Merge pull request #294049 from MicrosoftDocs/repo_sync_working_branch

v-alje · web-flow · commit 0634762d7819 · 2025-02-04T09:16:57.000-08:00
Confirm merge from repo_sync_working_branch to main to sync with https://github.com/MicrosoftDocs/azure-docs (branch main)
diff --git a/articles/app-service/configure-basic-auth-disable.md b/articles/app-service/configure-basic-auth-disable.md
@@ -74,7 +74,7 @@ The following table shows how various deployment methods behave when basic authe
 | [GitHub Actions](deploy-continuous-deployment.md?tabs=github) | - An existing GitHub Actions workflow that uses **basic authentication** can't authenticate. In the Deployment Center, disconnect the existing GitHub configuration and create a new GitHub Actions configuration with the **user-assigned identity** option instead. <br/> - If the existing GitHub Actions deployment is [manually configured](deploy-github-actions.md), try using a service principal or OpenID Connect instead. <br/> - For new GitHub Actions configuration in the Deployment Center, use the **user-assigned identity** option. |
 | Deployment in [create wizard](https://portal.azure.com/#create/Microsoft.WebSite) | When **Basic authentication** is set to **Disable** and **Continuous deployment** set to **Enable**, GitHub Actions is configured with the **user-assigned identity** option (OpenID Connect). |
 | [Azure Repos with App Service Build Service](deploy-continuous-deployment.md?tabs=github) | Doesn't work. |
-| [BitBucket](deploy-continuous-deployment.md?tabs=bitbucket) | Doesn't work. |
+| [Bitbucket](deploy-continuous-deployment.md?tabs=bitbucket) | Doesn't work. |
 | [Azure Pipelines](deploy-azure-pipelines.md) with [AzureWebApp](/azure/devops/pipelines/tasks/reference/azure-web-app-v1) task | Works. |
 | [Azure Pipelines](deploy-azure-pipelines.md) with [AzureRmWebAppDeployment](/azure/devops/pipelines/tasks/deploy/azure-rm-web-app-deployment) task | - Use the latest AzureRmWebAppDeployment task to get fallback behavior. <br/> - The **Publish Profile (`PublishProfile`)** connection type doesn't work, because it uses basic authentication. Change the connection type to **Azure Resource Manager (`AzureRM`)**. <br/> - On non-Windows Pipelines agents, authentication works. <br/> - On Windows agents, the [deployment method used by the task](/azure/devops/pipelines/tasks/reference/azure-rm-web-app-deployment-v4#deployment-methods) might need to be modified. When Web Deploy is used (`DeploymentType: 'webDeploy'`) and basic authentication is disabled, the task authenticates with a Microsoft Entra token. There are additional requirements if you're not using the `windows-latest` agent or if you're using a self-hosted agent. For more information, see [I can't Web Deploy to my Azure App Service using Microsoft Entra authentication from my Windows agent](/azure/devops/pipelines/tasks/reference/azure-rm-web-app-deployment-v4#i-cant-web-deploy-to-my-azure-app-service-using-microsoft-entra-id-authentication-from-my-windows-agent).<br/> - Other deployment methods work, such as **zip deploy** or **run from package**. |
 
diff --git a/articles/app-service/deploy-best-practices.md b/articles/app-service/deploy-best-practices.md
@@ -23,7 +23,7 @@ This section describes the three main components for deploying to App Service.
 
 ### Deployment source
 
-A *deployment source* is the location of your application code. For production apps, the deployment source is usually a repository hosted by version control software such as [GitHub, BitBucket, or Azure Repos](deploy-continuous-deployment.md). For development and test scenarios, the deployment source might be [a project on your local machine](deploy-local-git.md).
+A *deployment source* is the location of your application code. For production apps, the deployment source is usually a repository hosted by version control software such as [GitHub, Bitbucket, or Azure Repos](deploy-continuous-deployment.md). For development and test scenarios, the deployment source might be [a project on your local machine](deploy-local-git.md).
 
 ### Build pipeline
 
diff --git a/articles/app-service/manage-backup.md b/articles/app-service/manage-backup.md
@@ -182,6 +182,11 @@ To back up and restore over Azure Virtual Network:
 1. When configuring [custom backups](#create-a-custom-backup), select **Backup/restore over virtual network integration**. 
 1. Save your settings by selecting **Configure**.
 
+To enable backup/restore over virtual network for deployment slots, you need to complete the necessary steps specifically for each slot:
+
+- Virtual network integration is enabled for the deployment slots, or the slot is in a v3 [App Service Environment](environment/overview.md). 
+- The option for backup/restore over virtual network integration is selected for deployment slots.
+
 If you don't see the checkbox, or if the checkbox is disabled, verify that your resources fulfill the requirements. 
 
 Once the configuration is saved, any manual backup, scheduled backup, or restore is made through the virtual network. If you make changes to the app, the virtual network, or the storage account that prevent the app from accessing the storage account through the virtual network, the backup or restore operations fail.
diff --git a/articles/app-service/migrate-wordpress.md b/articles/app-service/migrate-wordpress.md
@@ -71,7 +71,7 @@ The prerequisite is that the WordPress on Linux Azure App Service must have been
 
 ### Manually import the data at destination site
 
-1. Create a new Wordpress app using our [WordPress on Linux App Service template](https://aka.ms/linux-wordpress)
+1. Create a new WordPress app using our [WordPress on Linux App Service template](https://aka.ms/linux-wordpress)
 
 2. Open an SSH session using **WebSSH** from the Azure portal.
 ![Web SSH](./media/app-service-migrate-wordpress/post-startup-script-1.png)
diff --git a/articles/app-service/overview-vnet-integration.md b/articles/app-service/overview-vnet-integration.md
@@ -154,7 +154,7 @@ App settings using Key Vault references attempt to get secrets over the public r
 
 > [!NOTE]
 > * Configure SSL/TLS certificates from private Key Vaults is currently not supported.
-> * App Service Logs to private storage accounts is currently not supported. We recommend using Diagnostics Logging and allowing Trusted Services for the storage account.
+
 
 ### Routing app settings
 
@@ -221,6 +221,7 @@ There are some limitations with using virtual network integration:
 * You can't delete a virtual network with an integrated app. Remove the integration before you delete the virtual network.
 * You can't have more than two virtual network integrations per App Service plan. Multiple apps in the same App Service plan can use the same virtual network integration.
 * You can't change the subscription of an app or a plan while there's an app that's using virtual network integration.
+* App Service Logs to private storage accounts is currently not supported. We recommend using Diagnostics Logging and allowing Trusted Services for the storage account.
 
 ## Access on-premises resources
 
diff --git a/articles/app-service/overview.md b/articles/app-service/overview.md
@@ -27,7 +27,7 @@ Azure App Service is a fully managed platform as a service (PaaS) offering for d
 * **Multiple languages and frameworks** - App Service has first-class support for ASP.NET, ASP.NET Core, Java, Node.js, Python, and PHP. You can also run [PowerShell and other scripts or executables](webjobs-create.md) as background services.
 * **Managed production environment** - App Service automatically [patches and maintains the OS and language frameworks](overview-patch-os-runtime.md) for you. Spend time writing great apps and let Azure worry about the platform.
 * **Containerization and Docker** - Dockerize your app and host a custom Windows or Linux container in App Service. Run sidecar containers of your choice. Migrate your Docker skills directly to App Service.
-* **DevOps optimization** - Set up [continuous integration and deployment](deploy-continuous-deployment.md) with Azure DevOps, GitHub, BitBucket, Docker Hub, or Azure Container Registry. Promote updates through [test and staging environments](deploy-staging-slots.md). Manage your apps in App Service by using [Azure PowerShell](/powershell/azure/) or the [cross-platform command-line interface (CLI)](/cli/azure/install-azure-cli).
+* **DevOps optimization** - Set up [continuous integration and deployment](deploy-continuous-deployment.md) with Azure DevOps, GitHub, Bitbucket, Docker Hub, or Azure Container Registry. Promote updates through [test and staging environments](deploy-staging-slots.md). Manage your apps in App Service by using [Azure PowerShell](/powershell/azure/) or the [cross-platform command-line interface (CLI)](/cli/azure/install-azure-cli).
 * **Global scale with high availability** - Scale [up](manage-scale-up.md) or [out](/azure/azure-monitor/autoscale/autoscale-get-started) manually or automatically. Host your apps anywhere in the global Microsoft datacenter infrastructure, and the App Service [SLA](https://azure.microsoft.com/support/legal/sla/app-service/) promises high availability.
 * **Connections to SaaS platforms and on-premises data** - Choose from [many hundreds of  connectors](/connectors/connector-reference/connector-reference-logicapps-connectors) for enterprise systems (such as SAP), SaaS services (such as Salesforce), and internet services (such as Facebook). Access on-premises data using [Hybrid Connections](app-service-hybrid-connections.md) and [Azure Virtual Network](./overview-vnet-integration.md).
 * **Security and compliance** - App Service is [ISO, SOC, and PCI compliant](https://www.microsoft.com/trust-center). Create [IP address restrictions](app-service-ip-restrictions.md) and [managed service identities](overview-managed-identity.md). [Protect against subdomain takeovers](reference-dangling-subdomain-prevention.md).
diff --git a/articles/azure-sql-edge/onnx-overview.md b/articles/azure-sql-edge/onnx-overview.md
@@ -33,7 +33,7 @@ To obtain a model in the ONNX format:
 
      **Supported frameworks**
    * [PyTorch](http://pytorch.org/docs/master/onnx.html)
-   * [Tensorflow](https://github.com/onnx/tensorflow-onnx)
+   * [TensorFlow](https://github.com/onnx/tensorflow-onnx)
    * [Keras](https://github.com/onnx/keras-onnx)
    * [Scikit-learn](https://github.com/onnx/sklearn-onnx)
    * [CoreML](https://github.com/onnx/onnxmltools)
diff --git a/articles/data-factory/airflow-sync-github-repository.md b/articles/data-factory/airflow-sync-github-repository.md
@@ -43,7 +43,7 @@ To sync your GitHub repository by using the Workflow Orchestration Manager UI:
    - **GitHub**
    - **ADO**
    - **GitLab**
-   - **BitBucket**
+   - **Bitbucket**
 
    :::image type="content" source="media/airflow-git-sync-repository/git-service-type.png" alt-text="Screenshot that shows the Git service type selection dropdown in the  environment setup dialog that appears during creation of an Workflow Orchestration Manager integration runtime.":::
 
@@ -57,7 +57,7 @@ To sync your GitHub repository by using the Workflow Orchestration Manager UI:
      - GitHub personal access token
      - ADO personal access token
      - GitLab personal access token
-     - BitBucket personal access token
+     - Bitbucket personal access token
 
      :::image type="content" source="media/airflow-git-sync-repository/git-pat-credentials.png" alt-text="Screenshot that shows the Git PAT credential options in the Airflow environment setup dialog that appears during creation of an AWorkflow Orchestration Manager integration runtime.":::
    - **SPN** ([service principal name](https://devblogs.microsoft.com/devops/introducing-service-principal-and-managed-identity-support-on-azure-devops/)): Only ADO supports this credential type.
@@ -134,7 +134,7 @@ To sync your GitHub repository by using the Rest API:
 
   |Name  |Type  |Description  |
   |---------|---------|---------|
-  |gitServiceType | string | The Git service where your desired repository is located. Values are GitHub, ADO, GitLab, or BitBucket. |
+  |gitServiceType | string | The Git service where your desired repository is located. Values are GitHub, ADO, GitLab, or Bitbucket. |
   |gitCredentialType | string | Type of Git credential. Values are PAT (for personal access token), SPN (supported only by ADO), and None. |
   |repo | string | Repository link. |
   |branch | string | Branch to use in the repository. |
diff --git a/articles/data-factory/rest-apis-for-airflow-integrated-runtime.md b/articles/data-factory/rest-apis-for-airflow-integrated-runtime.md
@@ -78,7 +78,7 @@ This article documents the REST APIs for the Azure Data Factory Workflow Orchest
 
   |Name  |Type  |Description  |
   |---------|---------|---------|
-  |gitServiceType | string | The Git service where your desired repository is located. Values are GitHub, ADO, GitLab, or BitBucket. |
+  |gitServiceType | string | The Git service where your desired repository is located. Values are GitHub, ADO, GitLab, or Bitbucket. |
   |gitCredentialType | string | Type of Git credential. Values are PAT (for personal access token) and None. |
   |repo | string | Repository link. |
   |branch | string | Branch to use in the repository. |
diff --git a/articles/iot-dps/tutorial-custom-hsm-enrollment-group-x509.md b/articles/iot-dps/tutorial-custom-hsm-enrollment-group-x509.md
@@ -225,7 +225,7 @@ For more information about certificate chains, see [X.509 certificate attestatio
 
 ### Set up the X.509 OpenSSL environment
 
-In this section, you create the Openssl configuration files, directory structure, and other files used by the Openssl commands.
+In this section, you create the OpenSSL configuration files, directory structure, and other files used by the OpenSSL commands.
 
 1. Open a Git Bash command prompt and navigate to a folder where you want to generate the X.509 certificates and keys for this tutorial.
 
diff --git a/articles/iot-edge/tutorial-deploy-custom-vision.md b/articles/iot-edge/tutorial-deploy-custom-vision.md
@@ -77,7 +77,7 @@ Once your image classifier is built and trained, you can export it as a Docker c
    | Project Types | **Classification** |
    | Classification Types | **Multiclass (single tag per image)** |
    | Domains | **General (compact)** |
-   | Export Capabilities | **Basic platforms (Tensorflow, CoreML, ONNX, ...)** |
+   | Export Capabilities | **Basic platforms (TensorFlow, CoreML, ONNX, ...)** |
 
 5. Select **Create project**.
 
diff --git a/articles/spring-apps/enterprise/how-to-use-accelerator.md b/articles/spring-apps/enterprise/how-to-use-accelerator.md
@@ -202,7 +202,7 @@ az spring application-accelerator predefined-accelerator enable \
 
 ### Manage your own accelerators
 
-In addition to using the predefined accelerators, you can create your own accelerators. You can use any Git repository in Azure DevOps, GitHub, GitLab, or BitBucket.
+In addition to using the predefined accelerators, you can create your own accelerators. You can use any Git repository in Azure DevOps, GitHub, GitLab, or Bitbucket.
 
 Use the following steps to create and maintain your own accelerators:
 
diff --git a/articles/synapse-analytics/machine-learning/concept-deep-learning.md b/articles/synapse-analytics/machine-learning/concept-deep-learning.md
@@ -34,11 +34,11 @@ To simplify the process for creating and managing pools, Azure Synapse takes car
 
 Azure Synapse Analytics provides built-in support for deep learning infrastructure. The Azure Synapse Analytics runtimes for Apache Spark 3 include support for the most common deep learning libraries like TensorFlow and PyTorch. The Azure Synapse runtime also includes supporting libraries like Petastorm and Horovod which are commonly used for distributed training.
 
-### Tensorflow
+### TensorFlow
 
 TensorFlow is an open source machine learning framework for all developers. It is used for implementing machine learning and deep learning applications.
 
-For more information about Tensorflow, you can visit the [Tensorflow API documentation](https://www.tensorflow.org/api_docs/python/tf).
+For more information about TensorFlow, you can visit the [TensorFlow API documentation](https://www.tensorflow.org/api_docs/python/tf).
 
 ### PyTorch
 
@@ -52,13 +52,13 @@ Horovod is a distributed deep learning training framework for TensorFlow, Keras,
 
 To learn more about how to run distributed training jobs in Azure Synapse Analytics, you can visit the following tutorials:
     - [Tutorial: Distributed training with Horovod and PyTorch](./tutorial-horovod-pytorch.md)
-    - [Tutorial: Distributed training with Horovod and Tensorflow](./tutorial-horovod-tensorflow.md)
+    - [Tutorial: Distributed training with Horovod and TensorFlow](./tutorial-horovod-tensorflow.md)
 
 For more information about Horovod, you can visit the [Horovod documentation](https://horovod.readthedocs.io/en/stable/),
 
 ### Petastorm
 
-Petastorm is an open source data access library which enables single-node or distributed training of deep learning models. This library enables training directly from datasets in Apache Parquet format and datasets that have already been loaded as an Apache Spark DataFrame. Petastorm supports popular training frameworks such as Tensorflow and PyTorch.
+Petastorm is an open source data access library which enables single-node or distributed training of deep learning models. This library enables training directly from datasets in Apache Parquet format and datasets that have already been loaded as an Apache Spark DataFrame. Petastorm supports popular training frameworks such as TensorFlow and PyTorch.
 
 For more information about Petastorm, you can visit the [Petastorm GitHub page](https://github.com/uber/petastorm) or the [Petastorm API documentation](https://petastorm.readthedocs.io/en/latest/).
 
diff --git a/articles/synapse-analytics/machine-learning/tutorial-horovod-pytorch.md b/articles/synapse-analytics/machine-learning/tutorial-horovod-pytorch.md
@@ -30,7 +30,7 @@ Within Azure Synapse Analytics, users can quickly get started with Horovod using
 
 ## Configure the Apache Spark session
 
-At the start of the session, we need to configure a few Apache Spark settings. In most cases, we only need to set the numExecutors and spark.rapids.memory.gpu.reserve. For large models, users may also need to configure the  ```spark.kryoserializer.buffer.max``` setting. For Tensorflow models, users need to set the ```spark.executorEnv.TF_FORCE_GPU_ALLOW_GROWTH``` to be true.
+At the start of the session, we need to configure a few Apache Spark settings. In most cases, we only need to set the numExecutors and spark.rapids.memory.gpu.reserve. For large models, users may also need to configure the  ```spark.kryoserializer.buffer.max``` setting. For TensorFlow models, users need to set the ```spark.executorEnv.TF_FORCE_GPU_ALLOW_GROWTH``` to be true.
 
 In the example, you can see how the Spark configurations can be passed with the ```%%configure``` command. The detailed meaning of each parameter is explained in the [Apache Spark configuration documentation](https://spark.apache.org/docs/latest/configuration.html). The values provided are the suggested, best practice values for Azure Synapse GPU-large pools.  
 
diff --git a/articles/synapse-analytics/machine-learning/tutorial-load-data-petastorm.md b/articles/synapse-analytics/machine-learning/tutorial-load-data-petastorm.md
@@ -11,7 +11,7 @@ ms.author: midesa
 
 # Load data with Petastorm (deprecated)
 
-Petastorm is an open source data access library, which enables single-node or distributed training of deep learning models. This library enables training directly from datasets in Apache Parquet format and datasets that are loaded as an Apache Spark DataFrame. Petastorm supports popular training frameworks such as Tensorflow and PyTorch.
+Petastorm is an open source data access library, which enables single-node or distributed training of deep learning models. This library enables training directly from datasets in Apache Parquet format and datasets that are loaded as an Apache Spark DataFrame. Petastorm supports popular training frameworks such as TensorFlow and PyTorch.
 
 For more information about Petastorm, you can visit the [Petastorm GitHub page](https://github.com/uber/petastorm) or the [Petastorm API documentation](https://petastorm.readthedocs.io/en/latest).
 
@@ -103,7 +103,7 @@ generate_petastorm_dataset(output_url)
 
 ### Read dataset from a primary storage account
 
-The ```petastorm.reader.Reader``` class is the main entry point for user code that accesses the data from an ML framework such as Tensorflow or Pytorch. You can read a dataset using the ```petastorm.reader.Reader``` class and the ```petastorm.make_reader``` factory method.
+The ```petastorm.reader.Reader``` class is the main entry point for user code that accesses the data from an ML framework such as TensorFlow or Pytorch. You can read a dataset using the ```petastorm.reader.Reader``` class and the ```petastorm.make_reader``` factory method.
 
 In the example, you can see how you can pass an ```abfs``` URL protocol.
 
diff --git a/articles/synapse-analytics/spark/apache-spark-gpu-concept.md b/articles/synapse-analytics/spark/apache-spark-gpu-concept.md
@@ -63,10 +63,10 @@ To learn more about how you can use the NVIDIA RAPIDS Accelerator with your GPU-
 
 ## Train deep learning models
 
-Deep learning models are often data and computation intensive. Because of this, organizations often accelerate their training process with GPU-enabled clusters. In Azure Synapse Analytics, organizations can build models using frameworks like Tensorflow and PyTorch. Then, users can scale up their deep learning models with Horovod and  Petastorm.
+Deep learning models are often data and computation intensive. Because of this, organizations often accelerate their training process with GPU-enabled clusters. In Azure Synapse Analytics, organizations can build models using frameworks like TensorFlow and PyTorch. Then, users can scale up their deep learning models with Horovod and  Petastorm.
 
 To learn more about how you can train distributed deep learning models, visit the following guides:
-    - [Tutorial: Distributed training with Horovod and Tensorflow](../machine-learning/tutorial-horovod-tensorflow.md)
+    - [Tutorial: Distributed training with Horovod and TensorFlow](../machine-learning/tutorial-horovod-tensorflow.md)
     - [Tutorial: Distributed training with Horovod and PyTorch](../machine-learning/tutorial-horovod-pytorch.md)
 
 ## Improve machine learning scoring workloads
diff --git a/articles/synapse-analytics/spark/apache-spark-machine-learning-training.md b/articles/synapse-analytics/spark/apache-spark-machine-learning-training.md
diff --git a/articles/synapse-analytics/spark/apache-spark-manage-session-packages.md b/articles/synapse-analytics/spark/apache-spark-manage-session-packages.md
diff --git a/includes/api-management-developer-portal-editor.md b/includes/api-management-developer-portal-editor.md
diff --git a/includes/api-management-developer-portal-wordpress.md b/includes/api-management-developer-portal-wordpress.md
