Case Study: Baseten achieves faster error resolution and saves 10 hours a month with Sentry

How Baseten Saves 10 Hours a Month through Accelerated Error Identification and Resolution

Baseten, a San Francisco-based platform for developing, deploying, and testing ML models in production, needed better visibility into errors and system issues across its fast-moving, multi-service environment. As a rapidly deploying startup, Baseten turned to Sentry’s error monitoring to gain actionable context and avoid delays in tracking down bugs, regressions, and silent failures.

With Sentry, Baseten improved error identification through stack traces, source-code access, and detailed event data, enabling the team to find and resolve issues in hours instead of days. Sentry also supported Baseten’s Python and Golang services and Slack-based alerting, helping the team save 10 hours a month, speed triage, and maintain user trust through faster rollbacks and issue resolution.

Baseten

Sid Shanker

Backend Engineer