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Copy file name to clipboardExpand all lines: articles/app-service/samples-terraform.md
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@@ -20,4 +20,5 @@ The following table includes links to Terraform scripts.
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|**Create app**||
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|[Create two apps and connect securely with Private Endpoint and VNet integration](./scripts/terraform-secure-backend-frontend.md)| Creates two App Service apps and connect apps together with Private Endpoint and VNet integration. |
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|[Provision App Service and use slot swap to deploy](/azure/developer/terraform/provision-infrastructure-using-azure-deployment-slots)| Provision App Service infrastructure with Azure deployment slots. |
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|[Create an Azure Windows web app with a backup](./scripts/terraform-backup.md)| Create an Azure Windows web app with a backup schedule. |
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|[Create an Azure Windows web app with a backup](./scripts/terraform-backup.md)| Create an Azure Windows web app with a backup schedule. |
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|[Create a Windows container app on App Service](/azure/app-service/provision-resource-terraform?tabs=windows-container)| Create an Azure Windows web app with a backup schedule. |
Copy file name to clipboardExpand all lines: articles/azure-health-insights/radiology-insights/get-started.md
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This quickstart provides an overview on how to use the Radiology Insights.
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## Prerequisites
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To use the Radiology Insights (Preview) model, you must have an Azure AI Health Insights service created.
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To use the Radiology Insights model, you must have an Azure AI Health Insights service created.
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If you have no Azure AI Health Insights service, see [Deploy Azure AI Health Insights using the Azure portal.](../deploy-portal.md)
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If you have an Azure AI Health Insights service, you must link it to an Azure AI Language resource to enable Text Analytics for Health by the Health Insight AI models.
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Once deployment is complete, you use the Azure portal to navigate to the newly created Azure AI Health Insights service to see the details, including your Service URL.
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The Service URL to access your service is: https://```YOUR-NAME```.cognitiveservices.azure.com.
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#### Pending tasks
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With this autoscale formula, the pool is initially created with a single VM. The `$PendingTasks` metric defines the number of tasks that are running or queued. The formula finds the average number of pending tasks in the last 180 seconds and sets the `$TargetDedicatedNodes` variable accordingly. The formula ensures that the target number of dedicated nodes never exceeds 25 VMs. As new tasks are submitted, the pool automatically grows. As tasks complete, VMs become free and the autoscaling formula shrinks the pool.
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With this autoscale formula, the pool is initially created with a single VM. The `$PendingTasks` metric defines the number of tasks that are running or queued. The formula finds the average number of pending tasks in the last 15 minutes and sets the `$TargetDedicatedNodes` variable accordingly. The formula ensures that the target number of dedicated nodes never exceeds 25 VMs. As new tasks are submitted, the pool automatically grows. As tasks complete, VMs become free and the autoscaling formula shrinks the pool.
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This formula scales dedicated nodes, but can be modified to apply to scale Spot nodes as well.
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