Microsoft technology licensing, llc (20240202279). TRAINING AND IMPLEMENTING A STEADY STATE LOG ANALYZER simplified abstract

TRAINING AND IMPLEMENTING A STEADY STATE LOG ANALYZER

Organization Name

microsoft technology licensing, llc

Inventor(s)

Mohit Verma of Seattle WA (US)

Ananth Geethanath of Bothell WA (US)

Rakesh Namineni of Sammamish WA (US)

Ali Alam of Seattle WA (US)

Kamaljit Singh Bath of Redmond WA (US)

Ramanathan Muthiah of Bellevue WA (US)

Suneel Suresh of Redmond WA (US)

TRAINING AND IMPLEMENTING A STEADY STATE LOG ANALYZER - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240202279 titled 'TRAINING AND IMPLEMENTING A STEADY STATE LOG ANALYZER

The present disclosure involves methods, systems, and computer readable media for analyzing log files of various services to determine if they are functioning as intended over a specific period.

• Training or generating a model to predict if parts of an input log file contain data reflecting normal operations of a corresponding service.
• Domain-agnostic approach to training an outlier detection model for analyzing log files of different services.

Potential Applications: - Monitoring and troubleshooting cloud computing services. - Enhancing the performance of microservices by identifying anomalies in log files.

Problems Solved: - Detecting deviations from normal operations in various services. - Improving the overall reliability and efficiency of services.

Benefits: - Early detection of issues in services. - Enhanced performance and reliability. - Streamlined troubleshooting processes.

Commercial Applications: Title: Log File Analysis System for Service Monitoring This technology can be utilized by IT companies offering cloud computing services to ensure optimal performance and reliability for their clients. It can also be valuable for companies utilizing microservices for their operations.

Prior Art: Readers can explore existing research on outlier detection models for log file analysis in the field of IT and service monitoring.

Frequently Updated Research: Stay updated on the latest advancements in outlier detection models and log file analysis techniques for service monitoring.

Questions about Log File Analysis for Service Monitoring: 1. How does this technology contribute to improving the efficiency of cloud computing services? 2. What are the key advantages of using outlier detection models for log file analysis in service monitoring?

Original Abstract Submitted

the present disclosure relates to methods, systems, and computer readable media for analyzing log files for a wide variety of services (e.g., cloud computing services or microservices) to determine whether the services are operating as designed over some period of time associated with the log file(s). the present disclosure includes features and functionality for training or otherwise generating a model being configured to predict whether portions of an input log file include data reflective of normal operations of a corresponding service used to generate the input log file. the present disclosure provides a domain-agnostic approach to training an outlier detection model to analyze log files for a wide variety of services.