Event Hub Connector

Stream millions of IoT events per second to Azure Event Hubs for high-throughput event ingestion. Partition-based consumption enables parallel processing by multiple consumers with configurable retention.

What is Event Hub

Azure Event Hubs is a big data streaming platform and event ingestion service capable of receiving and processing millions of events per second. It is built for high-throughput IoT telemetry streaming and real-time analytics.

Key Features:

Massive Throughput: Ingest millions of events per second with low latency.

Partitioned Consumption: Multiple consumer groups process events in parallel independently.

Capture to Storage: Automatically capture streaming data to Blob Storage or Data Lake in Avro format.

Kafka Compatibility: Kafka protocol support — use existing Kafka clients without code changes.

Schema Registry: Centralized schema management for event data validation and evolution.

How it Works

When the Event Hub connector is enabled, /IOTCONNECT™ streams device events to your Event Hub namespace:

Devices stream data → High-volume telemetry arrives at /IOTCONNECT™.

Events batched → Data is batched for optimal throughput and sent to your Event Hub.

Partitioned → Events are distributed across partitions by device ID for parallel processing.

Multiple consumers → Stream Analytics, Spark, Flink, or custom consumers process in parallel.

User Manual

Step 1: Navigate to Connector Settings

Go to Settings > Configuration > Live Data Streaming in the /IOTCONNECT™ portal.

Step 2: Enable Event Hub

Find the Event Hub connector card and toggle the switch to ON (green).

Step 3: Select Data Types

Choose which data to stream: Telemetry, Faulty, Diagnostics, Command History.

Step 4: Run ARM Template

Click the ARM template link. This deploys:

An Event Hubs namespace with configured throughput units

Event Hub with partition count optimized for your workload

Shared Access Policy for cross-tenant publishing

Consumer groups for multiple downstream processors

Step 5: Confirm Subscription ID

Subscription ID auto-populates after deployment.

Step 6: Save

Click Save. Events begin streaming to your Event Hub.

Use Cases

Stream Analytics: Connect Azure Stream Analytics for real-time aggregation and anomaly detection on telemetry streams.

Big Data Pipelines: Feed Apache Spark, Flink, or Databricks for large-scale telemetry processing.

High-volume Ingestion: Handle millions of sensor readings per second from large device fleets.

Event Sourcing: Maintain a complete event log for replay and audit purposes.

Kafka Migration: Use Kafka protocol compatibility to integrate with existing Kafka consumers.

ⓘ NOTE

Event Hub retention can be configured from 1 to 90 days. Enable Capture to automatically archive all events to Blob Storage or Data Lake for long-term retention. Partition count should match your expected consumer parallelism.