1. Real-Time Telemetry Processing on Azure IoT Hub


    Real-time telemetry processing using Azure IoT Hub involves receiving a continuous stream of data from various IoT devices, analyzing it, and potentially taking actions such as triggering alerts, updating dashboards in real-time, or storing data for further analysis. To implement this on Azure using Pulumi, you would need to provision a few key resources:

    1. Azure IoT Hub: This service acts as the central message hub for bi-directional communication between your IoT application and the devices it manages.
    2. Event Hubs / Event Source: To process the data, Event Hubs can be used as an event ingestion service. Alternatively, Azure Time Series Insights can be set up with an IoT Hub as the event source for real-time analytics.
    3. Stream Analytics Job (optional): For real-time analytics, an Azure Stream Analytics job could be defined to transform or analyze the telemetry data.

    Below is a Pulumi program written in Python that sets up an Azure IoT Hub with an Event Hub endpoint for telemetry ingestion. If you need real-time analytics, this could further be integrated with Azure Stream Analytics or Azure Time Series Insights.

    import pulumi import pulumi_azure_native as azure_native # Resource group for organizing the resources resource_group = azure_native.resources.ResourceGroup('resource_group') # Create an Azure IoT Hub to receive the telemetry from your IoT Devices iot_hub = azure_native.devices.IotHubResource( 'myIotHub', resource_group_name=resource_group.name, sku=azure_native.devices.IotHubSkuInfoArgs( name='S1', # Standard tier capacity=1 # Number of units ), location=resource_group.location, properties=azure_native.devices.IotHubPropertiesArgs( # Event Hub-compatible endpoint for telemetry events. You may have # more fine-grained control on the routes and endpoints used. event_hub_endpoints={ 'events': azure_native.devices.EventHubPropertiesArgs( partition_count=2, retention_time_in_days=1 ) } ) ) # Exports the primary key of the IoT Hub to be used by your devices to connect primary_key = pulumi.Output.all(resource_group.name, iot_hub.name).apply( lambda args: azure_native.devices.list_keys_for_iot_hub( resource_group_name=args[0], resource_name=args[1] ).then(lambda response: next(x.primary_key for x in response.value if x.key_name == 'iothubowner')) ) pulumi.export('iotHubId', iot_hub.id) pulumi.export('iotHubPrimaryKey', primary_key)

    How this code works:

    1. Resource Group: A resource group is a collection of resources in Azure that are managed together.

    2. IoT Hub Resource: This is the Azure IoT Hub service which allows you to manage all your IoT devices. The SKU chosen here is 'S1', which is a standard tier, and the capacity of units to start with is 1. You can adjust the SKU and capacity based on your scenario.

    3. IoT Hub Properties: Inside the IoT Hub resource, we specify properties such as the Event Hub endpoints and relevant configurations like the number of partitions and the retention time for the telemetry data.

    4. List Keys for IoT Hub: This retrieves the primary connection string for the IoT Hub, which is necessary for devices to connect to the IoT Hub. We are searching for a key named 'iothubowner' and extracting its primary key in a secure way using Pulumi's secrets management.

    5. Export: The 'iotHubId' and 'iotHubPrimaryKey' are exported as stack outputs so you can easily retrieve them when you run your Pulumi program.

    Please note, for a full end-to-end telemetry processing solution, you might want to integrate this setup with other services like Azure Functions, Azure Storage, or Azure Stream Analytics for real-time processing. This code establishes the starting point of your IoT infrastructure on Azure using Pulumi.