Azure Event Hubs is a massively scalable data streaming platform and event ingestion service. It can capture, transform, and store millions of events per second. When data needs to be processed in real-time or streamed, Event Hubs is a foundational service to consider.
Key Concepts
Event Hub
An Event Hub is the central entity in Azure Event Hubs. It acts as a container for events. Each Event Hub is associated with a specific data stream or telemetry source. Think of it as a logical set of event producers and consumers.
- Producers: Applications or devices that send events to an Event Hub.
- Consumers: Applications that read events from an Event Hub.
Event
An event is a small unit of information, typically representing a record or a data point. Events are usually immutable records of something that has happened. They are sent to Event Hubs by producers and consumed by consumers.
Producer
A producer is any application or service that sends events to an Event Hub. Producers are unaware of the consumers; they simply send events to the Event Hub endpoint. This decouples the event generation process from event consumption.
Consumer
A consumer is an application that reads events from an Event Hub. Consumers are typically organized into Consumer Groups to process the event stream in parallel without interfering with each other.
Consumer Group
A consumer group is a logical view of an Event Hub's event stream. Each consumer group allows multiple applications, or multiple instances of the same application, to read from an Event Hub independently. Without consumer groups, multiple applications trying to read from the same hub would compete for the same events, leading to only one application receiving specific events.
For example, one consumer group might be used for real-time analytics, another for archival to long-term storage, and a third for feeding a machine learning model.
An Event Hub can have multiple consumer groups, each with its own offset within the partition's stream.
Partition
Event Hubs partitions the event stream to enable parallel processing and scalability. An Event Hub can have multiple partitions (up to the configured number of partitions for the namespace). Events sent to a specific partition are strictly ordered within that partition. Producers can either specify a partition key (which ensures events with the same key go to the same partition) or let Event Hubs select a partition.
The number of partitions determines the maximum degree of parallelism for consumers reading from that Event Hub. A consumer group can have at most as many concurrent consumers as there are partitions.
Partition Key
When a producer sends an event to an Event Hub, it can optionally include a partition key. If a partition key is provided, Event Hubs uses a hash of the key to deterministically select a partition for the event. This ensures that all events with the same partition key are sent to the same partition, maintaining strict ordering for related events.
Offset
An offset is a unique, sequential identifier assigned to each event within a partition. It represents the position of an event in the stream. Consumer groups track their progress by maintaining their current offset for each partition they are consuming from. This allows consumers to resume processing from where they left off if they are interrupted.
Capture
Event Hubs Capture is a feature that automatically archives events from an Event Hub into an Azure Blob Storage account or Azure Data Lake Storage account. It provides a cost-effective way to store large volumes of event data for later processing or analysis without the complexity of managing custom archival solutions.
How it Works Together
Producers send events to an Event Hub. The Event Hub distributes these events across its Partitions. Consumers, organized into Consumer Groups, read events from these partitions. Each consumer within a group reads from a specific partition. The Offset allows consumers to track their position within a partition. A Partition Key can be used by producers to ensure related events are processed in order. The Capture feature can be enabled to automatically archive events to storage.
Example Scenario
Imagine you have IoT devices sending telemetry data. Each device could be a producer sending data to an Event Hub. You might have a Consumer Group for real-time dashboard monitoring, another for anomaly detection using machine learning, and a third for archiving all raw data to Azure Data Lake Storage using Event Hubs Capture.
// Producer Example (Conceptual)
const producer = new EventHubProducerClient(connectionString, eventHubName);
await producer.send({ body: "sensor reading: 25C" });
// Consumer Group Example (Conceptual)
const consumerClient = new EventHubConsumerClient(consumerGroupName, connectionString, eventHubName);
const subscription = consumerClient.subscribe({
processEvents: async (events, context) => {
for (const event of events) {
console.log(`Received event: ${event.body}`);
}
},
processError: async (err, context) => {
console.error("Error occurred:", err);
}
});