Traceable Logging in Microservices

sai prasad (~sai45)




Problem Statement: In a distributed microservices architecture, tracking and tracing requests across multiple services poses a significant challenge. Traditional logging approaches often fail to correlate logs related to the same request as it traverses through various microservices. This deficiency leads to difficulties in troubleshooting, debugging, and monitoring the flow of requests in the system. As the number of microservices grows, the need for traceable logging becomes even more critical to maintain system reliability and performance.

Solution approach: To address the complexities of tracking and tracing requests in distributed microservices, we propose a solution tailored for Python frameworks such as Flask and FastAPI. Our approach involves integrating a custom middleware to assign a unique trace ID to each request. This trace ID accompanies the request across all microservices and is stored in context variables for easy access throughout the application. Additionally, we streamline the process by configuring a custom logging setup where the trace ID is automatically included in all log entries.

Conclusion: Through the implementation of this solution, we effectively tackle the challenges associated with tracking requests across multiple microservices. The adoption of traceable logging significantly enhances our ability to troubleshoot, debug, and monitor the flow of requests within the system. Moreover, as our microservices ecosystem expands, the traceable logging mechanism ensures ongoing reliability and performance, thereby contributing to the seamless operation of our distributed architecture.


  1. Basic Python programming knowledge
  2. Familiarity with Python Frameworks like Flask, FastAPI
  3. Understanding of Microservices Architecture

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Speaker Info:

My name is Sai Prasad. I currently work as a senior software developer at BNI. I'm passionate about exploring new technologies, especially in Python programming and problem solving.

Speaker Links:

Section: Python in Web and Applications
Type: Talk
Target Audience: Intermediate
Last Updated: