Data integration and processing in Industrial IoT (IIoT, aka Industry 4.0 or Automation Industry). Apache Kafka, its ecosystem (Kafka Connect, KSQL) and Apache PLC4X are a great open source choice to implement this integration end to end in a scalable, reliable and flexible way.
Apache Kafka and Machine Learning for Real Time Supply Chain Optimization: Integrate in real time with the legacy world and proprietary IIoT protocols (like Siemens S7, Modbus, Beckhoff ADS, OPC-UA, et al). You can process the data at scale and then ingest it into a modern database or analytic / machine learning framework.
This post shares a slide deck and video recording of the differences between an event-driven streaming platform like Apache Kafka and middleware like Message Queues (MQ), Extract-Transform-Load (ETL) and Enterprise Service Bus (ESB).
Streaming Processing with Apache Kafka and KSQL for Data Scientists via Python and Jupyter Notebooks to build analytic models with TensorFlow and Keras.
MQTT and Apache Kafka are a perfect combination for end-to-end IoT integration from edge to data center. This post discusses two different approaches and refers to implementations on Github using Apache Kafka, Kafka Connect, Confluent MQTT Proxy and Mosquitto.