SaaS
Cutting Production Incidents by 70%
Automated remediation and SLO-driven alerting for a high-traffic SaaS platform.
- Incident volume
- -70%
- Alert noise
- -82%
- Deploy frequency
- 2.1×
/01The challenge
A growth-stage SaaS team was on PagerDuty every other night. Alerts were noisy, runbooks were stale, and the same three incident classes accounted for most of the wake-ups.
/02Our approach
We instrumented their stack against SLOs, killed every alert that didn't map to user-visible impact, and built self-healing for the top recurring failures. Then we automated the post-mortem template so learnings actually fed back into the system.
/03The outcome
Two quarters in, alert volume is down 70%, the on-call rotation is back to one engineer per week (was three), and the team ships features twice as often.
/04Next step