1. Collaborative AI Development via Shared Azure Dashboards


    To facilitate collaborative AI development using Azure, one approach is to set up shared dashboards. These shared dashboards can help team members monitor and analyze different metrics, KPIs, and data related to AI projects in a centralized location.

    In the Azure ecosystem, you can implement shared dashboards using azure-native.portal.Dashboard. This Azure resource provides a way to create, update, and manage dashboards in the Azure portal, which can be customized with various tiles representing different insights and data points relevant to the AI projects. It's a place where team members can simultaneously view and interact with different analytics and data visualizations.

    Below is a Pulumi Python program that demonstrates how to create an Azure shared dashboard with a couple of tiles for displaying text and a metric. You can tailor the dashboard by adding different types of tiles such as markdown content, web tests, and more, to fit the exact needs of your AI development project.

    import pulumi import pulumi_azure_native.portal as azure_portal # Create an Azure resource group which will contain all the resources. resource_group = azure_portal.ResourceGroup("ai_resource_group") # Create a shared Dashboard in the resource group we just defined. # This Dashboard is an empty canvas, where you can specify the structure # of your Dashboard using your desired configuration. dashboard = azure_portal.Dashboard( "ai_shared_dashboard", resource_group_name=resource_group.name, location="East US", # You can specify the location where the dashboard is created. properties={ # Properties to define the dashboard structure. "lenses": [{ # Lenses are the panels that contain tiles. "order": 1, "parts": [{ # Parts are individual tiles within a lens. "position": { "x": 0, "y": 0, "colSpan": 3, "rowSpan": 4 }, "metadata": { "inputs": [], "settings": { "content": { "settings": { "markdown": """ # Welcome to our AI Project Dashboard Here you can find real-time analytics and metrics for our AI services. """ } }, "type": "Extension/HubsExtension/MarkdownTile" } } }, { "position": { "x": 3, "y": 0, "colSpan": 3, "rowSpan": 4 }, "metadata": { "inputs": [], "settings": { "content": { "settings": { # Here you would specify the ID of the metric or resource you wish to display. "resourceId": "/subscriptions/{subscription_id}/resourceGroups/{resource_group_name}/providers/Microsoft.Insights/metrics/", "metric": "CpuPercentage", "timeRange": { "value": { "relative": { "duration": 24, "timeUnit": 1 } }, "type": "MsPortalFx.Composition.Configuration.ValueTypes.TimeRange" } } }, "type": "Extension/Microsoft_Azure_Monitoring/PartType/MetricsChartPart" } } }] }], "metadata": { "model": { "timeRange": { "value": { "relative": { "duration": 24, "timeUnit": 1 } } } } } } ) # Export the Dashboard URL so that it can be accessed directly after it's created. pulumi.export("dashboardUrl", dashboard.id.apply(lambda id: f"https://portal.azure.com/#resource{id}"))


    • azure_portal.ResourceGroup: Creates a new Azure resource group in which other resources, including our dashboard, will reside.

    • azure_portal.Dashboard: Defines a new shared Azure dashboard within the specified resource group.

    • location: While Azure dashboards are global resources, you must specify the location that hosts the metadata about the dashboard.

    • properties: Describes the dashboard's content. I've described two tiles in this example:

      • A Markdown tile (MarkdownTile) containing some welcoming text.
      • A Metrics chart tile (MetricsChartPart) that could display a CPU percentage metric. You will need to replace the placeholders with actual resource IDs and metric names relevant to your AI deployment.
    • pulumi.export: Outputs the URL of the created Dashboard so you can easily access it from the Azure portal.

    This program sets the groundwork for collaborative AI development through shared Azure dashboards. You'd continue to customize it with additional tiles and metrics that represent the aspects of the AI systems you and your team are developing or monitoring.