Processing Internet of Things (IoT) Data from End to End with MQTT and Apache Kafka.
Live demos for my two projects on Github from Kafka Summit in San Francisco 2018 using Kafka Connect respectively Confluent MQTT Proxy:
Apache Kafka + Kafka Connect + MQTT Connector + Sensor Data: https://github.com/kaiwaehner/kafka-connect-iot-mqtt-connector-example
Deep Learning UDF for KSQL for Streaming Anomaly Detection of MQTT IoT Sensor Data: https://github.com/kaiwaehner/ksql-udf-deep-learning-mqtt-iot
Live Demo: https://www.youtube.com/watch?v=L38-6ilGeKE
This session discusses end-to-end use cases such as connected cars, smart home or healthcare sensors, where you integrate Internet of Things (IoT) devices with enterprise IT using open source technologies and standards. MQTT is a lightweight messaging protocol for IoT. However, MQTT is not built for high scalability, longer storage or easy integration to legacy systems. Apache Kafka is a highly scalable distributed streaming platform, which ingests, stores, processes and forwards high volumes of data from thousands of IoT devices. Abstract from my corresponding session at Kafka Summit: This session discusses the Apache Kafka open source ecosystem as a streaming platform to process IoT data. See a live demo of how MQTT brokers like Mosquitto or RabbitMQ integrate with Kafka, and how you can even integrate MQTT clients to Kafka without MQTT Broker. Learn how to analyze the IoT data either natively on Kafka with Kafka Streams/KSQL or on an external big data cluster like Spark, Flink or Elasticsearch leveraging Kafka Connect.