Correlation Identifier Tracking Data Flow Through Service Callstacks
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Solution Overview
Problem
Service providers face challenges in understanding how data flows through their systems and which services are utilized during transactions, as actual user interactions differ from predicted flows, leading to unknown service usage and potential service failures.
Innovation Solution
The use of a correlation identifier in callstack data to track and reassemble data processing flows, allowing service providers to determine service usage patterns, identify underutilized or critical services, and optimize system performance by mapping data flows through the service provider's system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If service providers rely on predicted data flows and required services to describe system operation, then system design can be simplified, but actual service usage remains unknown and cannot be accurately tracked
Solution Approach 1:
The patent introduces a correlation identifier as an intermediary element that bridges the gap between predicted data flows and actual service usage. This identifier is embedded in data packets and traverses through the service provider's network, allowing the system to capture actual service interactions without fundamentally redesigning the entire system architecture. The correlation identifier acts as a mediator that connects request data with response data across multiple services, enabling tracking while maintaining system design simplicity.
Solution Approach 2:
The system enables self-service by having the data packets carry their own correlation identifiers throughout their journey through the service provider's network. Each service that processes the data can autonomously log the correlation identifier and its associated service information without requiring complex centralized coordination. This self-service approach allows individual services to contribute to the overall tracking functionality independently, reducing system design complexity while capturing comprehensive service usage information.
2Measurement precision
If service providers implement comprehensive data flow tracking to identify actual service usage, then service monitoring accuracy improves, but system complexity and implementation difficulty increase
Solution Approach 1:
The patent segments the data flow tracking function into discrete, manageable components. The correlation identifier is divided into segments that are independently processed by different services along the data path. Each service logs only its interaction with the data packet using the correlation identifier, rather than requiring a monolithic tracking system. This segmentation enables accurate service usage tracking while keeping individual service implementations simple and modular.
Solution Approach 2:
The system performs preliminary action by pre-generating correlation identifiers that are embedded in data packets before they enter the service provider's network. This preliminary tagging allows subsequent services to simply read and log the pre-existing identifier rather than generating or managing tracking information dynamically. This approach achieves high measurement precision while minimizing the complexity of individual service implementations, as each service only needs to perform straightforward logging of the pre-assigned correlation identifier.
3Ease of operation
If service providers use traditional data flow prediction methods, then system operation can be straightforwardly managed, but actual user interactions and service utilization patterns remain unidentified
Solution Approach 1:
The patent implements feedback by capturing actual service usage information through correlation identifiers and making this data available for analysis. The system logs the actual services accessed by each correlation identifier and compares this with predicted data flows. This feedback mechanism enables service providers to identify discrepancies between predicted and actual usage patterns, allowing them to adjust their understanding of system operation while maintaining straightforward management through existing infrastructure.
Solution Approach 2:
The tracking system operates through self-service by having data packets automatically carry their own correlation identifiers through the entire service processing chain. Each service independently logs its interaction with the data packet using the correlation identifier without requiring external coordination or complex management overhead. This self-service approach enables comprehensive service usage data collection while keeping system management simple, as the tracking functionality is inherently distributed and autonomous across services.
Data Source
AI summary
There are provided systems and methods for tracking data flow through data services using a processing request identifier in callstack data. During processing requests with a service provider, each request is assigned a particular identifier, called a correlation identifier. The correlation identifier is stored in callstack data and may be used to map these individual data processing flows for the requests to the data processing services of the service provider used during the flows. Once the data flows are determined the actual used services may be identified. The mapping system may also provide for removal of erroneous callstack and reassembly of callstack data during asynchronous service calls. Additionally, the data flows may be used to see where multiple callstacks have divergent data flows. A service provider may utilize the data flows for determination of service usage rates.