALY DETECTION OF MEASURED TRANSACTION EXECUTION PARAMETERS LIKE RESPONSE TIMES
    Publication number: 20150032752
    Abstract: A combined transaction execution monitoring, transaction classification and transaction execution performance anomaly detection system is disclosed. The system receives and analyzes transaction tracing data which may be provided by monitoring agents deployed to transaction executing entities like processes. In a first classification stage, parameters are extracted from received transaction tracing data, and the transaction tracing data is tagged with the extracted classification data. A subsequent measure extraction stage analyzes the classified transaction tracing data and creates corresponding measurements which are tagged with the transaction classifier. A following statistical analysis process maintains statistical data describing the long term statistical behavior of classified measures as a baseline, and also calculates corresponding statistical data describing the current statistical behavior of the classified measures.
    Type: Application
    Filed: July 23, 2014
    Publication date: January 29, 2015
    Inventors: Bernd Greifeneder, Andreas Lehofer, Günther Schwarzbauer