Repo sync for protected branch

data-explorer/flow.md

@@ -1,12 +1,14 @@
 ---
-title: Azure Data Explorer connector for Power Automate
+title: Azure Data Explorer Connector for Power Automate
 description: Learn about using Azure Data Explorer connector for Power Automate to create flows of automatically scheduled or triggered tasks.
+#customer intent: As a Power Automate user, I want to create flows using the Azure Data Explorer connector so that I can automate tasks and send notifications based on query results.
 ms.reviewer: miwalia
 ms.topic: how-to
-ms.date: 08/15/2024
+ms.date: 09/24/2025
 no-loc: [Power Automate]
 ---
 
+
 # Azure Data Explorer connector for Microsoft Power Automate
 
 [!INCLUDE [real-time-analytics-connectors-note](includes/real-time-analytics-connectors-note.md)]
@@ -59,7 +61,7 @@ To use the connector, you must first add a trigger. You can define a trigger bas
 
 When you select the Azure Data Explorer connector, you can choose one of the following actions to add to your flow:
 
-- [Run KQL query](#run-kql-query)
+- [Run Kusto Query Language (KQL) query](#run-kql-query)
 - [Run KQL query and render a chart](#run-kql-query-and-render-a-chart)
 - [Run async management command](#run-async-management-command)
 - [Run management command and render a chart](#run-management-command-and-render-a-chart)
@@ -74,7 +76,7 @@ This section describes the capabilities and parameters for each action and provi
 
 Use this action to query the specified cluster. The actions that are added afterwards iterate over each line of the results of the query.
 
-If the query takes more than 8 minutes to run, it will fail with a "RequestTimeout" exception. To prevent this issue, optimize your query or divide it into smaller parts. For more information, see [Query best practices](/kusto/query/best-practices?view=azure-data-explorer&preserve-view=true).
+If the query takes more than 8 minutes to run, it fails with a "RequestTimeout" exception. To prevent this issue, optimize your query or divide it into smaller parts. For more information, see [Query best practices](/kusto/query/best-practices?view=azure-data-explorer&preserve-view=true).
 
 #### Example
 
@@ -89,43 +91,43 @@ The following flow triggers a query every minute. The query checks the number of
 
 Use this action to visualize a KQL query result as a table or chart. For example, use this flow to receive daily reports by email.
 
-If the query takes more than 8 minutes to run, it will fail with a "RequestTimeout" exception. To prevent this issue, optimize your query or divide it into smaller parts. For more information, see [Query best practices](/kusto/query/best-practices?view=azure-data-explorer&preserve-view=true).
+If the query takes more than 8 minutes to run, it fails with a "RequestTimeout" exception. To prevent this issue, optimize your query or divide it into smaller parts. For more information, see [Query best practices](/kusto/query/best-practices?view=azure-data-explorer&preserve-view=true).
 
 #### Example
 
-The following flow will present the query results as a timechart.
+The following flow presents the query results as a timechart.
 
 :::image type="content" source="media/flow/flow-run-query.png" alt-text="Screenshot of Azure Data Explorer connector, showing the Run KQL query and render a chart action.":::
 
 ### Run async management command
 
-Use this action to run a [management command](/kusto/management/index?view=azure-data-explorer&preserve-view=true) asynchronously, which means it will continue to run in the background. The action returns an ID, state, and status. To check the status and details of an async command, use the [.show operations](/kusto/management/show-operations?view=azure-data-explorer&preserve-view=true) command with the ID returned by this action.
+Use this action to run a [management command](/kusto/management/index?view=azure-data-explorer&preserve-view=true) asynchronously, which means it continues to run in the background. The action returns an ID, state, and status. To check the status and details of an async command, use the [`.show operations`](/kusto/management/show-operations?view=azure-data-explorer&preserve-view=true) command with the ID returned by this action.
 
-If the async management command takes more than 60 minutes to run, it will fail with a "RequestTimeout" exception.
+If the async management command takes more than 60 minutes to run, it fails with a "RequestTimeout" exception.
 
 #### Example
 
-The following flow triggers an async command to copy 10 records from the 'TransformedSysLogs' table to the 'TargetTable'. Note that the 'async' keyword is required in the query.
+The following flow triggers an async command to copy 10 records from the TransformedSysLogs table to the TargetTable. The `async` keyword is required in the query.
 
 :::image type="content" source="media/flow/flow-run-async-control-command.png" alt-text="Screenshot of Azure Data Explorer connector, showing the Run async management command action.":::
 
 ### Run management command and render a chart
 
 Use this action to run a [management command](/kusto/management/index?view=azure-data-explorer&preserve-view=true) and display the result as a chart. The chart options include an HTML table, pie chart, time chart, and bar chart.
 
-If the management command takes more than 8 minutes to run, it will fail with a "RequestTimeout" exception.
+If the management command takes more than 8 minutes to run, it fails with a "RequestTimeout" exception.
 
 :::image type="content" source="media/flow/flow-run-control-command.png" alt-text="Screenshot of Run management command and render a chart in recurrence pane.":::
 
 ### Run show management command
 
 This action runs the show management command and returns the result that can be used in the following connectors.
 
-If the management command takes more than 8 minutes to run, it will fail with a "RequestTimeout" exception.
+If the management command takes more than 8 minutes to run, it fails with a "RequestTimeout" exception.
 
 #### Example
 
-The following flow runs the [.show operation](/kusto/management/show-operations?view=azure-data-explorer&preserve-view=true) command to find the status of an async command using an operation ID returned by an async command execution.
+The following flow runs the [`.show operation`](/kusto/management/show-operations?view=azure-data-explorer&preserve-view=true) command to find the status of an async command using an operation ID returned by an async command execution.
 
 :::image type="content" source="media/flow/flow-run-show-control-command.png" alt-text="Screenshot of Azure Data Explorer connector, showing the Run show management command action.":::
 
@@ -157,7 +159,7 @@ To run a flow that contains an Azure Data Explorer connector, you must use a val
 
 The following steps show how to create a connection from within a flow.
 
-1. In **Run KQL query**, select the three dots at the top right of the power automate connector.
+1. In **Run KQL query**, select the three dots at the top right of the Power Automate connector.
 
     :::image type="content" source="media/flow/flow-add-connection.png" alt-text="Screenshot of Azure Data Explorer connection, showing the authentication option.":::
 
@@ -174,7 +176,7 @@ To authenticate with a Service Principal:
 1. Select **Connect with Service Principal**.
 1. Fill out the form with the following information:
 
-    - **Connection Name**: A descriptive and meaningful name for the new connection. In this example, we've used "MyApplication".
+    - **Connection Name**: A descriptive and meaningful name for the new connection. In this example, we've used **MyApplication**.
     - **Client ID**: Your application ID.
     - **Client Secret**: Your application key.
     - **Tenant**: The ID of the Microsoft Entra directory in which you created the application.
@@ -210,7 +212,7 @@ To check if your flow works, check the flow's run history:
 
     :::image type="content" source="media/flow/flow-full-details.png" alt-text="Screenshot of Run history full results page.":::
 
-To see why a run failed, select the run start time. The flow appears, and the step of the flow that failed is indicated by a red exclamation point. Expand the failed step to view its details. The **Details** pane on the right contains information about the failure so that you can troubleshoot it.
+To see why a run failed, select the run start time. The flow appears, and the step of the flow that failed is indicated by a red exclamation point. Expand the failed step to view its details. The **Details** pane to the right contains information about the failure so that you can troubleshoot it.
 
 :::image type="content" source="media/flow/flow-error.png" alt-text="Screenshot of flow run, showing an error message.":::
 

data-explorer/manage-cluster-vertical-scaling.md

@@ -1,40 +1,43 @@
 ---
-title: 'Manage cluster vertical scaling (scale up) to match demand in Azure Data Explorer'
-description: This article describes steps to scale up and scale down an Azure Data Explorer cluster based on changing demand.
+title: "Scale Azure Data Explorer Clusters Vertically to Match Demand"
+description: Learn how to scale up or down your Azure Data Explorer cluster to match changing demand and optimize performance with minimal service disruption.
+#customer intent: As an Azure admin, I want to scale up an Azure Data Explorer cluster so that I can handle increased demand efficiently.
 ms.reviewer: radennis
 ms.topic: how-to
-ms.date: 12/17/2023
+ms.date: 09/24/2025
 ---
 
-# Manage cluster vertical scaling (scale up) in Azure Data Explorer to accommodate changing demand
 
-Sizing a cluster appropriately is critical to the performance of Azure Data Explorer. A static cluster size can lead to under-utilization or over-utilization, neither of which is ideal.
+# Manage cluster vertical scaling (scale up) in Azure Data Explorer to accommodate changing demand
 
-Since demand on a cluster can't be predicted with absolute accuracy, a better approach is to *scale* a cluster, adding and removing capacity and CPU resources with changing demand.
+Azure Data Explorer cluster performance depends on appropriate sizing to match your workload demands. When demand changes, you can scale your cluster vertically by changing the Stock Keeping Unit (SKU) to add or remove CPU and memory resources.
 
-There are two workflows for scaling an Azure Data Explorer cluster:
+Vertical scaling (scaling up or down) changes the compute power of your cluster by switching to a different SKU with more or fewer resources. This process maintains your data while upgrading or downgrading the underlying infrastructure to better match your performance needs.
 
-* [Horizontal scaling](manage-cluster-horizontal-scaling.md), also called scaling in and out.
-* Vertical scaling, also called scaling up and down.
+Use vertical scaling when you need to:
+- Handle increased query complexity or data processing requirements
+- Optimize costs by moving to a more appropriate SKU
+- Improve performance for CPU or memory-intensive workloads
 
-This article explains the vertical scaling workflow:
+> [!NOTE]
+> To learn about horizontal scaling, see [horizontal scaling](manage-cluster-horizontal-scaling.md). One of the reasons you might want to scale the cluster horizontally is when you need to handle massive traffic loads that exceed what a single server can manage.
 
 ## Configure vertical scaling
 
 1. In the Azure portal, go to your Azure Data Explorer cluster resource. Under **Settings**, select **Scale up**.
-1. In the **Scale up** window, you'll see available SKUs for your cluster. For example, in the following figure, there are eight recommended SKUs available. Expand the **Storage optimized**, **Compute optimized**, and **Dev/test** dropdowns to see more options.
+1. In the **Scale up** window, you see available (Stock Keeping Unit) SKUs for your cluster. For example, in the following figure, there are eight recommended SKUs available. Expand the **Storage optimized**, **Compute optimized**, and **Dev/test** dropdowns to see more options.
 
-    ![Scale up.](media/manage-cluster-vertical-scaling/scale-up.png)
+    :::image type="content" source="media/manage-cluster-vertical-scaling/scale-up.png" alt-text="Screenshot of the Scale up window in Azure portal showing eight recommended SKUs with dropdowns for Storage optimized, Compute optimized, and Dev/test." lightbox="media/manage-cluster-vertical-scaling/scale-up.png":::
 
     The SKUs are disabled because they're the current SKU, or they aren't available in the region where the cluster is located.
 1. To change your SKU, select a new SKU and then select **Apply**.
 
     > [!NOTE]
     >
-    > * During the vertical scaling process, while a new cluster's resources are prepared the old cluster's resources continuing to provide service. This process may take tens of minutes. Only when the new cluster's resources are ready, switchover is performed to the new cluster. The parallel process makes the SKU migration experience relatively seamless, with minimal service disruption during the switchover process that takes about one to three minutes to complete. Query performance may be impacted during SKU migration. The impact may vary due to usage patterns.
+    > * During the vertical scaling process, while a new cluster's resources are prepared, the old cluster's resources continuing to provide service. This process might take tens of minutes. Only when the new cluster's resources are ready, switchover is performed to the new cluster. The parallel process makes the SKU migration experience relatively seamless, with minimal service disruption during the switchover process that takes about one to three minutes to complete. Query performance might be impacted during SKU migration. The impact might vary due to usage patterns.
     > * We recommend enabling [Optimized Autoscale](/azure/data-explorer/manage-cluster-horizontal-scaling) to allow the cluster to scale-in following migration. For SKU migration recommendation, see [Change Data Explorer clusters to a more cost effective and better performing SKU](/azure/data-explorer/azure-advisor).
-    > * Clusters with Virtual Network configuration may experience longer service disruptions.
-    > * The price is an estimate of the cluster's virtual machines and Azure Data Explorer service costs. Other costs are not included. For an estimate, see the Azure Data Explorer [cost estimator](https://dataexplorer.azure.com/AzureDataExplorerCostEstimator.html). For full pricing, see the Azure Data Explorer [pricing page](https://azure.microsoft.com/pricing/details/data-explorer/).
+    > * Clusters with Virtual Network configuration might experience longer service disruptions.
+    > * The price is an estimate of the cluster's virtual machines and Azure Data Explorer service costs. Other costs aren't included. For an estimate, see the Azure Data Explorer [cost estimator](https://dataexplorer.azure.com/AzureDataExplorerCostEstimator.html). For full pricing, see the Azure Data Explorer [pricing page](https://azure.microsoft.com/pricing/details/data-explorer/).
 
 You've now configured vertical scaling for your Azure Data Explorer cluster. Add another rule for a horizontal scaling. If you need assistance with cluster-scaling issues, [open a support request](https://portal.azure.com/#blade/Microsoft_Azure_Support/HelpAndSupportBlade/overview) in the Azure portal.
 

data-explorer/start-for-free.md

@@ -1,18 +1,20 @@
 ---
-title: Start for free using Azure Data Explorer
-description: This article shows you how to get started with a free Azure Data Explorer cluster.
+title: Start for Free with Azure Data Explorer
+description: Start exploring Azure Data Explorer with a free cluster—no subscription or credit card required. Learn how to create, query, and manage your data today.
+#customer intent: As a new user, I want to create a free Azure Data Explorer cluster so that I can explore its features without needing an Azure subscription.
 ms.reviewer: avnera
 ms.topic: how-to
-ms.date: 07/02/2023
+ms.date: 09/24/2025
 ---
 
+
 # What is a free Azure Data Explorer cluster?
 
 Free cluster allows anyone with a Microsoft account or a Microsoft Entra user identity to create a [free Azure Data Explorer cluster](start-for-free-web-ui.md) without needing an Azure subscription or a credit card.
 
 The free cluster can be used for any purpose and is the ideal solution for anyone who wants to get started quickly with Azure Data Explorer. It allows you to explore the wide range of [data ingestion](ingest-data-overview.md) methods, use the [Kusto Query Language](/kusto/query/index?view=azure-data-explorer&preserve-view=true), and experience the incredible ingestion and query performance.
 
-The cluster's trial period is for a year and may automatically be extended. The cluster is provided *as-is* and isn't subject to the Azure Data Explorer service level agreement. At any time, you can upgrade the cluster to a full Azure Data Explorer cluster.
+The cluster's trial period is for a year and might automatically be extended. The cluster is provided *as-is* and isn't subject to the Azure Data Explorer service level agreement. At any time, you can upgrade the cluster to a full Azure Data Explorer cluster.
 
 Start your journey by [creating your own free cluster](https://aka.ms/kustofree) and reviewing the [Microsoft Software License Terms](https://aka.ms/kustofreeeula).