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Apr 15, 2024 · Azure Event Hubs is a powerful tool for organizations needing to ingest, store, and process large volumes of data in real-time. Its scalability, reliability, and integration capabilities make it ...
- Overview
- Namespace
- Partitions
- Event publishers
- Capture
- SAS tokens
- Event consumers
- Application groups
- Apache Kafka support
- Next steps
Azure Event Hubs is a scalable event processing service that ingests and processes large volumes of events and data, with low latency and high reliability. For a high-level overview of the service, see What is Event Hubs?.
This article builds on the information in the overview article, and provides technical and implementation details about Event Hubs components and features.
An Event Hubs namespace is a management container for event hubs (or topics, in Kafka parlance). It provides DNS-integrated network endpoints and a range of access control and network integration management features such as IP filtering, virtual network service endpoint, and Private Link.
Event Hubs organizes sequences of events sent to an event hub into one or more partitions. As newer events arrive, they're added to the end of this sequence.
A partition can be thought of as a commit log. Partitions hold event data that contains the following information:
•Body of the event
•User-defined property bag describing the event
•Metadata such as its offset in the partition, its number in the stream sequence
•Service-side timestamp at which it was accepted
Any entity that sends data to an event hub is an event publisher (synonymously used with event producer). Event publishers can publish events using HTTPS or AMQP 1.0 or the Kafka protocol. Event publishers use Microsoft Entra ID based authorization with OAuth2-issued JWT tokens or an Event Hub-specific Shared Access Signature (SAS) token to gain publishing access.
You can publish an event via AMQP 1.0, the Kafka protocol, or HTTPS. The Event Hubs service provides REST API and .NET, Java, Python, JavaScript, and Go client libraries for publishing events to an event hub. For other runtimes and platforms, you can use any AMQP 1.0 client, such as Apache Qpid.
The choice to use AMQP or HTTPS is specific to the usage scenario. AMQP requires the establishment of a persistent bidirectional socket in addition to transport level security (TLS) or SSL/TLS. AMQP has higher network costs when initializing the session, however HTTPS requires extra TLS overhead for every request. AMQP has higher performance for frequent publishers and can achieve much lower latencies when used with asynchronous publishing code.
You can publish events individually or batched. A single publication has a limit of 1 MB, regardless of whether it's a single event or a batch. Publishing events larger than this threshold is rejected.
Event Hubs throughput is scaled by using partitions and throughput-unit allocations. It's a best practice for publishers to remain unaware of the specific partitioning model chosen for an event hub and to only specify a partition key that is used to consistently assign related events to the same partition.
Event Hubs ensures that all events sharing a partition key value are stored together and delivered in order of arrival. If partition keys are used with publisher policies, then the identity of the publisher and the value of the partition key must match. Otherwise, an error occurs.
Event Hubs Capture enables you to automatically capture the streaming data in Event Hubs and save it to your choice of either a Blob storage account, or an Azure Data Lake Storage account. You can enable capture from the Azure portal, and specify a minimum size and time window to perform the capture. Using Event Hubs Capture, you specify your own Azure Blob Storage account and container, or Azure Data Lake Storage account, one of which is used to store the captured data. Captured data is written in the Apache Avro format.
The files produced by Event Hubs Capture have the following Avro schema:
Event Hubs uses Shared Access Signatures, which are available at the namespace and event hub level. A SAS token is generated from a SAS key and is an SHA hash of a URL, encoded in a specific format. Event Hubs can regenerate the hash by using the name of the key (policy) and the token and thus authenticate the sender. Normally, SAS tokens for event...
Consumer groups
The publish/subscribe mechanism of Event Hubs is enabled through consumer groups. A consumer group is a logical grouping of consumers that read data from an event hub or Kafka topic. It enables multiple consuming applications to read the same streaming data in an event hub independently at their own pace with their offsets. It allows you to parallelize the consumption of messages and distribute the workload among multiple consumers while maintaining the order of messages within each partition. We recommend that there's only one active receiver on a partition within a consumer group. However, in certain scenarios, you can use up to five consumers or receivers per partition where all receivers get all the events of the partition. If you have multiple readers on the same partition, then you process duplicate events. You need to handle it in your code, which isn't trivial. However, it's a valid approach in some scenarios. In a stream processing architecture, each downstream application equates to a consumer group. If you want to write event data to long-term storage, then that storage writer application is a consumer group. Complex event processing can then be performed by another, separate consumer group. You can only access partitions through a consumer group. There's always a default consumer group in an event hub, and you can create up to the maximum number of consumer groups for the corresponding pricing tier. Some clients offered by the Azure SDKs are intelligent consumer agents that automatically manage the details of ensuring that each partition has a single reader and that all partitions for an event hub are being read from. It allows your code to focus on processing the events being read from the event hub so it can ignore many of the details of the partitions. For more information, see Connect to a partition. The following examples show the consumer group URI convention: The following figure shows the Event Hubs stream processing architecture:
Stream offsets
An offset is the position of an event within a partition. You can think of an offset as a client-side cursor. The offset is a byte numbering of the event. This offset enables an event consumer (reader) to specify a point in the event stream from which they want to begin reading events. You can specify the offset as a timestamp or as an offset value. Consumers are responsible for storing their own offset values outside of the Event Hubs service. Within a partition, each event includes an offset.
Checkpointing
Checkpointing is a process by which readers mark or commit their position within a partition event sequence. Checkpointing is the responsibility of the consumer and occurs on a per-partition basis within a consumer group. This responsibility means that for each consumer group, each partition reader must keep track of its current position in the event stream, and can inform the service when it considers the data stream complete. If a reader disconnects from a partition, when it reconnects it begins reading at the checkpoint that was previously submitted by the last reader of that partition in that consumer group. When the reader connects, it passes the offset to the event hub to specify the location at which to start reading. In this way, you can use checkpointing to both mark events as "complete" by downstream applications, and to provide resiliency if a failover between readers running on different machines occurs. It's possible to return to older data by specifying a lower offset from this checkpointing process. Through this mechanism, checkpointing enables both failover resiliency and event stream replay. Important Offsets are provided by the Event Hubs service. It's the responsibility of the consumer to checkpoint as events are processed. Follow these recommendations when using Azure Blob Storage as a checkpoint store: •Use a separate container for each consumer group. You can use the same storage account, but use one container per each group. •Don't use the container for anything else, and don't use the storage account for anything else. •Storage account should be in the same region as the deployed application is located in. If the application is on-premises, try to choose the closest region possible. On the Storage account page in the Azure portal, in the Blob service section, ensure that the following settings are disabled. •Hierarchical namespace •Blob soft delete •Versioning
An application group is a collection of client applications that connect to an Event Hubs namespace sharing a unique identifying condition such as the security context - shared access policy or Microsoft Entra application ID.
Azure Event Hubs enables you to define resource access policies such as throttling policies for a given application group and controls event streaming (publishing or consuming) between client applications and Event Hubs.
The protocol support for Apache Kafka clients (versions >=1.0) provides endpoints that enable existing Kafka applications to use Event Hubs. Most existing Kafka applications can simply be reconfigured to point to an s namespace instead of a Kafka cluster bootstrap server.
From the perspective of cost, operational effort, and reliability, Azure Event Hubs is a great alternative to deploying and operating your own Kafka and Zookeeper clusters and to Kafka-as-a-Service offerings not native to Azure.
For more information about Event Hubs, visit the following links:
•Get started with Event Hubs
•.NET
•Java
•Python
•JavaScript
Usage example
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Azure Event Hubs support HTTPS and AMQP 1.0 protocols for event publishing. Event publishers use Shared Access Signature (SAS) tokens for authentication. SAS tokens for event publishers can be created with send-only privileges on a specific Event Hub. .NET
Feb 16, 2024 · The Event Hubs Premium (premium tier) is designed for high-end streaming scenarios that require elastic, superior performance with predictable latency. The premium tier provides reserved compute, memory, and storage resources, which minimize cross-tenant interference in a managed multitenant PaaS environment.
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side-by-side comparison of Amazon Kinesis vs. Azure Event Hubs. based on preference data from user reviews. Amazon Kinesis rates 4.7/5 stars with 26 reviews. By contrast, Azure Event Hubs rates 4.2/5 stars with 13 reviews.
