Observability Metric Correlation Across Distributed Transaction Spans
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Solution Overview
Problem
Existing solutions for monitoring operational metrics in complex online transactional platforms face challenges in correlating dimensions across multiple microservices, requiring complex configuration and maintenance, especially in modern distributed architectures.
Innovation Solution
A mechanism for obtaining operational attributes across multiple spans and generating metric measurements with corresponding dimensions, enabling easy configuration and analysis of operational metrics through prescriptive templates and user-friendly interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If custom metrics or OpenTelemetry span metrics are used for monitoring operational metrics, then metric collection is possible, but configuration and maintenance become complex and require code changes
Solution Approach 1:
The patent introduces an intermediary layer between the distributed microservices and the monitoring system. This intermediary automatically collects attributes from multiple spans, correlates them by transaction ID, and presents them as unified operational metrics. This eliminates the need for complex custom metric configurations and code changes in each service.
Solution Approach 2:
The system enables self-service metric collection by automatically traversing and scraping attributes from distributed spans without requiring manual configuration in each microservice. The correlation and aggregation happen automatically through the platform, reducing maintenance burden.
2Reliability
If custom metrics or span metrics are used in distributed architectures with multiple microservices, then monitoring can be implemented, but correlating dimensions across spans becomes difficult
Solution Approach 1:
The patent segments the metric collection process into distinct operations: traversing spans, scraping attributes, correlating by transaction ID, and aggregating measurements. This segmentation allows each operation to be optimized independently and makes the overall process more manageable in distributed systems.
Solution Approach 2:
The platform acts as an intermediary that collects attributes from multiple distributed spans, correlates them using transaction IDs, and reconstructs complete operational metrics. This prevents loss of dimension information that would otherwise be scattered across multiple microservices.
3Quantity of substance
If metric measurements are generated from distributed spans, then comprehensive operational data can be collected, but the process requires code changes and multiple iterations
Solution Approach 1:
The system performs self-service by automatically traversing distributed spans and collecting attributes without requiring code instrumentation in each microservice. This eliminates the need for code changes and multiple iteration cycles while still achieving comprehensive operational data collection.
Solution Approach 2:
The patent performs preliminary actions by establishing the attribute scraping and correlation framework upfront, allowing comprehensive metric collection to occur automatically as transactions flow through the system. This avoids the need for iterative code changes and testing.
Data Source
AI summary
In one implementation, a device may obtain operational attributes across a plurality of spans associated with a monitored transaction over a network. The device may provide the operational attributes for configuration as an operational metric attribute and as dimension attributes corresponding to the operational metric attribute. The device may generate, based on the configuration, an operational metric measurement corresponding to the operational metric attribute and one or more dimensions corresponding to the dimension attributes. The device may provide the operational metric measurement for at least one of the one or more dimensions for operational analysis.