Hi guys,
I am on the search for a side-project and was thinking about a couple of issues or things that annoyed me in the past while being a developer. One of them was that I personally didn't like the Supabase edge function logs, I don't know it was a bit cumbersome and sometimes when there were some traces I couldn't fully comprehend what was happening.
This was like 8 months ago. Maybe things have changed so far. But what I did often is to have LLM's read the error message and then debug it for me on the code, deploy a new deployment and then test the new deployment to see e.x. if the bug if fixed (edit: <-- all by AI / Cursor which was a nice automated shortcut).
I was thinking to build an AI agent that goes through your logs in real-time, considers recent deployments and expected behaviours looking at the commit messages and autonomously have look out for any side-effects and notifies you if something goes wrong + if desired have AI create a pull request for you.
Especially error codes could be a good trigger for automated investigations by AI through the database, logs, docs or questions to the developer.
What do you guys think? I am thinking to develop this over the weekend and put it open-source?
Feel free to give harsh feedback. Open to learn and get insights.
The user expresses frustration with Supabase edge function logs, describing them as cumbersome and difficult to understand. They propose developing an AI agent that analyzes logs in real-time, monitors deployments, and autonomously detects issues, potentially creating pull requests for fixes. The user seeks feedback on this idea and plans to open-source the project.
Are you against LLM's monitor logs, metrics and alarms in real-time?