Customers
Teams running NOFire in their own production.
What broke, what the investigation found, and what changed after, told by the engineers who were on call
Online Learning Platform
Fifteen indexes applied. No school went down.
12,000+ schools at risk during mongodb incidents · 15 index issues caught before outage · 130+ hrs investigation time eliminated
Read the storyHome Services Technology
Alert config debt they did not know they had.
1,190+ investigations automated · 700+ hrs saved vs. manual triage · 102× peak db query spike diagnosed
Read the storyMaritime Technology
Days of investigation, collapsed into a Slack thread.
3 min to trace the change (from days) · 35+ investigations completed · 100+ hrs saved vs. manual cross-tool work
Read the storyIn their words
On call, in their own words.
We jumped between 5 dashboards to see what broke. Now on-call sees the cause and the impact, and they fix it.
We fixed the change that exhausted RDS. Releases no longer end with scaling the database by hand.
We spent days in Loki, CloudWatch, and GitHub. Now on-call sees the change that caused the incident.
89% root-cause accuracy, on a benchmark anyone can rerun.
The methodology behind the numbers on these pages: how root cause is measured on real incidents, failures included.
See your own production on the map.
A live map of your production and every change in it, built read-only, with no change to your application code.