The use case: how Rootly deploys Sentry
Rootly's engineering team uses Sentry for error monitoring across its Ruby on Rails backend, serverless functions and web frontend. Sentry issues feed into Rootly's own On-Call app to page the right engineer, and the team traces errors to the offending commit so they can revert it quickly.
More reported results
Figures published in Sentry’s case study. They are not independently measured by usedby.
Directly avoid a negative impact on Annual Recurring Revenue (ARR) of >$100,000+, thanks to detecting and mitigating errors before they could impact users and poison their experience
We deploy 10-20 times a day—only possible with Sentry pinpointing issues down to the commit and broken line of code.
In the customer’s words
We deploy 10-20 times a day—only possible with Sentry pinpointing issues down to the commit and broken line of code. Instead of hours, fixes take minutes, keeping our team shipping without delays.Other AI tools used by Rootly
Other public relationships recorded on usedby.
Explore Rootly’s AI stack
Other companies using Sentry
Customers across industries, with public evidence.
AdRollConfirmed
Animation Digital NetworkConfirmed
AnthropicConfirmed
App NouveauConfirmed
ArcadeConfirmed
AtlassianConfirmedGo straight to the source
Based on Sentry’s published case study. We check the public evidence; the results are reported by the vendor.
sentry.io- Last checked
- Nov 14, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 50%Checked
Printed word for word on the page, near the name of Rootly.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Rootly.
- Rootly uses SentryChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
Improve Mean Time To Resolution (MTTR) for errors by 50%, which is critical to mitigate the impact of errors, reduce business impact for themselves and their users, and protect revenue.