Contextual Log File Collection via Symptom Analysis

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Solution Overview

Problem

Current log collection methods in computing systems transfer large volumes of irrelevant data to backend support teams, consuming resources and prolonging diagnostic processes, as customers and administrators often send entire sets of log files without identifying the relevant data needed for issue characterization.

Innovation Solution

A management system that analyzes alert data to identify current symptoms, uses a lookup table to determine relevant log categories, and transfers only those log files, reducing unnecessary data transfer and resource consumption by collecting and transferring only contextual log files.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If all log files are transferred to backend support team, then complete diagnostic data is available, but network bandwidth and storage resources are consumed unnecessarily

Engineering Contradiction:

Improvediagnostic completenessVSAvoidnetwork bandwidth consumption

Core Design Contradiction:

ReliabilityVSLoss of energy

Solution Approach 1:

The patent extracts only the relevant log files needed for diagnosing the specific issue from the complete set of log files. The system identifies and transfers only those log files that are contextually relevant to the reported problem, eliminating unnecessary data transfer while maintaining diagnostic effectiveness.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent segments the complete log file set into relevant and irrelevant portions based on the specific issue being diagnosed. By dividing the log collection into targeted subsets, the system transfers only the necessary segments, reducing network bandwidth consumption while preserving diagnostic completeness.

Inventive Principle:

Principle #1Segmentation

2Reliability

If all log files are transferred to backend support team, then complete diagnostic data is available, but storage resources at backend are consumed unnecessarily

Engineering Contradiction:

Improvediagnostic completenessVSAvoidstorage space consumption

Core Design Contradiction:

ReliabilityVSQuantity of substance

Solution Approach 1:

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

Inventive Principle:

Principle #1Segmentation

3Reliability

If all log files are transferred to backend support team, then complete diagnostic data is available, but diagnostic time is prolonged due to data volume

Engineering Contradiction:

Improvediagnostic completenessVSAvoiddiagnostic processing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

Inventive Principle:

Principle #1Segmentation

4Productivity

If contextual log files are selectively transferred, then resource consumption is reduced, but risk of transferring irrelevant logs increases

Engineering Contradiction:

Improveresource efficiencyVSAvoidlog relevance accuracy

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The patent performs preliminary analysis at the customer premises to identify which log files are relevant to the specific issue before transfer. By pre-processing and filtering logs locally, the system ensures only relevant files are selected for transfer, maintaining high relevance accuracy while improving resource efficiency.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary filtering mechanism that acts as a bridge between the complete log set and the transferred logs. This intermediary layer analyzes and selects only the contextually relevant log files, ensuring accuracy while reducing the volume of transferred data.

Inventive Principle:

Principle #24Intermediary (Mediator)

Data Source

PatentUS11436072B2System and method for collecting contextual log files from a computing system

Publication Date: 2022.09.06 HEWLETT PACKARD ENTERPRISE DEV LP

AI summary

Example implementations relate to method and management system for collecting contextual log files to an issue in a computing system. The method includes analyzing alert data to identify a current symptom associated with the issue in the computing system, and determining whether the current symptom exists in a first lookup table including a plurality of first symptoms and a plurality of first log categories. Each first symptom is mapped to one or more first log categories in the first lookup table. In response to determining that the current symptom exists in the first lookup table, the method includes collecting one or more log files from a plurality of log files corresponding to the one or more first log categories mapped to the current symptom, from the computing system. Further, the method includes transferring the one or more log files to an external computing system for performing diagnostics on the issue.