I built a production risk scanner in one day, here's what it caught

If you're an SRE or DevOps engineer — try blastradar.vercel.app and tell me what you actually think.

The tool

BlastRadar scores any code diff for production risk — paste a diff, get a 1-10 score, a plain English explanation of what could break, and a blast radius showing which systems are affected.

Last month a Cursor agent deleted a company's entire production database in 9 seconds. Amazon's AI coding mandate caused a 13-hour AWS Cost Explorer outage. A developer using Claude Code wiped 2.5 years of course submissions in one command.

AI coding agents are merging code into production faster than any human can review it. SREs are the ones getting paged at 2am when it breaks.

I wanted to see if I could build something useful for this problem in a single day. Here's what I built and what I learned.

What it caught: I tested it on two diffs

A documentation PR — scored 1/10. Output: "zero production impact, documentation only." Correct.

A database config change pointing production at a read replica with a connection pool of 2 — scored 9/10. It caught three things: all writes would fail immediately against a read-only replica, a pool of 2 causes connection starvation under any real load, and dropping timeout from 5000ms to 500ms would trigger a retry storm on an already broken connection pool.

That last one — the retry storm — is second-order thinking. The tool didn't just list what changed, it reasoned about the cascade.

What I don't know yet

Whether this is actually useful in a real SRE workflow. Whether the risk scoring is calibrated correctly for real production diffs. Whether existing tools like CodeRabbit already solve this well enough.

That's why I'm posting here. If you're an SRE or DevOps engineer — try it at blastradar.vercel.app and tell me what you actually think. What does it get wrong? What would make it useful in your daily workflow?