Posts tagged “backend”.
Calling an LLM API is easy. Running it in production is not. These are the backend patterns I use to make AI features reliable, cheap and safe: timeouts, retries, queues, caching and good boundaries.
Your app works on your laptop. But what happens in production at 3 a.m.? Observability helps you answer questions you didn't plan. Here is a simple guide to logs, metrics and traces, with AI features in mind.
A good API is easy to use and hard to use wrong. These are the REST API design rules I follow every day as a backend developer: names, status codes, errors, pagination, versioning and safe retries.
Scout checks your app's metrics every 20 minutes. When something goes wrong, it finds the broken part of the code and asks an AI model to explain the problem — and how to fix it.