20240028442. METHODS AND SYSTEMS FOR RESOLVING PERFORMANCE PROBLEMS WITH OBJECTS OF A DATA CENTER simplified abstract (VMware, Inc.)

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METHODS AND SYSTEMS FOR RESOLVING PERFORMANCE PROBLEMS WITH OBJECTS OF A DATA CENTER

Organization Name

VMware, Inc.

Inventor(s)

Ashot Nshan Harutyunyan of Yerevan (AM)

Arnak Poghosyan of Yerevan (AM)

Lilit Harutyunyan of Yerevan (AM)

Nelli Aghajanyan of Yerevan (AM)

Tigran Bunarjyan of Yerevan (AM)

Marine Harutyunyan of Yerevan (AM)

Sam Israelyan of Yerevan (AM)

METHODS AND SYSTEMS FOR RESOLVING PERFORMANCE PROBLEMS WITH OBJECTS OF A DATA CENTER - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240028442 titled 'METHODS AND SYSTEMS FOR RESOLVING PERFORMANCE PROBLEMS WITH OBJECTS OF A DATA CENTER

Simplified Explanation

The patent application describes automated methods and systems for resolving performance problems with objects in a data center. These methods use machine learning to train a model that defines relationships between event types in log messages and a key performance indicator (KPI) of the object. When a KPI violates a threshold, the rules in the model are used to evaluate runtime log messages and identify the probable root cause of the performance problem. An alert is generated to notify the user of the KPI threshold violation, and the relevant log messages are displayed in a graphical user interface.

  • The patent application describes automated methods and systems for resolving performance problems with objects in a data center.
  • Machine learning is used to train a model that defines relationships between event types in log messages and a key performance indicator (KPI) of the object.
  • When a KPI violates a threshold, the model is used to evaluate runtime log messages and identify the probable root cause of the performance problem.
  • An alert is generated to notify the user of the KPI threshold violation.
  • The relevant log messages are displayed in a graphical user interface for easy analysis.

Potential applications of this technology:

  • Monitoring and troubleshooting performance issues in data centers.
  • Optimizing the performance of objects executing in a data center.
  • Enhancing the efficiency and reliability of data center operations.

Problems solved by this technology:

  • Identifying and resolving performance problems in real-time.
  • Streamlining the troubleshooting process by automatically analyzing log messages.
  • Improving the overall performance and stability of objects in a data center.

Benefits of this technology:

  • Faster detection and resolution of performance problems.
  • Reduction in downtime and associated costs.
  • Improved efficiency and reliability of data center operations.
  • Enhanced user experience and satisfaction.


Original Abstract Submitted

automated, computer-implemented methods and systems for resolving performance problems with objects executing in a data center are described. the automated methods use machine learning to train a model that comprises rules defining relationships between probabilities of event types of in log messages and values of a key performance indictor (“kpi”) of the object over a historical time period. when a kpi violates a corresponding threshold, the rules are used to evaluate run time log messages that describe the probable root cause of the performance problem. an alert identifying the kpi threshold violation, and the log messages are displayed in a graphical user interface of an electronic display device.

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