What the Client Was Facing
A SaaS platform was experiencing 8–10 P1 incidents per month. Mean time to detect was 22 minutes and mean time to resolve was 4.5 hours. Alert noise was so high that critical alerts were being missed among hundreds of false positives.
What ZippyOPS Was Engaged To Do
ZippyOPS was brought in to design and implement a solution addressing the root causes of the client's challenges — delivering measurable outcomes within a fixed engagement timeline. Our team worked embedded with the client's engineers throughout the entire project.
How We Solved It
ZippyOPS implemented a full AIOps stack — Prometheus and Grafana for metrics, Loki for logs, Tempo for traces and SigNoz for AI-powered correlation. Anomaly detection was configured using VictoriaMetrics. Automated runbooks in PagerDuty handled 60% of P2/P3 incidents without human intervention.
Technologies Used
Measurable Outcomes Delivered
P1 incident count reduced from 8–10 per month to 2–3
Mean time to detect reduced from 22 minutes to 3 minutes
Alert noise reduced 72% — critical alerts now visible and acted on
Automated runbooks handling 60% of P2/P3 incidents without human intervention
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