1. Blue-Green Deployments for AI Services on Azure App Service

    Python

    Blue-Green deployment is a strategy for updating applications with minimal downtime and risk by maintaining two identical production environments, only one of which serves live production traffic at any time. For example, the Blue environment may be the active production environment, while the Green is the staged or pre-production environment which includes the new code changes.

    When you're ready to deploy new changes, you update the Green environment. After testing to ensure that the changes are successful in the Green environment, you can then switch the router so all incoming requests now go to Green instead of Blue. If issues are detected after the swap, you can revert back to the Blue environment by switching the router back.

    In Azure App Service, Blue-Green deployments can be implemented using deployment slots. Deployment slots are live web apps with their own hostnames. App content and configurations elements can be swapped between two deployment slots, including the production slot.

    Here's how you can implement a Blue-Green deployment for AI services using Pulumi to manage the Azure App Service resources:

    1. Create an Azure App Service Plan, which defines the region and the size of the server farm.
    2. Create an Azure App Service, which represents your main application.
    3. Create two deployment slots for the Azure App Service: one for Blue and one for Green.
    4. Set up the necessary application settings and configurations for each slot.
    5. Deploy your app to the Green slot.
    6. Test your changes in the Green slot.
    7. Once you're ready, swap the Green slot with the production slot.
    8. If something goes wrong, swap back the slots to revert to the original state.

    Below is a Pulumi program that sets up a basic Blue-Green deployment scenario using Azure App Service:

    import pulumi import pulumi_azure_native as azure_native # Configuration for your Azure resource group and location resource_group = azure_native.resources.ResourceGroup('resource_group') # Create an App Service plan app_service_plan = azure_native.web.AppServicePlan('app-service-plan', resource_group_name=resource_group.name, kind='Linux', reserved=True, # Must be true for Linux plans sku=azure_native.web.SkuDescriptionArgs( tier='Basic', name='B1', size='B1', family='B', capacity=1, ), location=resource_group.location ) # Create an App Service for your AI service app_service = azure_native.web.WebApp('app-service', resource_group_name=resource_group.name, server_farm_id=app_service_plan.id, location=resource_group.location, site_config=azure_native.web.SiteConfigArgs( app_settings=[ azure_native.web.NameValuePairArgs(name='WEBSITES_ENABLE_APP_SERVICE_STORAGE', value='false') ], # Configure any other required settings... ) ) # Create a deployment slot for the Blue environment blue_slot = azure_native.web.WebAppSlot('blue-slot', name=app_service.name, slot='blue', resource_group_name=resource_group.name ) # Create a deployment slot for the Green environment green_slot = azure_native.web.WebAppSlot('green-slot', name=app_service.name, slot='green', resource_group_name=resource_group.name ) # When you are ready to deploy to the Green slot, you can use pulumi up # to update and apply the changes to the green slot. After testing and # validating the changes in the Green slot, you can swap it with the production slot # For example: # azure_native.web.WebAppSwapSlotWithProduction(f"swap-slot",{ # "target_slot": "production", # "resource_group_name": resource_group_name, # "name": app_service_name, # }) # Export the endpoints for the Blue and Green slots as stack outputs pulumi.export('blue_endpoint', pulumi.Output.concat('https://', blue_slot.default_host_name)) pulumi.export('green_endpoint', pulumi.Output.concat('https://', green_slot.default_host_name))

    This code sets up two deployment slots in which you can deploy your AI service application. You should deploy your new changes to the Green slot and test them. Once you are confident in the changes, you can use the WebAppSwapSlotWithProduction function (commented out in the code) to swap Green into production. If you encounter any problems with the new changes in production, you can swap back, effectively rolling back the changes.

    Remember to add AI service-specific configurations in the site_config section under the WebApp resource and in the deployment slot configurations if necessary. Also, upon swapping slots, the settings configured in the App Service are swapped as well, so ensure that all slot-specific settings are labeled as "Slot settings" in the Azure Portal or configured correctly in Pulumi to be maintained across swaps.

    For more information on the Azure App Service Plan, Azure App Service, and deployment slots used in this program, refer to the following documentation:


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