Developers can scale real-time tracking in customer journeys by architecting a resilient event-driven system, leveraging technologies such as Kafka or Kinesis for high-volume data ingestion and processing. This strategy often involves deploying serverless functions like AWS Lambda for asynchronous event handling and utilizing distributed NoSQL databases, including Cassandra or DynamoDB, optimized for write scalability and low-latency access. To further enhance performance and resilience, key practices include efficient data serialization formats like Protobuf or Avro; using API Gateways for secure, scalable ingestion; employing edge computing or CDNs to minimize global latency; and intelligently distinguishing between real-time stream processing for immediate actions versus batch processing for analytical insights. This comprehensive approach ensures that vast amounts of customer interaction data can be tracked, processed, and acted upon in real-time, maintaining high performance and reliability even under peak loads. More details: https://core1.adunity.com/click?spgid=0&__x1ts=&uhad=[uhad]&xcrid=739497&pub=382594055637429&site=382594055637429.ron_white_media&pagecat=382594055637429./0/&zone=382594055637429.TrackZone&size=0x0&sclickurl=https://infoguide.com.ua