If you’ve ever heard about or experienced a scenario where a production python bug can’t be fixed because we’re not able to reproduce the same, sometimes even after adding additional logs, then this session is for you.
Black box debugging is an idea where we add low footprint and encoded debug logs in the production code which drastically increases the chances of detecting the cause of a bug without requiring a recurrence with additional logs (read Debug Logs).
Traditionally, we tend to include a limited amount of logs in the production code because writing the logs on the disk is a costly affair and can potentially impact the performances, but at the same time if something goes wrong, then we need the logs to debug the system.
So what if I tell you that you can have debug logs in the production code without impacting the performance of the code…!!! I bet you’ll be pleasantly surprised.
Welcome to the world of harnessing an unexpected and unintended benefit of In-Memory NoSQL databases which revolutionized the way we write debug logs for our python code.
In this talk, I’ll talk about how we use In-Memory NoSQL with python code and get persistent logs without impacting the performance of the production code.
This talk is for all Python programmers irrespective of their expertise level