Event Hubs Capture

Azure Event Hubs Capture is a fully managed Event Hubs feature that automatically and incrementally captures the output of an Event Hubs stream and writes it into an Azure Blob Storage or Azure Data Lake Storage account of your choice.

How Capture Works

When you enable Event Hubs Capture, it reads events from your Event Hubs namespace and writes them into storage. Capture can be configured to write to either:

• Azure Blob Storage: Ideal for batch processing, archival, and analytics using services like Azure Databricks or Azure Synapse Analytics.
• Azure Data Lake Storage Gen2: Provides a hierarchical namespace and robust analytics capabilities, optimized for big data workloads.

Key Benefits of Using Capture

• Automatic Archival: Seamlessly offload event data without custom code or infrastructure management.
• Scalability: Scales automatically with your Event Hubs throughput.
• Cost-Effectiveness: Pay only for the storage consumed and Event Hubs capture capabilities.
• Integration: Easily integrate with other Azure data services for further processing and analysis.
• Flexible Output Formats: Data can be captured in Avro or Parquet format, suitable for various analytical tools.

Configuring Event Hubs Capture

You can enable and configure Event Hubs Capture through the Azure portal, Azure CLI, PowerShell, or ARM templates. The configuration typically involves:

1. Selecting the Destination: Choose between Azure Blob Storage or Azure Data Lake Storage Gen2.
2. Providing Storage Account Details: Specify the storage account, container, and optionally a directory path.
3. Defining Capture Interval: Configure how often data should be captured (e.g., every X minutes or after X GB of data).
4. Choosing the File Format: Select between Avro (default) or Parquet.

Capture File Naming Convention

Captured files follow a specific naming convention to help organize and identify them. The default format is:

{
    "storage_account_name": "{StorageAccountName}",
    "container_name": "{ContainerName}",
    "namespace_name": "{NamespaceName}",
    "event_hub_name": "{EventHubName}",
    "partition_id": "{PartitionId}",
    "creation_time_utc": "{YYYY}/{MM}/{DD}/{HH}/{mm}/{ss}"
}

For example, a captured file might look like:

/web/logs/2023/10/27/15/30/05/yournamespace/youreventhub/0/yourcapturefile.avro

Use Cases for Capture

• Data Archival: Store historical event data for compliance, auditing, or long-term analysis.
• Batch Analytics: Process large volumes of event data offline using big data processing frameworks.
• Machine Learning: Train machine learning models on historical event streams.
• Data Warehousing: Load captured data into data warehouses for business intelligence.
• Troubleshooting and Debugging: Replay events from storage to diagnose issues.

Limitations and Considerations

• Capture is not designed for real-time processing. For real-time scenarios, consider using Event Hubs with Azure Stream Analytics or Azure Functions.
• Ensure sufficient capacity in your Event Hubs namespace to handle the ingress of events.
• Monitor your storage account for costs and performance.

By leveraging Event Hubs Capture, you can create a robust and scalable solution for managing and analyzing your streaming event data.