1. Durable Event Storage for AI Event Sourcing with Azure Event Hubs


    To create a durable event storage solution for AI event sourcing using Azure, we'll take advantage of Azure Event Hubs. Event Hubs is a fully managed, real-time data ingestion service that’s highly scalable and capable of streaming millions of events per second. Events can be stored for later processing or real-time analytics. We will use Pulumi's infrastructure as code approach to define and deploy our resources to Azure.

    We'll define an Event Hubs Namespace, an Event Hub, and configure the Event Hub to ensure it retains events for a durable period (which can be up to 7 days on the standard tier), and enable the Capture feature to automatically save the streaming data to a blob storage for long-term retention.

    Here's a basic overview of the components we’ll set up:

    • Event Hubs Namespace: A namespace is a scoping container for multiple Event Hubs.
    • Event Hub: Where the events are sent. Each Event Hub corresponds to a consumer group or category of related events.
    • Capture Feature: An automated way to save the incoming events to a Blob storage or an Azure Data Lake service.

    Below is a Python program that uses Pulumi to set up these resources. We will define the necessary components using azure-native package, which is the Pulumi provider for Azure. Ensure you have the Pulumi CLI and Azure provider set up before running this program.

    import pulumi import pulumi_azure_native.eventhub as eventhub import pulumi_azure_native.resources as resources import pulumi_azure_native.storage as storage # Create an Azure Resource Group resource_group = resources.ResourceGroup('eventhub-rg') # Create an Azure Storage Account for long-term storage storage_account = storage.StorageAccount('storacc', resource_group_name=resource_group.name, kind=storage.Kind.STORAGE_V2, sku=storage.SkuArgs(name=storage.SkuName.STANDARD_LRS)) # Create an Azure Storage Blob Container where the captured data will be stored blob_container = storage.BlobContainer('eventcontainer', account_name=storage_account.name, resource_group_name=resource_group.name, public_access=storage.PublicAccess.NONE) # Create an Event Hubs Namespace event_hub_namespace = eventhub.Namespace('eventhubnamespace', resource_group_name=resource_group.name, sku=eventhub.SkuArgs( name=eventhub.SkuName.STANDARD )) # Create an Event Hub with Capture enabled for long-term storage event_hub = eventhub.EventHub('eventhub', resource_group_name=resource_group.name, namespace_name=event_hub_namespace.name, message_retention_in_days=7, partition_count=2, capture_description=eventhub.CaptureDescriptionArgs( enabled=True, encoding=eventhub.EncodingCaptureDescription.AVRO, interval_in_seconds=300, size_limit_in_bytes=314572800, # 300 MB destination=eventhub.DestinationArgs( name="EventHubArchive.AzureBlockBlob", blob_container=blob_container.name, archive_name_format="{Namespace}/{EventHub}/{PartitionId}/{Year}/{Month}/{Day}/{Hour}/{Minute}/{Second}", storage_account_resource_id=storage_account.id ) )) # Exporting the Event Hub connection string and Storage Account name primary_connection_string = pulumi.Output.all(resource_group.name, event_hub_namespace.name) \ .apply(lambda args: eventhub.list_namespace_keys(resource_group_name=args[0], namespace_name=args[1])) \ .apply(lambda list_keys: list_keys.primary_connection_string) pulumi.export('Primary Event Hub Connection String', primary_connection_string) pulumi.export('Storage Account Name', storage_account.name)

    In the program above, the pulumi_azure_native.eventhub.Namespace and pulumi_azure_native.eventhub.EventHub are used to create the namespace and event hub respectively. We've enabled the Capture feature on the Event Hub to save the data to Azure Blob storage created using pulumi_azure_native.storage.StorageAccount and pulumi_azure_native.storage.BlobContainer.

    We’ve also exported the primary connection string of the Event Hub namespace, which you may need to send events to your Event Hub, and the name of the storage account being used for long-term retention.

    To deploy these resources, save the program into a file, for example main.py. Run pulumi up and follow the prompts to authenticate with Azure if you haven't already done so.

    Remember to destroy the resources with pulumi destroy when you no longer need them to avoid incurring unnecessary costs.