Introducing Impressions at Netflix

Netflix uses impressions—images and promotional banners that users interact with—to fuel its personalization engine. By tracking impressions, Netflix optimizes recommendations, maintains frequency capping, and highlights new releases. The system handles billions of impressions daily using technologies like Apache Kafka and Apache Iceberg for real-time and historical data processing. The architecture includes a centralized event processing queue, data enrichment through Apache Flink, and stringent data quality measures. Future improvements aim to manage schema flexibility, automate performance tuning, and enhance data quality alerts.