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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

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