A manufacturing client: 500 sensors on a production line, data every second. How do you get it to the cloud, process it in real time, and visualize it?
Azure IoT Hub¶
A central message broker for IoT devices. Device provisioning, bi-directional communication, device twins for configuration. Scales to millions of devices.
Edge Processing with IoT Edge¶
Not everything needs to go to the cloud. Azure IoT Edge runs on a gateway device, filtering and aggregating data locally. Only anomalies and aggregates are sent to the cloud — saving bandwidth and reducing latency.
Stream Processing¶
Event Hubs → Azure Stream Analytics → Power BI real-time dashboard. Rules: temperature above 85°C = alert, vibration outside normal range = predictive maintenance ticket. Processing in the order of seconds.
Digital Twins¶
Azure Digital Twins — a virtual model of the production line. Sensor data updates the twin in real time. Simulate scenarios like “what happens if we increase throughput by 20%” without risk to the physical line.
IoT = Data Pipeline on Steroids¶
The principles are the same as in data engineering — ingestion, processing, storage, visualization. Only the scale and latency requirements differ.
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