It still feels a little strange to have AI writing practically all the code — but I decided to give it a real shot on this new project. A bit of context: I was running low on project ideas to share here, so I asked the AI for a list and picked one called Database Performance Testing. The goal was to run performance tests against a relational database. I built it in roughly two days, and in this article I want to share my honest impressions — both technical and about the AI-assisted workflow itself.
Why run performance tests on a database?
I think this is the first question we need to ask before starting any project. As it happens, I'm currently on a project where data performance is a critical system concern — which got me thinking: what would it look like to run performance tests directly against a relational database?
From a QA perspective, performance isn't just about how the API connects to the database. It's also about how queries are written and how the chosen database handles query concurrency, especially in synchronous systems. A slow endpoint isn't always a slow endpoint — sometimes it's a slow query hiding behind it. That's what drove me to start here.
What are we testing?
