Azure Event Hubs Concepts

Introduction to Azure Event Hubs

Azure Event Hubs is a massively scalable data streaming platform and event ingestion service. It can capture millions of events per second so you can develop applications and services that react to, and are driven by, data streams.

Event Hubs is designed for high-throughput scenarios where data is produced and consumed at a rapid pace. It acts as a central nervous system for real-time data, enabling you to connect various components of your modern applications and ingest data from diverse sources.

What are Event Hubs?

At its core, Azure Event Hubs is a distributed streaming platform. It's a highly available, globally scalable service that allows you to ingest vast amounts of telemetry and application data. Think of it as a highly efficient pipeline that can handle enormous volumes of incoming data from many sources simultaneously.

It adheres to the publish-subscribe pattern, where data producers send events to Event Hubs, and consumers read those events. This decoupling of producers and consumers is a key benefit, allowing each to operate independently at its own pace.

Key Concepts

Event Hub

An Event Hub is the fundamental entity in Event Hubs. It acts as a container for events. You can think of it as a logical stream of events. Data producers send events to a specific Event Hub, and consumers read events from it.

Namespaces

An Event Hubs Namespace is a container for one or more Event Hubs. A namespace provides a unique scoping container. You must create a namespace before you can create Event Hubs within it. A namespace is also a boundary for billing and management.

Producers

Producers are applications or devices that send (publish) events to an Event Hub. These can be IoT devices, web servers, mobile applications, or any service generating data streams.

Consumers

Consumers are applications that read (subscribe) events from an Event Hub. Consumers process the events for various purposes, such as real-time analytics, data warehousing, or triggering other actions.

Consumer Groups

A Consumer Group is a view of an Event Hub that enables multiple independent consumers to read from the Event Hub. Each consumer group maintains its own state and offset. This means that multiple applications or services can independently read the same stream of events without interfering with each other.

Partitions

An Event Hub is divided into one or more Partitions. Partitions are ordered, immutable sequences of events. Event Hubs uses partitions to scale the ingestion and throughput of events. Producers can send events to specific partitions or let Event Hubs decide where to route them based on a partitioning key. Consumers typically read from partitions in parallel.

The number of partitions is determined when the Event Hub is created and cannot be changed later. This is an important design consideration.

Offsets

An Offset is a unique, sequential identifier assigned to each event within a partition. Consumers use offsets to track their position in the event stream for a given partition. When a consumer reads events, it advances its offset to know where to resume reading from next time.

Capture

Event Hubs Capture is a feature that automatically and incrementally captures the data streaming through an Event Hub into a specified Azure Blob Storage account or Azure Data Lake Storage account. This is useful for archival purposes, batch analytics, or reprocessing data later.

Common Use Cases

• Telemetry Collection: Ingesting massive amounts of telemetry data from IoT devices, sensors, or applications.
• Real-time Analytics: Processing streaming data for immediate insights, fraud detection, or anomaly detection.
• Log Aggregation: Collecting logs from distributed systems for centralized monitoring and analysis.
• Application Activity Monitoring: Tracking user interactions and application events in real-time.
• Data Archiving: Using Event Hubs Capture to reliably store event streams for compliance or later analysis.

Architecture Overview

Azure Event Hubs is built on a robust, distributed architecture designed for high availability and scalability. When you send data to Event Hubs, it's stored in partitioned logs. Producers can send events to specific partitions or have them distributed automatically. Consumers, organized into consumer groups, can then read these events from the partitions in parallel. The service automatically manages load balancing and fault tolerance, ensuring that your data streams are processed reliably.

Here's a simplified view: