Merge pull request #215031 from EdB-MSFT/autoscale-supported-services

updated supported services

Author: prmerger-automator[bot]

articles/azure-monitor/autoscale/autoscale-overview.md

@@ -34,7 +34,7 @@ When the conditions in the rules are met, one or more autoscale actions are trig
 
 ## Scaling out and scaling up
 
-Autoscale scales in and out, which is an increase, or decrease of the number of resource instances. Scaling in and out is also called horizontal scaling. For example, for a virtual machine scale set, scaling out means adding more virtual machines. Scaling in means removing virtual machines. Horizontal scaling is flexible in a cloud situation as it allows you to run a large number of VMs to handle load.
+Autoscale scales in and out, which is an increase, or decrease of the number of resource instances. Scaling in and out is also called horizontal scaling. For example, for a Virtual Machine Scale Set, scaling out means adding more virtual machines. Scaling in means removing virtual machines. Horizontal scaling is flexible in a cloud situation as it allows you to run a large number of VMs to handle load.
 
 In contrast, scaling up and down, or vertical scaling, keeps the number of resources constant, but gives those resources more capacity in terms of memory, CPU speed, disk space and network. Vertical scaling is limited by the availability of larger hardware, which eventually reaches an upper limit. Hardware size availability varies in Azure by region. Vertical scaling may also require a restart of the virtual machine during the scaling process.
 
@@ -44,7 +44,7 @@ When the conditions in the rules are met, one or more autoscale actions are trig
 
 ### Predictive autoscale (preview)
 
-[Predictive autoscale](./autoscale-predictive.md) uses machine learning to help manage and scale Azure virtual machine scale sets with cyclical workload patterns. It forecasts the overall CPU load on your virtual machine scale set, based on historical CPU usage patterns. The scale set can then be scaled out in time to meet the predicted demand.
+[Predictive autoscale](./autoscale-predictive.md) uses machine learning to help manage and scale Azure Virtual Machine Scale Sets with cyclical workload patterns. It forecasts the overall CPU load on your Virtual Machine Scale Set, based on historical CPU usage patterns. The scale set can then be scaled out in time to meet the predicted demand.
 
 ## Autoscale setup
 
@@ -63,7 +63,7 @@ The following diagram shows the autoscale architecture.
 
 ### Resource metrics
 
-Resources generate metrics that are used in autoscale rules to trigger scale events. Virtual machine scale sets use telemetry data from Azure diagnostics agents to generate metrics. Telemetry for Web apps and Cloud services comes directly from the Azure Infrastructure. Some commonly used metrics include CPU usage, memory usage, thread counts, queue length, and disk usage. See [Autoscale Common Metrics](autoscale-common-metrics.md) for a list of available metrics.
+Resources generate metrics that are used in autoscale rules to trigger scale events. Virtual Machine Scale Sets use telemetry data from Azure diagnostics agents to generate metrics. Telemetry for Web apps and Cloud services comes directly from the Azure Infrastructure. Some commonly used metrics include CPU usage, memory usage, thread counts, queue length, and disk usage. See [Autoscale Common Metrics](autoscale-common-metrics.md) for a list of available metrics.
 
 ### Custom metrics
 
@@ -117,12 +117,12 @@ The full list of configurable fields and descriptions is available in the [Autos
 
 For code examples, see
 
-* [Tutorial: Automatically scale a virtual machine scale set with an Azure template](https://learn.microsoft.com/azure/virtual-machine-scale-sets/tutorial-autoscale-template)
-* [Tutorial: Automatically scale a virtual machine scale set with the Azure CLI](https://learn.microsoft.com/azure/virtual-machine-scale-sets/tutorial-autoscale-cli)
-* [Tutorial: Automatically scale a virtual machine scale set with an Azure template](https://learn.microsoft.com/azure/virtual-machine-scale-sets/tutorial-autoscale-powershell)
+* [Tutorial: Automatically scale a Virtual Machine Scale Set with an Azure template](https://learn.microsoft.com/azure/virtual-machine-scale-sets/tutorial-autoscale-template)
+* [Tutorial: Automatically scale a Virtual Machine Scale Set with the Azure CLI](https://learn.microsoft.com/azure/virtual-machine-scale-sets/tutorial-autoscale-cli)
+* [Tutorial: Automatically scale a Virtual Machine Scale Set with an Azure template](https://learn.microsoft.com/azure/virtual-machine-scale-sets/tutorial-autoscale-powershell)
 ## Horizontal vs vertical scaling
 
-Autoscale scales horizontally, which is an increase, or decrease of the number of resource instances. For example, in a virtual machine scale set, scaling out means adding more virtual machines Scaling in means removing virtual machines. Horizontal scaling is flexible in a cloud situation as it allows you to run a large number of VMs to handle load.
+Autoscale scales horizontally, which is an increase, or decrease of the number of resource instances. For example, in a Virtual Machine Scale Set, scaling out means adding more virtual machines Scaling in means removing virtual machines. Horizontal scaling is flexible in a cloud situation as it allows you to run a large number of VMs to handle load.
 
 In contrast, vertical scaling, keeps the same number of resources constant, but gives them more capacity in terms of memory, CPU speed, disk space and network. Adding or removing capacity in vertical scaling is known as scaling or down. Vertical scaling is limited by the availability of larger hardware, which eventually reaches an upper limit. Hardware size availability varies in Azure by region. Vertical scaling may also require a restart of the virtual machine during the scaling process.
 
@@ -132,22 +132,26 @@ The following services are supported by autoscale:
 
 | Service | Schema & Documentation |
 | --- | --- |
-| Azure Virtual machines scale sets |[Overview of autoscale with Azure virtual machine scale sets](../../virtual-machine-scale-sets/virtual-machine-scale-sets-autoscale-overview.md) |
+| Azure Virtual machines scale sets |[Overview of autoscale with Azure Virtual Machine Scale Sets](../../virtual-machine-scale-sets/virtual-machine-scale-sets-autoscale-overview.md) |
 | Web apps |[Scaling Web Apps](autoscale-get-started.md) |
 | Azure API Management service|[Automatically scale an Azure API Management instance](../../api-management/api-management-howto-autoscale.md)
 | Azure Data Explorer Clusters|[Manage Azure Data Explorer clusters scaling to accommodate changing demand](/azure/data-explorer/manage-cluster-horizontal-scaling)|
 | Azure Stream Analytics | [Autoscale streaming units (Preview)](../../stream-analytics/stream-analytics-autoscale.md) |
 | Azure Machine Learning Workspace | [Autoscale an online endpoint](../../machine-learning/how-to-autoscale-endpoints.md) |
+ Spring Cloud |[Set up autoscale for microservice applications](../../spring-apps/how-to-setup-autoscale.md)|
+| Media Services | [Autoscaling in Media Services](/azure/media-services/latest/release-notes#autoscaling) |
+| Service Bus |[Automatically update messaging units of an Azure Service Bus namespace](../../service-bus-messaging/automate-update-messaging-units.md)|
+| Logic Apps - Integration Service Environment(ISE) | [Add ISE capacity](../../logic-apps/ise-manage-integration-service-environment.md#add-ise-capacity) |
 
 ## Next steps
 
 To learn more about autoscale, see the following resources:
 
 * [Azure Monitor autoscale common metrics](autoscale-common-metrics.md)
 * [Use autoscale actions to send email and webhook alert notifications](autoscale-webhook-email.md)
-* [Tutorial: Automatically scale a virtual machine scale set with an Azure template](https://learn.microsoft.com/azure/virtual-machine-scale-sets/tutorial-autoscale-template)
-* [Tutorial: Automatically scale a virtual machine scale set with the Azure CLI](https://learn.microsoft.com/azure/virtual-machine-scale-sets/tutorial-autoscale-cli)
-* [Tutorial: Automatically scale a virtual machine scale set with an Azure template](https://learn.microsoft.com/azure/virtual-machine-scale-sets/tutorial-autoscale-powershell)
+* [Tutorial: Automatically scale a Virtual Machine Scale Set with an Azure template](https://learn.microsoft.com/azure/virtual-machine-scale-sets/tutorial-autoscale-template)
+* [Tutorial: Automatically scale a Virtual Machine Scale Set with the Azure CLI](https://learn.microsoft.com/azure/virtual-machine-scale-sets/tutorial-autoscale-cli)
+* [Tutorial: Automatically scale a Virtual Machine Scale Set with Azure PowerShell](https://learn.microsoft.com/azure/virtual-machine-scale-sets/tutorial-autoscale-powershell)
 * [Autoscale CLI reference](https://learn.microsoft.com/cli/azure/monitor/autoscale?view=azure-cli-latest)
 * [ARM template resource definition](https://learn.microsoft.com/azure/templates/microsoft.insights/autoscalesettings)
 * [PowerShell Az.Monitor Reference](https://learn.microsoft.com/powershell/module/az.monitor/#monitor)