Intelligent Feature Controller for Network Failure Containment
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Solution Overview
Problem
Existing enterprise software systems face challenges in managing interdependencies between subcomponents, leading to collateral damage and reactive incident handling when a subcomponent fails, with difficulties in identifying and remediating failures without manual intervention.
Innovation Solution
An intelligent feature controller system using AI/ML monitors subcomponents, identifies interdependencies, and proactively turns off or on features based on availability, leveraging a dependency repository and rule manager to manage failures and alert stakeholders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a subcomponent fails in an interconnected enterprise software system, then the failure is detected, but other dependent subcomponents are affected or impaired causing collateral damage
Solution Approach 1:
The system performs preliminary actions by proactively identifying and remediating failures before they propagate to dependent subcomponents. The failure remediation system continuously monitors system health, detects issues early, and automatically executes remediation actions to prevent collateral damage, rather than reacting after failures have already impacted other components.
Solution Approach 2:
The failure remediation system acts as an intermediary layer between subcomponents, managing dependencies and preventing failure propagation. By monitoring interdependencies and controlling the activation/deactivation of subcomponents based on their operational status, the system mediates the impact of failures and protects dependent components from being affected.
2Measurement precision
If manual intervention is used to identify and remediate failures, then detailed analysis can be performed, but response time is delayed and productivity is reduced
Solution Approach 1:
The system implements self-service by automatically detecting, analyzing, and remediating failures without requiring manual intervention. The failure remediation system autonomously monitors system components, identifies failures through continuous health checks, determines appropriate remediation actions, and executes them automatically, thereby maintaining high response speed while ensuring accurate failure analysis through systematic monitoring and analysis capabilities.
Solution Approach 2:
The system employs continuous feedback loops where the failure remediation system monitors system health, receives feedback on component status, analyzes failure patterns, and automatically adjusts remediation strategies. This closed-loop feedback mechanism enables both rapid response and precise analysis by continuously gathering data on system state and failure characteristics, allowing the system to learn from past incidents and improve remediation accuracy over time.
3Reliability
If the system continuously monitors all subcomponents for failures, then reliability is improved, but system complexity and resource consumption increase
Solution Approach 1:
The failure remediation system implements a universal monitoring framework that can monitor multiple subcomponents and failure types through a single integrated system. Rather than implementing separate monitoring mechanisms for each component, the system provides multi-functional monitoring capabilities that can detect various failure modes across different subcomponents using unified monitoring logic and data collection methods, thereby reducing overall system complexity.
Solution Approach 2:
The system merges monitoring, analysis, and remediation functions into an integrated failure remediation system. By combining these previously separate functions into a single coordinated system, the patent reduces complexity that would arise from having separate monitoring and remediation systems. The integrated approach allows the system to efficiently manage the monitoring of multiple subcomponents through a unified architecture that shares resources and coordination mechanisms.
Data Source
AI summary
An intelligent feature controller is provided. The intelligent feature controller identifies failures to various features within a network. The intelligent feature controller identifies features that are dependent on the failed features within the network. The intelligent feature controller turns off the features that are dependent on the failed features within the network. As such, the network may continue operating with certain features being turned off. This limits the failures within the network to the affected features, instead of entire systems failing because of a failed feature.


