Monitoring Application for Automated Dependency Discovery and Root Cause Analysis

Resolve Bottlenecks,
Find Innovative SolutionsGenerate Solutions

Solution Overview

Problem

Existing monitoring systems struggle to efficiently diagnose and address root causes of performance issues in complex application dependency settings, often requiring manual tracing and collaboration among multiple system administrators.

Innovation Solution

A monitoring application that collects and reports the operating status of monitored applications and their dependencies, using existing monitoring interfaces to identify problem services and traverse dependency trees, while also employing machine learning techniques to predict performance issues and generate corrective actions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If manual tracing and collaboration among multiple system administrators is used to diagnose performance issues, then comprehensive problem analysis can be achieved, but the time required for diagnosis and incident recovery increases significantly

Engineering Contradiction:

Improveproblem analysis comprehensivenessVSAvoiddiagnosis time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The monitoring system automatically performs dependency discovery, health status collection, and root cause analysis without requiring manual administrator intervention. The system self-services by autonomously traversing dependency trees, collecting metrics from multiple sources, and generating diagnostic reports, thereby eliminating the time-consuming manual collaboration while maintaining comprehensive analysis capability

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system pre-establishes dependency maps and relationship graphs before incidents occur. By proactively discovering and storing dependency relationships in advance, the system enables rapid diagnosis during incidents without needing to manually trace dependencies in real-time, thus reducing diagnosis time while preserving analytical depth

Inventive Principle:

Principle #10Preliminary action

2Reliability

If multiple monitoring systems and alerts are used to track complex dependencies, then system coverage is improved, but the complexity of troubleshooting and correlating issues increases

Engineering Contradiction:

Improvemonitoring coverageVSAvoidtroubleshooting complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The patent consolidates multiple monitoring systems and alert sources into a unified view by automatically correlating issues across dependencies. The system merges data from various monitoring tools and presents a consolidated diagnostic picture, reducing troubleshooting complexity while maintaining comprehensive monitoring coverage

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The system introduces an intermediary layer that automatically correlates and contextualizes alerts from multiple monitoring sources. This intermediary processing layer translates raw alerts from different systems into unified diagnostic information, reducing the complexity of troubleshooting while preserving extensive monitoring coverage

Inventive Principle:

Principle #24Intermediary (Mediator)

3Measurement precision

If extensive manual effort is dedicated to tracing dependency chains, then root cause identification accuracy improves, but productivity and incident resolution speed decrease

Engineering Contradiction:

Improveroot cause identification accuracyVSAvoidincident resolution speed

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system replaces manual mechanical tracing efforts with automated computational analysis. Algorithms automatically traverse dependency trees, analyze health metrics, and identify root causes through systematic computation rather than manual exploration, thereby maintaining high identification accuracy while dramatically improving incident resolution speed

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20250103475A1Intelligent Services and Training Agent for Application Dependency Discovery, Reporting and Manageme

Publication Date: 2025.03.27 CAPITAL ONE SERVICES LLC

AI summary

Techniques for monitoring operating statuses of an application and its dependencies are provided. A monitoring application may collect and report the operating status of the monitored application and each dependency. Through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. The monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. Dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. Machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. Also provided are techniques for testing a response of the monitored application through modifications to API calls. Such tests may be used to train the machine learning model.