Case Study: Xandr (the advertising marketplace) achieves real-time incident detection and resolves issues in under a day to prevent revenue loss with Anodot's AI-driven anomaly detection

Xandr Uses Anodot for Real Time Monitoring of Its Massive Scale Marketplace

Xandr is a global advertising marketplace that connects publishers and marketers at massive scale — serving billions of ads daily, handling about 45 million transactions per second and processing 175+ TB of data. Its complex, partner-driven ecosystem suffered from fragmented monitoring, excessive alert noise and hard-to-detect, client‑specific incidents (like blank ads) that quickly cost revenue and customer experience if not found and fixed fast.

Xandr deployed Anodot’s cloud-based, machine‑learning anomaly detection to ingest near‑real‑time metrics, learn normal patterns, correlate related alerts and route root‑cause notifications via Slack to the right teams. The result: time‑to‑detection fell from a week or more to under a day (often hours), faster resolution of incidents, reduced resource waste and measurable prevention of revenue loss — enabling Xandr to scale monitoring across its platform.

Xandr

Ben John

Chief Technology Officer