AI BriefingBuilding Real-Time Monitoring for 3,500 POS Systems Nationwide
Key point
Olive Young adopted Datadog to improve monitoring across 3,500 POS systems nationwide, cutting incident response time by 76%.
Details
Olive Young adopted Datadog to efficiently manage the over 3,500 POS and self-checkout (SCO) units installed across 1,370 stores nationwide. Previously, incidents could only be recognized when reported by stores, which limited response speed.
Considering the unstable network environment of offline stores, they designed a network architecture that builds a proxy server bridging the closed network and the public network. They also standardized the log format to JSON-based and improved resource efficiency by selectively collecting logs focused on user events and error logs.
During installation, they implemented automated deployment via scripts using a POS remote management solution, and rolled it out gradually during early morning hours to prevent network overload. As a result, they achieved a 76% reduction in incident detection time, from 4 minutes 30 seconds to 59 seconds, successfully shifting the operational paradigm from reactive response to prevention-focused operations.
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