Episode description

There are two primary industries within the Internet of Things (IoT): industrial IoT (IIoT) and consumer IoT (CIoT), both of which can benefit from the Apache Kafka® ecosystem, including Kafka Streams and Kafka Connect. Kai Waehner, who works in the advanced tech group at Confluent with customers, defining their needs, use cases, and architecture, shares example use cases where he’s seen IoT integration in action. He specifically focuses on Walmart and its real-time customer integration using the Walmart app. Kafka Streams helps fine-tune the Walmart app, optimizing the user experience, offering a seamless omni-channel experience, and contributing to business success. 

Other topics discussed in today’s episode include integration from various legacy and modern IoT data sources, latency sensitivity, machine learning for quality control and predictive maintenance, and when event streaming can be more useful than traditional databases or data lakes.

EPISODE LINKS

• Apache Kafka 2.5 – Overview of Latest Features, Updates, and KIPs
• Machine Learning with Kafka Streams, Kafka Connect, and ksqlDB ft. Kai Waehner
• Blog posts by Kai Waehner
• Processing IoT Data from End to End with MQTT and Apache Kafka®
• End-to-End Integration: IoT Edge to Confluent Cloud
• Apache Kafka is the New Black at the Edge in Industrial IoT, Logistics, and Retailing
• Apache Kafka, KSQL, and Apache PLC4X for IIoT Data Integration and Processing
• Streaming Machine Learning at Scale from 100,000 IoT Devices with HiveMQ, Apache Kafka, and TensorFlow
• Event-Model Serving: Stream Processing vs. RPC with Kafka and TensorFlow
• Join the Confluent Community Slack
• Learn about Kafka at Confluent Developer