IoT devices generate substantial data volumes requiring continuous processing and analysis. Apache Kafka serves as a highly scalable open-source streaming platform enabling reading, storage, processing, and forwarding of massive data flows from thousands of IoT devices. KSQL, an open-source streaming SQL engine built natively on Kafka, democratizes stream processing through straightforward SQL commands.
The presentation illustrates a healthcare sector scenario demonstrating how Kafka and KSQL facilitate real-time patient health monitoring. A live demonstration showcases deploying machine learning models—trained using frameworks like TensorFlow, DeepLearning4J, or H2O—into scalable, runtime-critical real-time applications.
Key Takeaways:
- Kafka functions as a streaming platform for managing high-volume data ingestion from distributed IoT device networks
- KSQL enables continuous data integration and analysis without requiring external big data infrastructure or custom code development
- Machine learning models integrate seamlessly within the Kafka ecosystem for real-time scoring and insights
