A company is designing a data storage solution for its IoT devices that generate telemetry data. The data is ingested at high velocity (millions of events per second) and must be stored for real-time dashboards and historical analysis. The solution must also support complex event processing and alerting. Which two Azure services should the company use together? (Choose two.)
Azure Event Hubs is the correct choice because it is a fully managed, partitioned event-streaming platform engineered for high-throughput telemetry ingestion from millions of IoT devices, supporting millions of events per second and automatic data retention for replay. It decouples producers (devices) from consumers, exposes Kafka-compatible APIs, and enables Stream Analytics, functions, or custom consumers to process the stream, making it the foundational buffer before durable storage.
Why this answer
Azure Event Hubs is the correct choice because it is a high-throughput data ingestion service designed to handle millions of events per second from IoT devices, providing low-latency, durable event capture for real-time dashboards and historical analysis. Azure Stream Analytics is the correct companion service because it natively integrates with Event Hubs to perform complex event processing (CEP), such as pattern matching, aggregation, and alerting, on the streaming telemetry data in real time.
Exam trap
The trap here is that candidates often confuse Azure IoT Hub with Event Hubs, assuming IoT Hub is the default for all IoT data ingestion, but IoT Hub is for device management and lower-throughput scenarios, while Event Hubs is the correct choice for high-velocity, multi-million-events-per-second telemetry ingestion.