The use case: how Nextdoor deploys Sentry
Nextdoor's engineering team uses Sentry to detect errors proactively, route them to the right owning team through Code Owners and Slack alerts, and automatically create Jira tickets. Stack traces, trace details and Breadcrumbs give context to troubleshoot and resolve issues faster.
More reported results
Figures published in Sentry’s case study. They are not independently measured by usedby.
Acceleration of speed to resolution by 15-30 minutes per issue
In the customer’s words
Some bugs are impossible to discover without Sentry. We have accelerated time to triage because of the richness of context Sentry gives us. It is more structured and straightforward to find issues and resolve them faster.Other AI tools used by Nextdoor
Other public relationships recorded on usedby.
Explore Nextdoor’s AI stack
Sentry users in Media & Publishing
Companies in the same sector, with public evidence.
See all Sentry customers
Go 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 13, 2026
Open source capture What the story claims, and what we checked
What we compared with the page.
- The figure: 15 minutesChecked
Printed word for word on the page, near the name of Nextdoor.
- The passage quoted aboveChecked
Copied word for word from the page, near the name of Nextdoor.
- Nextdoor uses SentryChecked
Confirmed line.
- The result itselfNot checked
We quote it; we did not measure it.
Now, with Sentry—and the team's growing familiarity with it—Nextdoor proactively catches issues before its customers, accelerates triage, and decreases time to resolution.