Laying the right technical foundation to scale

STAT Trading wanted to scale from a Discord channel to a full blown web app in which each user could set up their alerts and monitoring differently. Working with the technical founder, I architected the project, laid out the foundational models, and provided coaching to enable him to get to the right start.

Software Architecture
STAT Trading wanted to scale to a full blown web app in which each user could set up their alerts and monitoring differently.
Since the founder was experienced in coding, we focused on setting him up well through software architecture, laying foundational models, and providing coaching.


We met Tom years ago when did a very small contract with me for a couple hours of consulting on a Django app he was working on. Fast forward a couple years later, and he was part of a group of founders at STAT Trading building a platform and community to teach a particular set of trading strategies. He built a working Discord bot that did alerts for their particular strategies and setups, but wanted to scale to a full blown web app, where each user could set up their alerts and monitoring differently.

Tom was quite technically skilled and versatile himself: He’d already built this whole bot alerting system in Python, and didn’t need me to do everything for him. However, he wanted to deploy a production grade Django app with a nice base to work off of, and for us to give him the foundational pointers to make sure he built things in the right direction.


Given Tom’s technical experience, we wanted to provide just what he needed and not more (which would be overlapping and charging for things he could do himself). We provided Tom with a solid “starter kit” that was a combination of an industry standard starter template (Cookiecutter Django), and our own Django core components, methodologies, and structure, and made a number of Loom videos showing Tom how to proceed in various directions to add in what he wanted to add in. We laid out the foundational models, taking from his original Python code and porting enough of it to Django to show him how to proceed. We also configured Celery with a robust production-grade setup, and wrote a few of the initial tasks to show him how that would look. Beyond that, we set up a Pusher integration so that his frontend could have easy real-time features; their community was somewhat niche, so users scale beyond the thousands wasn’t going to be an issue for a while, meaning Pusher’s pricing for their user count was quite low.


From there, Tom was able to run with what we gave him and get the platform out to his user base. Since then, he has added many features, and has been able to grow a thriving platform and community. Every once in a while, if he runs into a challenging technical question, we’ll hop on a quick consulting call, but beyond that, the buildout and relationship has been just what we believe he hoped for: A solid foundation laid by an expert, and an open channel of communication to help with any difficult challenges that arise.

Client Testimonial