Recovery failures demand a fast explanation without turning inference into a production decision.
The investigation needs less repeated log reading, while crash-and-recovery evidence still needs an engineer's judgment.
Who you’d be doing this for
“Our job queue came back, but I spent the morning checking whether every order was really there.”
Pablo Moretti · Backend Developer
Runs an application whose transactional records depend on a database recovering predictably after a production fault.
What is at stake
Recovery investigations repeatedly produce competing explanations from the same logs and failed tests. You must decide what evidence the system can assemble and what an engineer must still confirm.
Why it isn’t already fixed
Every obvious fix costs something else. That’s the part you’d have to decide.
- faster diagnosis vs. verified causality
- broad evidence access vs. read-only boundaries
- known failure labels vs. novel failure investigation
- engineer time saved vs. review confidence
Why Supabase
PostgreSQL recovery behavior shapes whether application developers can trust their transactional data after a failure.
Written with these in mind
Not your kind of problem? 19 more at Supabase, or browse every organization.
This is the setup. The work is inside.
Running it puts you in the room: the full situation and its constraints, stakeholders who push back in their own words, and the decisions that are yours to make. What you produce becomes a Day One Plan — work you can show someone instead of describing.