What the Client Was Facing
A 200-service Kubernetes environment was producing 3,000+ alerts per day. On-call engineers were overwhelmed by noise, critical alerts were being missed and the team had lost trust in the alerting system — often ignoring pages for fear 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 deployed an AI-powered alert correlation and noise reduction layer using SigNoz and a custom alert grouping engine. Alerts were correlated by service dependency, timing and symptom pattern — reducing 3,000 daily alerts to 40–60 actionable notifications. Dynamic baselines replaced static threshold alerts.
Technologies Used
Measurable Outcomes Delivered
Alert volume reduced from 3,000/day to 40–60 actionable notifications
On-call engineer trust in alerting restored — zero ignored alerts in 60 days
Mean time to acknowledge improved from 14 minutes to 3 minutes
Zero missed critical alerts in 6 months since dynamic baseline implementation
Want Similar Results for Your Team?
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