Predictive Error Remediation in Distributed Systems
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Solution Overview
Problem
Current distributed systems face challenges in detecting and remediating errors efficiently, leading to compromised data and service performance due to human, machine, and integration errors, which are difficult to detect and costly to resolve.
Innovation Solution
A remediation node is introduced that forecasts service requests and detects error conditions before they occur, communicating remediation instructions to source systems to modify service parameters, utilizing machine learning models to prioritize and improve error detection and resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current error detection and remediation approaches are used in distributed systems, then errors can be detected and corrected, but the process is computationally expensive and time-consuming
Solution Approach 1:
The system performs preliminary error detection and remediation actions before service requests are actually processed. The error detection node proactively identifies potential errors in service parameters by comparing data across multiple source systems ahead of time, and the remediation node prepares corrective actions in advance. This preliminary action eliminates the need for time-consuming error detection and remediation when errors actually occur during service processing.
Solution Approach 2:
The patent introduces intermediary nodes (error detection node and remediation node) that mediate between the service authority and source systems. These intermediary nodes handle the computationally expensive error detection and remediation tasks separately, allowing the main service processing to proceed efficiently while errors are handled by specialized intermediary components.
2Reliability
If comprehensive error detection is performed across all service parameters, then data reliability is improved, but system complexity and computational cost increase
Solution Approach 1:
The system segments error detection and remediation functions into separate specialized nodes (error detection node and remediation node) that operate independently from the main service authority. This segmentation allows comprehensive error checking to be performed without complicating the core service processing logic, as error handling is delegated to dedicated components with specific responsibilities.
Solution Approach 2:
Intermediary nodes are introduced to handle the complexity of comprehensive error detection. These nodes act as buffers between the service authority and source systems, performing detailed parameter validation and cross-system data comparison without requiring the service authority itself to become complex. The intermediaries absorb the computational overhead of thorough error checking.
3Productivity
If service requests are processed immediately without forecasting, then processing speed is maintained, but errors may occur and compromise service quality
Solution Approach 1:
The system performs preliminary error detection on service parameters before actual service processing occurs. By proactively identifying potential errors in advance and preparing remediation actions, the system ensures that when service requests are processed immediately, they are already validated and less likely to fail, thus maintaining both speed and quality.
Solution Approach 2:
The system implements feedback loops where error detection nodes continuously monitor service parameters and provide information to remediation nodes. This feedback mechanism allows the system to adaptively adjust service processing based on detected error patterns, improving service quality without significantly impacting processing speed through automated real-time adjustments.
Data Source
AI summary
Systems and methods for remediating errors in distributed computing are provided. A system may include a remediation node. The remediation node may forecast receipt of a service request by a service authority. The service request may be configured to cause the service authority to modify a service assigned to an account. The service authority may be in communication with a plurality of source systems. The remediation node may acquire, from at least one of the source systems, a service parameter in which the service authority is configured to access to process the service request. The remediation node may determine an error condition corresponding to the service parameter. The remediation node may communicate, in response to determination of error condition, a remediation instruction to the at least one of the source systems, the remediation instruction configured to cause the at least one of the source systems to modify the service parameter.