Log Embedding Vector Search for System Reliability
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Solution Overview
Problem
Existing data processing systems lack effective methods to proactively manage operations and predict future performance based on historical logs, leading to impaired functionality and reduced uptime.
Innovation Solution
A data processing system manager uses machine learning models to generate vector representations of logs, storing them in a vector indexed database for efficient searching and analysis, enabling identification of similar past operations and root cause analysis to prevent future issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional log analysis methods are used, then system operation monitoring is performed, but the ability to proactively predict future performance and identify root causes is insufficient
Solution Approach 1:
The patent introduces an embedding model as an intermediary that transforms raw log data into vector representations. This mediator enables the system to efficiently compare and analyze operational patterns by converting unstructured log data into a format suitable for vector database querying, thereby improving root cause identification capability
Solution Approach 2:
The patent replaces traditional mechanical log analysis methods with a machine learning-based vector embedding approach. Instead of using conventional text-based log searching and pattern matching, the system uses embedding models to transform logs into vector space, enabling more effective similarity search and predictive analysis
2Loss of information
If comprehensive log data is collected for analysis, then operational insights are improved, but data processing complexity and storage requirements increase
Solution Approach 1:
The patent extracts only the essential features from comprehensive log data by using embedding models to transform raw logs into compact vector representations. This extraction process retains the critical operational information needed for analysis while removing redundant data, thereby reducing storage requirements and processing complexity
Solution Approach 2:
The patent changes the parameter representation of log data from raw text format to vector embedding format. This parameter transformation enables the system to process and store operational information more efficiently, as vector representations capture the essential meaning of logs in a condensed numerical form that is easier to query and analyze
Data Source
AI summary
Methods and systems for managing data processing systems are disclosed. A data processing system may include hardware and/or software components. The operation of the data processing system may depend on the operation of these components. To manage the operation of the data processing system, a system may include a data processing system manager. The data processing system manager may obtain logs for components of the data processing system reflecting the historical operation of these components and use the log to predict the future operation of the data processing system, identify similar operation of other data processing systems, and/or for other purposes. Based on the predictions, the data processing system manager may take action to reduce the likelihood of the data processing system becoming impaired.