Check out this real-world example of scaling IoT for predictive analysis with Redpanda, Iceberg, and Prophet—without high costs or complexity.

Redpanda

Building a scalable IoT data pipeline involves connecting ESP32 sensors to AWS IoT via MQTT, using Redpanda Connect to bridge messages into Redpanda topics, writing sensor data to Apache Iceberg tables with automatic schema management, and applying Prophet for time-series forecasting. This architecture handles real-time streaming from devices to predictive analytics while maintaining low complexity and cost. The pipeline supports scaling from a few devices to thousands without major infrastructure changes, with schema evolution through Avro and Redpanda's Schema Registry ensuring data consistency.

IoT for fun and Prophet: Scaling IoT and predicting the future