Automated Non-Intrusive Event Tracing Across Microservices
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Solution Overview
Problem
Microservice architectures in prescription drug fill processing systems face complex monitoring and lengthy troubleshooting due to non-integrated applications, requiring administrators to know the exact current microservice location of a request, which is inefficient and time-consuming.
Innovation Solution
A computer system with structured microservice configuration data and event log data, processor hardware, and computer-executable instructions for automated non-intrusive event tracing, which identifies microservices, analyzes message fields, builds configuration files, and transforms user interfaces to display event message entries, while masking sensitive data and determining correlation identifiers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated non-intrusive event tracing is implemented, then monitoring efficiency and system visibility are improved, but device complexity increases due to structured configuration data and event log management
Solution Approach 1:
The patent introduces an event tracing system that acts as an intermediary between microservices and administrators. This system automatically collects, correlates, and presents event data without requiring administrators to directly interact with complex microservice architectures, thereby improving monitoring efficiency while managing complexity through abstraction layers
Solution Approach 2:
The system creates copies of event data from multiple microservices and stores them in a centralized event log. This allows the system to monitor and trace request flows without modifying the original microservices, enabling efficient monitoring while maintaining system simplicity at the service level
2Loss of information
If event tracing monitors all microservice messages, then system visibility and troubleshooting capability are improved, but loss of information increases due to sensitive data handling requirements
Solution Approach 1:
The patent extracts and separates sensitive data from the event tracing logs. By identifying and removing sensitive information while preserving correlation identifiers and event flow data, the system maintains information availability for troubleshooting while preventing sensitive data exposure
Solution Approach 2:
The event tracing system serves as an intermediary that processes event data through filtering and masking mechanisms. It selectively captures only the information needed for monitoring and troubleshooting, excluding sensitive data, thus balancing information availability with data protection
3Loss of time
If administrators manually track microservice locations, then device complexity is reduced, but loss of time increases due to lengthy troubleshooting
Solution Approach 1:
The event tracing system performs self-service by automatically tracking, correlating, and presenting microservice event data without requiring administrator intervention. The system autonomously monitors request flows and provides real-time visibility, dramatically reducing troubleshooting time while operating at a high level of automation
Solution Approach 2:
The system implements continuous feedback mechanisms by automatically collecting event data from microservices, correlating it through identifiers, and presenting it in real-time. This closed-loop feedback enables administrators to quickly understand system state and resolve issues without manual tracking, reducing troubleshooting time while maintaining appropriate automation
Data Source
AI summary
A computer system includes memory hardware configured to store structured microservice configuration data having multiple microservice entries each associated with one of multiple microservice applications of a request processing architecture. The system includes processor hardware configured to access structured microservice configuration data to identify the microservice applications of the request processing architecture, subscribing to messages transmitted by the identified microservice applications for event monitoring, and receiving multiple messages transmitted by the identified microservice applications. For each of the multiple received messages, the instructions include analyzing one or more fields of the received message to determine a correlation identifier associated with the received message, identifying one of the multiple request data structures, storing an event message entry in the identified request data structure, and transforming a user interface of a user device to display at least a portion of the multiple event message entries.