A digital twin is a digital replica of a living or non-living physical entity. This session discusses the benefits and IoT architectures of a Digital Twin in Industrial IoT (IIoT) and its relation to Apache Kafka, IoT frameworks and Machine Learning. Kafka is often used as central event streaming platform to build a scalable and reliable digital twin for real time streaming sensor data. A live demo shows a scalable digital twin infrastructure for condition monitoring and predictive maintenance in real time for a connected car infrastructure leveraging Kafka, MQTT and TensorFlow. Key Take-Aways: • Learn about use cases and characteristics of a digital twin in various industries • Understand how to build a digital twin for every single (of tens of thousands) IoT device or machine • See different IoT architectures with Kafka and other IoT technologies and products, including edge, hybrid and global deployments • Understand the relation to Machine Learning and bring added value to your IoT infrastructure by enabling use cases like predictive maintenance • Understand how the Apache Kafka enables scalable and flexible end-to-end integration processing from IIoT data to various backend applications • Watch a live demo of an end-to-end integration, real time processing and analytics of thousands of IoT devices More details: https://www.kai-waehner.de/blog/2019/11/28/apache-kafka-industrial-iot-iiot-build-an-open-scalable-reliable-digital-twin/ https://www.kai-waehner.de/blog/2020/03/25/architectures-digital-twin-digital-thread-apache-kafka-iot-platforms-machine-learning/ https://youtu.be/Q3eKPEVwNVY