Root Cause Detection in Distributed Network Task Flows
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Solution Overview
Problem
Current technologies lack a reliable and efficient method to detect the root cause of exception errors in distributed networks, leading to time-consuming and error-prone manual inspections.
Innovation Solution
A system comprising a processor and memory that monitors communication data and acknowledgement messages between servers in a distributed network, using exception monitoring modules, an exception listener module, and a multi-layer detection module to identify failed messages and determine the root cause of exception errors by generating a communication matrix and analyzing message sequences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual inspection is used to detect failure causes in distributed networks, then operators can identify issues, but the process becomes time-consuming and error-prone
Solution Approach 1:
The system implements self-service by enabling the distributed network to automatically detect and diagnose its own failures through embedded monitoring modules in each server. The exception monitoring modules autonomously track message exchanges and generate diagnostics without requiring external manual inspection, thus improving both detection accuracy and reducing time loss.
Solution Approach 2:
The system applies feedback by implementing exception monitoring modules that continuously observe message exchanges between servers and provide real-time feedback about communication failures. This feedback mechanism enables automatic identification of root causes through analyzing acknowledgment patterns and message flow, eliminating the need for manual inspection while maintaining high detection accuracy.
2Measurement precision
If comprehensive monitoring of all server communications is implemented, then root cause detection accuracy improves, but system complexity increases
Solution Approach 1:
The system applies segmentation by dividing the monitoring function into discrete exception monitoring modules deployed in each server. Each module independently monitors specific message exchanges involving its host server, breaking down the complex global monitoring task into manageable local units. This segmentation maintains high detection accuracy while reducing overall system complexity through modular architecture.
Solution Approach 2:
The system implements universality by designing exception monitoring modules that perform multiple functions: tracking message exchanges, analyzing acknowledgment patterns, identifying communication failures, and determining root causes. This multi-functionality consolidates what would otherwise require multiple separate systems into a single versatile component, improving detection accuracy without proportionally increasing complexity.
Data Source
AI summary
A system for detecting a root cause of an exception error in a task flow in a distributed network receives communication data exchanged among servers. The system determines whether each message is received by a respective server based on acknowledgement data that indicates whether each message is received by a respective server. The system determines the sequence of the messages communicated between the servers. The system determines that a first server has reported an exception error that indicated the first server did not receive a message from a second server. The system determines that the second server is associated with a root cause of the exception error in response to determining that the second server did not send the message to the first server.