Laís Carvalho

Most Django developers have been there: something is slow, users are complaining, and the first instinct is to sprinkle print() statements or scroll through server logs hoping for a clue. Without proper observability, diagnosing performance bottlenecks in a Django application (or any application, for that matter) is guesswork. Observability is the practice of understanding what is happening inside your application by looking at the signals it produces: traces, metrics, and logs. While the concept is well-established in infrastructure and DevOps circles, it remains under-explored in the day-to-day workflow of many Django developers. Yet Django's middleware architecture, ORM, and request/response cycle make it particularly well-suited for instrumentation. In this talk, I will walk through how to add observability to a Django app. I'll cover the Four Golden Signals of observability (latency, traffic, errors, and saturation), explain why they matter for your Django app, and show how to expose them with minimal setup. Through a live demo, you will see how to use observability standards to monitor your system. You'll also see how to leverage AI to query your logs and traces in natural language or with SQL. Attendees will leave this talk with a practical, reproducible workflow for adding observability to their own Django projects, along with an understanding of which signals to monitor and why.