Workflow Error Debugger Using Tracking Identifiers
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Solution Overview
Problem
Debugging errors in workflows involving multiple microservices and applications across various compute environments is complex due to the challenge of identifying failures and errors across multiple instances, requiring significant manual effort and time.
Innovation Solution
A computing system aggregates logs from multiple workflow instances, assigns workflow names and instance identifiers, and uses tracking identifiers to stitch together logs from different microservices, enabling comprehensive error reporting and end-to-end analysis to identify errors in workflow execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If logs from multiple workflow instances are analyzed manually to identify errors, then error detection completeness is improved, but time consumption and manual effort increase significantly
Solution Approach 1:
The system performs preliminary actions by automatically aggregating logs from multiple workflow instances and pre-processing them into a unified format before error analysis. This includes collecting logs from various sources, standardizing their structure, and organizing them by workflow instance, thereby reducing the time required for manual error detection while maintaining completeness.
Solution Approach 2:
The system creates copies of log data from multiple workflow instances and processes them in a standardized manner. By copying and consolidating log information into a unified view, the system enables comprehensive error detection across instances without requiring manual examination of each individual log file, thus reducing time consumption.
2Measurement precision
If logs from multiple microservices are collected and analyzed separately, then service-level detail is improved, but system complexity increases
Solution Approach 1:
The system merges logs from multiple microservices into a unified aggregated view while preserving service-level details. By combining logs with a common tracking identifier into a single consolidated log group, the system maintains the ability to analyze service-specific errors while reducing the overall complexity of the debugging process through centralized management.
Solution Approach 2:
The system introduces an intermediary layer that sits between individual microservice logs and the final error analysis. This intermediary aggregates and standardizes logs from multiple services, translating heterogeneous service-level details into a unified format that is easier to analyze while preserving the necessary service-specific information.
3Measurement precision
If comprehensive log aggregation from multiple workflow instances is performed, then error analysis accuracy is improved, but data processing complexity increases
Solution Approach 1:
The system segments the comprehensive log aggregation process into manageable components: individual log collection from each workflow instance, standardization of log formats, grouping by tracking identifier, and final error analysis. This segmentation reduces processing complexity by breaking down the large-scale aggregation task into smaller, more manageable steps while maintaining error analysis accuracy.
Data Source
AI summary
Examples include aggregating logs, where each of the logs is associated with a workflow instance. Each log includes information indicative of an event occurring during the workflow instance. Further, examples include assigning, based on user intent of the workflow instance, a workflow name to each log, where the user intent is indicative of an outcome of execution of the workflow instance and assigning an instance identifier to each log, where the instance identifier corresponds to the workflow instance. Further, identifying a subset of the plurality of logs having an identical workflow name and an identical instance identifier, associating a tracking identifier to the subset, and creating an index of processed logs, wherein each processed log in the index includes the tracking identifier. Further, analyzing the index of processed logs based on a set of rules and identifying, based on the analysis, an error in execution of each the workflow instance.