Event Hubs overview & .NET QS

Author: spelluru

articles/event-hubs/event-hubs-about.md

@@ -5,25 +5,13 @@ ms.topic: overview
 ms.date: 03/07/2023
 ---
 
-# Azure Event Hubs — A big data streaming platform and event ingestion service
-Azure Event Hubs is a big data streaming platform and event ingestion service. It can receive and process millions of events per second. Data sent to an event hub can be transformed and stored by using any real-time analytics provider or batching/storage adapters.
-
-Here are a few scenarios where you can use Event Hubs:
-
-- Anomaly detection (fraud/outliers)
-- Application logging
-- Analytics pipelines, such as clickstreams
-- Live dashboards
-- Archiving data
-- Transaction processing
-- User telemetry processing
-- Device telemetry streaming
+# Azure Event Hubs—A big data streaming platform and event ingestion service
+Event Hubs is a modern big data streaming platform and event ingestion service that can seamlessly integrate with other Azure and Microsoft services, such as Stream Analytics, Power BI, and Event Grid, along with outside services like Apache Spark. The service can process millions of events per second with low latency. The data sent to an event hub (Event Hubs instance) can be transformed and stored by using any real-time analytics providers or batching or storage adapters. 
 
 ## Why use Event Hubs?
 Data is valuable only when there's an easy way to process and get timely insights from data sources. Event Hubs provides a distributed stream processing platform with low latency and seamless integration, with data and analytics services inside and outside Azure to build your complete big data pipeline.
 
-Event Hubs represents the "front door" for an event pipeline, often called an *event ingestor* in solution architectures. An event ingestor is a component or service that sits between event publishers and event consumers to decouple the production of an event stream from the consumption of those events. Event Hubs provides a unified streaming platform with time retention buffer, decoupling event producers from event consumers.
-
+Event Hubs represents the "front door" for an event pipeline, often called an **event ingestor** in solution architectures. An event ingestor is a component or service that sits between event publishers and event consumers to decouple the production of an event stream from the consumption of those events. Event Hubs provides a unified streaming platform with time retention buffer, decoupling event producers from event consumers.
 
 The following sections describe key features of the Azure Event Hubs service:
 
@@ -40,8 +28,7 @@ Ingest, buffer, store, and process your stream in real time to get actionable in
 With Event Hubs, you can start with data streams in megabytes, and grow to gigabytes or terabytes. The [Auto-inflate](event-hubs-auto-inflate.md) feature is one of the many options available to scale the number of throughput units or processing units to meet your usage needs.
 
 ## Rich ecosystem
-
-With a broad ecosystem based on the industry-standard AMQP 1.0 protocol and available in various languages [.NET](https://github.com/Azure/azure-sdk-for-net/), [Java](https://github.com/Azure/azure-sdk-for-java/), [Python](https://github.com/Azure/azure-sdk-for-python/), [JavaScript](https://github.com/Azure/azure-sdk-for-js/), you can easily start processing your streams from Event Hubs. All supported client languages provide low-level integration. The ecosystem also provides you with seamless integration with Azure services like Azure Stream Analytics and Azure Functions and thus enables you to build serverless architectures.
+With a broad ecosystem available for the industry-standard AMQP 1.0 protocol and SDKs available in various languages: [.NET](https://github.com/Azure/azure-sdk-for-net/), [Java](https://github.com/Azure/azure-sdk-for-java/), [Python](https://github.com/Azure/azure-sdk-for-python/), [JavaScript](https://github.com/Azure/azure-sdk-for-js/), you can easily start processing your streams from Event Hubs. All supported client languages provide low-level integration. The ecosystem also provides you with seamless integration with Azure services like Azure Stream Analytics and Azure Functions and thus enables you to build serverless architectures.
 
 ## Event Hubs for Apache Kafka
 [Event Hubs for Apache Kafka ecosystems](azure-event-hubs-kafka-overview.md) furthermore enables [Apache Kafka (1.0 and later)](https://kafka.apache.org/) clients and applications to talk to Event Hubs. You don't need to set up, configure, and manage your own Kafka and Zookeeper clusters or use some Kafka-as-a-Service offering not native to Azure.
@@ -51,28 +38,32 @@ Event Hubs **premium** caters to high-end streaming needs that require superior
 
 Event Hubs **dedicated** tier offers single-tenant deployments for customers with the most demanding streaming needs. This single-tenant offering has a guaranteed 99.99% SLA and is available only on our dedicated pricing tier. An Event Hubs cluster can ingress millions of events per second with guaranteed capacity and subsecond latency. Namespaces and event hubs created within the dedicated cluster include all features of the premium offering and more. For more information, see [Event Hubs Dedicated](event-hubs-dedicated-overview.md).
 
-See [comparison between Event Hubs tiers](event-hubs-quotas.md) for more details.
+For more information, see [comparison between Event Hubs tiers](event-hubs-quotas.md).
 
 ## Event Hubs on Azure Stack Hub
-Event Hubs on Azure Stack Hub allows you to realize hybrid cloud scenarios. Streaming and event-based solutions are supported, for both on-premises and Azure cloud processing. Whether your scenario is hybrid (connected), or disconnected, your solution can support processing of events/streams at large scale. Your scenario is only bound by the Event Hubs cluster size, which you can provision according to your needs. 
+The Event Hubs service on Azure Stack Hub allows you to realize hybrid cloud scenarios. Streaming and event-based solutions are supported for both on-premises and Azure cloud processing. Whether your scenario is hybrid (connected), or disconnected, your solution can support processing of events/streams at large scale. Your scenario is only bound by the Event Hubs cluster size, which you can provision according to your needs. 
 
 The Event Hubs editions (on Azure Stack Hub and on Azure) offer a high degree of feature parity. This parity means SDKs, samples, PowerShell, CLI, and portals offer a similar experience, with few differences. 
 
 For more information, see [Event Hubs on Azure Stack Hub overview](/azure-stack/user/event-hubs-overview).
 
 ## Key architecture components
-Event Hubs contains the following [key components](event-hubs-features.md):
+Event Hubs contains the following key components. 
 
-- **Event producers**: Any entity that sends data to an event hub. Event publishers can publish events using HTTPS or AMQP 1.0 or Apache Kafka (1.0 and above)
-- **Partitions**: Each consumer only reads a specific subset, or partition, of the message stream.
-- **Consumer groups**: A view (state, position, or offset) of an entire event hub. Consumer groups enable consuming applications to each have a separate view of the event stream. They read the stream independently at their own pace and with their own offsets.
-- [Throughput units (standard tier)](event-hubs-scalability.md#throughput-units) or [processing units (premium tier)](event-hubs-scalability.md#processing-units) or [capacity units (dedicated)](event-hubs-dedicated-overview.md) : Pre-purchased units of capacity that control the throughput capacity of Event Hubs.
-- **Event receivers**: Any entity that reads event data from an event hub. All Event Hubs consumers connect via the AMQP 1.0 session. The Event Hubs service delivers events through a session as they become available. All Kafka consumers connect via the Kafka protocol 1.0 and later.
+| Component | Description | 
+| --------- | ----------- | 
+| Event producers | Any entity that sends data to an event hub. Event publishers can publish events using HTTPS or AMQP 1.0 or Apache Kafka (1.0 and above). |
+| Partitions | Each consumer only reads a specific subset, or a partition, of the message stream. | 
+| Consumer groups | A view (state, position, or offset) of an entire event hub. Consumer groups enable consuming applications to each have a separate view of the event stream. They read the stream independently at their own pace and with their own offsets. | 
+| Event receivers | Any entity that reads event data from an event hub. All Event Hubs consumers connect via the AMQP 1.0 session. The Event Hubs service delivers events through a session as they become available. All Kafka consumers connect via the Kafka protocol 1.0 and later. | 
+| [Throughput units (standard tier)](event-hubs-scalability.md#throughput-units) or [processing units (premium tier)](event-hubs-scalability.md#processing-units) or [capacity units (dedicated)](event-hubs-dedicated-overview.md) | Pre-purchased units of capacity that control the throughput capacity of Event Hubs. | 
 
 The following figure shows the Event Hubs stream processing architecture:
-
 ![Event Hubs](./media/event-hubs-about/event_hubs_architecture.png)
 
+> [!NOTE]
+> For more information, see [Event Hubs features or components](event-hubs-features.md).
+
 
 ## Next steps