2022-06-29, 17:00–17:20, Hall 3
Startups choose python because it helps you to set up your application very quickly, but after a few months, it can get really messy. This is the story of how we in Databand managed to extract good backend guidelines with Python out of our monolith.
In this lecture, I'm going to talk about our experience in Databand.ai where we started with a quick-and-dirty web application architecture in order to quickly provide value to our customers.
Our application became larger and larger, and the business needs were significantly changed. A lot of new code and features were introduced, and we found ourselves chasing after our tails in order to detect problems in our app.
When we had enough, we started to conduct new backend guidelines and embraced a lot of DDD methodologies such as a bounded context, layering, unit of work, repository pattern, domain architecture, and so on.
I believe this tells the story of a lot of startups and there is a lot to learn from our experience - what went wrong, how to avoid it, and how to fix old problems.