Dynamic Debugger Service for Microservice Root Cause Analysis
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Solution Overview
Problem
In cloud environments, conventional AIOps and orchestration platforms face challenges in efficiently determining the root cause of microservice failures, especially when dealing with functional or logical errors, which often require manual analysis of codes and logged errors.
Innovation Solution
A dynamic debugger management helper service that utilizes open telemetry tracing, artificial intelligence, and custom tree building to perform targeted data collection and analysis, allowing for automated extraction of required traces and visualization of data flows to determine the root cause of failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional AIOps and orchestration platforms are used to analyze microservice failures, then manual analysis of codes and logged errors is required, but this increases the time and complexity of determining root cause
Solution Approach 1:
The system performs preliminary actions by proactively collecting and organizing telemetry data, building call graphs, and preparing trace information before failures occur. When a failure happens, the pre-prepared data structure enables immediate root cause analysis without manual code examination, thus reducing failure analysis time while maintaining high accuracy
Solution Approach 2:
The patent introduces an intermediary component (the helper service) that acts as a mediator between the microservice failure and the analysis process. This service automatically collects telemetry data, builds call graphs, and presents structured trace information, eliminating the need for manual code analysis and significantly reducing the time required for root cause identification
2Loss of information
If comprehensive telemetry tracing is performed on microservices, then complete data for failure analysis is obtained, but performance of the microservice is impacted
Solution Approach 1:
The system applies local quality by making the telemetry tracing optional and configurable for different microservices or service groups. Instead of uniformly enabling comprehensive tracing across all microservices, the helper service allows selective activation based on specific needs, thus obtaining necessary tracing data for failure analysis while minimizing performance impact on non-traced services
Solution Approach 2:
The patent implements partial action by enabling telemetry tracing only when necessary (e.g., during failure conditions or for specific critical services) rather than continuously for all services. The helper service can selectively collect trace data based on failure context, obtaining sufficient information for root cause analysis while avoiding the continuous performance overhead of universal tracing
Data Source
AI summary
Aspects of the present invention monitor at least one microservice within a container module for a failure; collect logged data in response to the at least one microservice having the failure; check the logged data to determine that an existing tree is not built for the logged data; perform telemetry tracing on the at least one microservice in response to the existing tree not being built for the logged data; collect logged tracing data based on performing the telemetry tracing on the at least one microservice; visualize an actual flow of the collected logged tracing data; and fix the at least one microservice based on the visualized actual flow the collected logged tracing data.