#profiling

#profiling

in a modern web app there are many potential causes of a performance problem: third-party JavaScript, overburdened servers, bloated assets, missing database indexes - a list as long as your arm. But decades of building for the web told me that this was a frontend problem. I could just smell it. The page looked janky while loading. And despite being the least-bad approach for web frontends today, the React ecosystem is lousy with ways for a codebase to get tangled, slow, and fishy.

Air is built on FastAPI, so we could use [pyinstrument's instructions](https://pyinstrument.readthedocs.io/en/latest/guide.html#profile-a-web-request-in-fastapi) modified. However, because profilers reveal a LOT of internal data, in our example we actively use an environment variable. You will need both `air` and `pyinstrument` to get this working: ```sh # preferred uv add "air[standard]" pyinstrument # old school pip install "air[standard]" pyinstrument ```

Code Optimizations is an AI-based service running on Azure Application Insights that uses telemetry gathered by the Application Insights Profiler for .NET to analyse runtime behaviour, find performance bottlenecks down to individual methods, and provide actionable suggestions. Developers can view aggregated data over time (defaulting to a rolling 24‑hour window, with history up to 30 days) for their production and non-production environments.