Developing Culture To Write Reliable And Performant Services At Scale

Python is a programming language known for its usefulness and ease of readability, making it an excellent choice for quickly creating services. These services can be scaled to millions of users. However, a myriad of problems comes hidden with it during the development phase if observability-driven development is not followed like the inability to meet the SLAs, poor performance, difficulty in tracking business metrics, etc and this can lead to anti-patterns in software.

Metrics such as these can be valuable for root cause analysis, driving business goals, component-level monitoring, improving performance, and so on. In this presentation, I will discuss how to adhere to best practices for observability and reliability when building a Python service from the ground up. I will explain the meaning of each concept, how to establish a culture that promotes these practices and provide a detailed code walkthrough demonstrating how to implement these concepts effectively.