Merge pull request #114024 from craigcaseyMSFT/vcraic0505

PMEds28 · web-flow · commit cd6d91c56136 · 2020-05-06T08:28:47.000+01:00
fix broken links from OPS report
diff --git a/articles/cognitive-services/Bing-News-Search/toc.yml b/articles/cognitive-services/Bing-News-Search/toc.yml
@@ -65,7 +65,7 @@
   - name: SDKs
     items:
       - name: .NET
-        href: https://docs.microsoft.com/dotnet/api/overview/azure/cognitiveservices/client/bingnews?view=azure-dotnet
+        href: https://docs.microsoft.com/dotnet/api/overview/azure/cognitiveservices/client/bingnewssearch?view=azure-dotnet
       - name: Java
         href: https://docs.microsoft.com/java/api/overview/azure/cognitiveservices/client/bingnewssearch?view=azure-java-stable
       - name: Python
diff --git a/articles/cognitive-services/Bing-Video-Search/toc.yml b/articles/cognitive-services/Bing-Video-Search/toc.yml
@@ -66,7 +66,7 @@
   - name: SDKs
     items:
     - name: .NET
-      href: https://docs.microsoft.com/dotnet/api/overview/azure/cognitiveservices/client/bingvideo?view=azure-dotnet
+      href: https://docs.microsoft.com/dotnet/api/overview/azure/cognitiveservices/client/bingvideosearch?view=azure-dotnet
     - name: Java
       href: https://docs.microsoft.com/java/api/overview/azure/cognitiveservices/client/bingvideosearch?view=azure-java-stable
     - name: Python 
diff --git a/articles/cognitive-services/QnAMaker/includes/quickstart-sdk-python.md b/articles/cognitive-services/QnAMaker/includes/quickstart-sdk-python.md
@@ -47,7 +47,7 @@ Create a [CognitiveServicesCredentials](https://docs.microsoft.com/python/api/ms
 
 Once the client is created, use the [Knowledge base](https://docs.microsoft.com/python/api/azure-cognitiveservices-knowledge-qnamaker/azure.cognitiveservices.knowledge.qnamaker.authoring.operations.knowledgebase_operations?view=azure-python) to create, manage, and publish your knowledge base.
 
-For immediate operations, a method usually returns a JSON object indicating status. For long-running operations, the response is the operation ID. Call the [client.Operations.getDetails](https://docs.microsoft.com/python/api/azure-cognitiveservices-knowledge-qnamaker/azure.cognitiveservices.knowledge.qnamaker.authoring.models.operationstatetype?view=azure-python) method with the operation ID to determine the [status of the request](https://docs.microsoft.com/python/api/azure-cognitiveservices-knowledge-qnamaker/azure.cognitiveservices.knowledge.qnamaker.models.operationstatetype?view=azure-python).
+For immediate operations, a method usually returns a JSON object indicating status. For long-running operations, the response is the operation ID. Call the [client.Operations.getDetails](https://docs.microsoft.com/python/api/azure-cognitiveservices-knowledge-qnamaker/azure.cognitiveservices.knowledge.qnamaker.authoring.models.operationstatetype?view=azure-python) method with the operation ID to determine the [status of the request](https://docs.microsoft.com/python/api/azure-cognitiveservices-knowledge-qnamaker/azure.cognitiveservices.knowledge.qnamaker.authoring.models.operationstatetype?view=azure-python).
 
 
 ## Code examples
@@ -78,7 +78,7 @@ Create variables for your resource's Azure endpoint and key. If you created the
 
 ## Authenticate the client
 
-Next, create a CognitiveServicesCredentials object with your key, and use it with your endpoint to create a [QnAMakerClient](https://docs.microsoft.com/python/api/azure-cognitiveservices-knowledge-qnamaker/azure.cognitiveservices.knowledge.qnamaker.qnamakerclient?view=azure-python) object.
+Next, create a CognitiveServicesCredentials object with your key, and use it with your endpoint to create a [QnAMakerClient](https://docs.microsoft.com/python/api/azure-cognitiveservices-knowledge-qnamaker/azure.cognitiveservices.knowledge.qnamaker.authoring.qnamakerclient?view=azure-python) object.
 
 
 [!code-python[Authorization to resource key](~/samples-qnamaker-python/documentation-samples/quickstarts/knowledgebase_quickstart/knowledgebase_quickstart.py?name=authorization)]
diff --git a/articles/container-instances/container-instances-quickstart-template.md b/articles/container-instances/container-instances-quickstart-template.md
@@ -98,4 +98,4 @@ In this quickstart, you created an Azure container instance from a public Micros
 For a step-by-step tutorial that guides you through the process of creating a template, see:
 
 > [!div class="nextstepaction"]
-> [Tutorial: Create and deploy your first Azure Resource Manager template](/azure/azure-resource-manager/templates/template-tutorial-create-first-template.md)
+> [Tutorial: Create and deploy your first Azure Resource Manager template](/azure/azure-resource-manager/templates/template-tutorial-create-first-template)
diff --git a/articles/container-instances/container-instances-update.md b/articles/container-instances/container-instances-update.md
@@ -23,7 +23,7 @@ To update an existing container group:
 * Set other properties with the values you provided previously. If you don't set a value for a property, it reverts to its default value.
 
 > [!TIP]
-> A [YAML file](/container-instances-container-groups.md#deployment) helps maintain a container group's deployment configuration, and provides a starting point to deploy an updated group. If you used a different method to create the group, you can export the configuration to YAML by using [az container export][az-container-export], 
+> A [YAML file](container-instances-container-groups.md#deployment) helps maintain a container group's deployment configuration, and provides a starting point to deploy an updated group. If you used a different method to create the group, you can export the configuration to YAML by using [az container export][az-container-export], 
 
 ### Example
 
diff --git a/articles/data-lake-store/TOC.yml b/articles/data-lake-store/TOC.yml
@@ -163,7 +163,7 @@
   - name: Node.js
     href: https://www.npmjs.com/package/azure-arm-datalake-store
   - name: Python (Account Mgmt.)
-    href: https://docs.microsoft.com/python/api/azure.mgmt.datalake.store?view=azure-python
+    href: https://docs.microsoft.com/python/api/azure-mgmt-datalake-store/azure.mgmt.datalake.store?view=azure-python
   - name: Python (Filesystem Mgmt.)
     href: https://azure-datalake-store.readthedocs.io/en/latest
   - name: REST
diff --git a/articles/event-hubs/TOC.yml b/articles/event-hubs/TOC.yml
@@ -250,7 +250,7 @@
     - name: Client library
       items:
       - name: azure-eventhub version 5
-        href: /python/api/overview/azure/eventhub/client
+        href: /python/api/azure-eventhub/?view=azure-python
       - name: azure-eventhub version 1
         href: /python/api/azure-eventhub/?view=azure-python-previous
     - name: Management library
diff --git a/articles/event-hubs/event-hubs-geo-dr.md b/articles/event-hubs/event-hubs-geo-dr.md
@@ -135,7 +135,7 @@ You can enable Availability Zones on new namespaces only, using the Azure portal
 ## Next steps
 
 * The [sample on GitHub](https://github.com/Azure/azure-event-hubs/tree/master/samples/DotNet/Microsoft.Azure.EventHubs/GeoDRClient) walks through a simple workflow that creates a geo-pairing and initiates a failover for a disaster recovery scenario.
-* The [REST API reference](/rest/api/eventhub/disasterrecoveryconfigs) describes APIs for performing the Geo-disaster recovery configuration.
+* The [REST API reference](/rest/api/eventhub/) describes APIs for performing the Geo-disaster recovery configuration.
 
 For more information about Event Hubs, visit the following links:
 
diff --git a/articles/hdinsight/hadoop/apache-hadoop-connect-hive-power-bi.md b/articles/hdinsight/hadoop/apache-hadoop-connect-hive-power-bi.md
@@ -71,4 +71,4 @@ In this article, you learned how to visualize data from HDInsight using Power BI
 
 * [Connect Excel to HDInsight with the Microsoft Hive ODBC Driver](./apache-hadoop-connect-excel-hive-odbc-driver.md).
 * [Connect Excel to Apache Hadoop by using Power Query](apache-hadoop-connect-excel-power-query.md).
-* [Visualize Interactive Query Apache Hive data with Microsoft Power BI using direct query](/interactive-query/apache-hadoop-connect-hive-power-bi-directquery.md)
+* [Visualize Interactive Query Apache Hive data with Microsoft Power BI using direct query](../interactive-query/apache-hadoop-connect-hive-power-bi-directquery.md)
diff --git a/articles/hdinsight/hadoop/hdinsight-tools-for-intellij-with-hortonworks-sandbox.md b/articles/hdinsight/hadoop/hdinsight-tools-for-intellij-with-hortonworks-sandbox.md
@@ -27,7 +27,7 @@ Before you begin this article, you must have the following items:
 
 - [Java Developer Kit (JDK) version 1.8 or later](https://aka.ms/azure-jdks). Azure Toolkit for IntelliJ requires JDK.
 
-- [IntelliJ IDEA community edition](https://www.jetbrains.com/idea/download) with the [Scala](https://plugins.jetbrains.com/idea/plugin/1347-scala) plug-in and the [Azure Toolkit for IntelliJ](https://docs.microsoft.com/java/azure/intellij/azure-toolkit-for-intellij) plug-in. HDInsight Tools for IntelliJ is available as part of Azure Toolkit for IntelliJ. 
+- [IntelliJ IDEA community edition](https://www.jetbrains.com/idea/download) with the [Scala](https://plugins.jetbrains.com/idea/plugin/1347-scala) plug-in and the [Azure Toolkit for IntelliJ](https://docs.microsoft.com/azure/developer/java/toolkit-for-intellij) plug-in. HDInsight Tools for IntelliJ is available as part of Azure Toolkit for IntelliJ.
 
 To install the plug-ins:
 
diff --git a/articles/hdinsight/spark/apache-spark-intellij-tool-debug-remotely-through-ssh.md b/articles/hdinsight/spark/apache-spark-intellij-tool-debug-remotely-through-ssh.md
@@ -12,7 +12,7 @@ ms.date: 12/23/2019
 
 # Debug Apache Spark applications on an HDInsight cluster with Azure Toolkit for IntelliJ through SSH
 
-This article provides step-by-step guidance on how to use HDInsight Tools in [Azure Toolkit for IntelliJ](https://docs.microsoft.com/java/azure/intellij/azure-toolkit-for-intellij?view=azure-java-stable) to debug applications remotely on an HDInsight cluster. To debug your project, you can also view the [Debug HDInsight Spark applications with Azure Toolkit for IntelliJ](https://channel9.msdn.com/Series/AzureDataLake/Debug-HDInsight-Spark-Applications-with-Azure-Toolkit-for-IntelliJ) video.
+This article provides step-by-step guidance on how to use HDInsight Tools in [Azure Toolkit for IntelliJ](https://docs.microsoft.com/azure/developer/java/toolkit-for-intellij) to debug applications remotely on an HDInsight cluster. To debug your project, you can also view the [Debug HDInsight Spark applications with Azure Toolkit for IntelliJ](https://channel9.msdn.com/Series/AzureDataLake/Debug-HDInsight-Spark-Applications-with-Azure-Toolkit-for-IntelliJ) video.
 
 ## Prerequisites
 
diff --git a/articles/hdinsight/spark/apache-spark-intellij-tool-failure-debug.md b/articles/hdinsight/spark/apache-spark-intellij-tool-failure-debug.md
@@ -13,15 +13,15 @@ ms.date: 07/12/2019
 
 # Failure spark job debugging with Azure Toolkit for IntelliJ (preview)
 
-This article provides step-by-step guidance on how to use HDInsight Tools in [Azure Toolkit for IntelliJ](https://docs.microsoft.com/java/azure/intellij/azure-toolkit-for-intellij?view=azure-java-stable) to run **Spark Failure Debug** applications.
+This article provides step-by-step guidance on how to use HDInsight Tools in [Azure Toolkit for IntelliJ](https://docs.microsoft.com/azure/developer/java/toolkit-for-intellij) to run **Spark Failure Debug** applications.
 
 ## Prerequisites
 
 * [Oracle Java Development kit](https://www.oracle.com/technetwork/java/javase/downloads/jdk8-downloads-2133151.html). This tutorial uses Java version 8.0.202.
   
 * IntelliJ IDEA. This article uses [IntelliJ IDEA Community ver. 2019.1.3](https://www.jetbrains.com/idea/download/#section=windows).
   
-* Azure Toolkit for IntelliJ. See [Installing the Azure Toolkit for IntelliJ](https://docs.microsoft.com/java/azure/intellij/azure-toolkit-for-intellij-installation?view=azure-java-stable).
+* Azure Toolkit for IntelliJ. See [Installing the Azure Toolkit for IntelliJ](https://docs.microsoft.com/azure/developer/java/toolkit-for-intellij/installation).
 
 * Connect to your HDInsight cluster. See [Connect to your HDInsight cluster](apache-spark-intellij-tool-plugin.md).
 
diff --git a/articles/iot-central/retail/toc.yml b/articles/iot-central/retail/toc.yml
@@ -130,7 +130,7 @@
       - name: IoT solution accelerators
         href: /azure/iot-accelerators
       - name: IoT Plug and Play
-        href: /azure/iot
+        href: /azure/iot-pnp
       - name: Azure Maps
         href: /azure/azure-maps
       - name: Time Series Insights
diff --git a/articles/key-vault/general/service-to-service-authentication.md b/articles/key-vault/general/service-to-service-authentication.md
@@ -269,7 +269,7 @@ Using Azure CLI, set the default subscription to one that has the account you wa
 
 #### Unauthorized access, access denied, forbidden, or similar error
 
-The principal used doesn't have access to the resource it's trying to access. Grant either your user account or the App Service's MSI "Contributor" access to a resource. Which one depends on whether you're running the sample on your local computer or deployed in Azure to your App Service. Some resources, like key vaults, also have their own [access policies](https://docs.microsoft.com/azure/key-vault/secure-your-key-vault#data-plane-and-access-policies) that you use grant access to principals, such as users, apps, and groups.
+The principal used doesn't have access to the resource it's trying to access. Grant either your user account or the App Service's MSI "Contributor" access to a resource. Which one depends on whether you're running the sample on your local computer or deployed in Azure to your App Service. Some resources, like key vaults, also have their own [access policies](https://docs.microsoft.com/azure/key-vault/general/secure-your-key-vault#data-plane-and-access-policies) that you use grant access to principals, such as users, apps, and groups.
 
 ### Common issues when deployed to Azure App Service
 
diff --git a/articles/load-balancer/upgrade-InternalBasic-To-PublicStandard.md b/articles/load-balancer/upgrade-InternalBasic-To-PublicStandard.md
@@ -10,7 +10,7 @@ ms.author: irenehua
 ---
 
 # Upgrade Azure Internal Load Balancer - Outbound Connection Required
-[Azure Standard Load Balancer](load-balancer-overview.md) offers a rich set of functionality and high availability through zone redundancy. To learn more about Load Balancer SKU, see [comparison table](https://docs.microsoft.com/azure/load-balancer/concepts-limitations#skus). Since Standard Internal Load Balancer does not provide outbound connection, we provide a solution to create a Standard Public Load Balancer instead.
+[Azure Standard Load Balancer](load-balancer-overview.md) offers a rich set of functionality and high availability through zone redundancy. To learn more about Load Balancer SKU, see [comparison table](https://docs.microsoft.com/azure/load-balancer/skus#skus). Since Standard Internal Load Balancer does not provide outbound connection, we provide a solution to create a Standard Public Load Balancer instead.
 
 There are four stages in a upgrade:
 
diff --git a/articles/load-balancer/upgrade-basic-standard.md b/articles/load-balancer/upgrade-basic-standard.md
@@ -10,7 +10,7 @@ ms.author: irenehua
 ---
 
 # Upgrade Azure Public Load Balancer
-[Azure Standard Load Balancer](load-balancer-overview.md) offers a rich set of functionality and high availability through zone redundancy. To learn more about Load Balancer SKU, see [comparison table](https://docs.microsoft.com/azure/load-balancer/concepts-limitations#skus).
+[Azure Standard Load Balancer](load-balancer-overview.md) offers a rich set of functionality and high availability through zone redundancy. To learn more about Load Balancer SKU, see [comparison table](https://docs.microsoft.com/azure/load-balancer/skus#skus).
 
 There are three stages in a upgrade:
 
diff --git a/articles/load-balancer/upgrade-basicInternal-standard.md b/articles/load-balancer/upgrade-basicInternal-standard.md
@@ -10,7 +10,7 @@ ms.author: irenehua
 ---
 
 # Upgrade Azure Internal Load Balancer- No Outbound Connection Required
-[Azure Standard Load Balancer](load-balancer-overview.md) offers a rich set of functionality and high availability through zone redundancy. To learn more about Load Balancer SKU, see [comparison table](https://docs.microsoft.com/azure/load-balancer/concepts-limitations#skus).
+[Azure Standard Load Balancer](load-balancer-overview.md) offers a rich set of functionality and high availability through zone redundancy. To learn more about Load Balancer SKU, see [comparison table](https://docs.microsoft.com/azure/load-balancer/skus#skus).
 
 This article introduces a PowerShell script which creates a Standard Load Balancer with the same configuration as the Basic Load Balancer along with migrating traffic from Basic Load Balancer to Standard Load Balancer.
 
diff --git a/articles/machine-learning/concept-plan-manage-cost.md b/articles/machine-learning/concept-plan-manage-cost.md
@@ -86,7 +86,7 @@ az ml computetarget create amlcompute --name testcluster --vm-size Standard_NC6
 
 Much like other Azure compute resources, AmlCompute comes with an inherent [quota (or limit) configuration](how-to-manage-quotas.md#azure-machine-learning-compute). This quota is by VM family (for example, Dv2 series, NCv3 series) and varies by region for each subscription. Subscriptions start with small defaults to get you going, but use this setting to control the amount of Amlcompute resources available to be spun up in your subscription. 
 
-Also configure [workspace level quota by VM family](/how-to-manage-quotas.md#workspace-level-quota), for each workspace within a subscription. This allows you to have more granular control on the costs that each workspace might potentially incur and restrict certain VM families. 
+Also configure [workspace level quota by VM family](how-to-manage-quotas.md#workspace-level-quota), for each workspace within a subscription. This allows you to have more granular control on the costs that each workspace might potentially incur and restrict certain VM families. 
 
 To set quotas at the workspace level, start in the [Azure portal](https://portal.azure.com).  Select any workspace in your subscription, and select **Usages + quotas** in the left pane. Then select the **Configure quotas** tab to view the quotas. You need privileges at the subscription scope to set this quota, since it's a setting that affects multiple workspaces.
 
diff --git a/articles/machine-learning/data-science-virtual-machine/dsvm-enterprise-overview.md b/articles/machine-learning/data-science-virtual-machine/dsvm-enterprise-overview.md
@@ -39,7 +39,7 @@ This series provides guidance and pointers for each of the preceding topics. It
 * [Role-based access control](https://docs.microsoft.com/azure/role-based-access-control/overview)
 * [Policy setting and enforcement](../../governance/policy/overview.md)
 * [Antimalware](https://docs.microsoft.com/azure/security/fundamentals/antimalware)
-* [Encryption](https://docs.microsoft.com/azure/virtual-machines/windows/disk-encryption-overview.md)
+* [Encryption](https://docs.microsoft.com/azure/virtual-machines/windows/disk-encryption-overview)
 * [Data discovery and governance](https://docs.microsoft.com/azure/data-catalog/)
 
 Finally, the [Azure Architecture Center](https://docs.microsoft.com/azure/architecture/) provides a detailed end-to-end architecture and models for building and managing your cloud-based analytics infrastructure.
diff --git a/articles/machine-learning/how-to-use-automlstep-in-pipelines.md b/articles/machine-learning/how-to-use-automlstep-in-pipelines.md
@@ -286,7 +286,7 @@ The snippet above creates the two `PipelineData` objects for the metrics and mod
 
 ### Configure and create the automated ML pipeline step
 
-Once the inputs and outputs are defined, it's time to create the `AutoMLConfig` and `AutoMLStep`. The details of the configuration will depend on your task, as described in [Configure automated ML experiments in Python](https://docs.microsoft.com/azure/machine-learning/how-to-configure-auto-train]). For the Titanic survival classification task, the following snippet demonstrates a simple configuration.
+Once the inputs and outputs are defined, it's time to create the `AutoMLConfig` and `AutoMLStep`. The details of the configuration will depend on your task, as described in [Configure automated ML experiments in Python](https://docs.microsoft.com/azure/machine-learning/how-to-configure-auto-train). For the Titanic survival classification task, the following snippet demonstrates a simple configuration.
 
 ```python
 from azureml.train.automl import AutoMLConfig
diff --git a/articles/media-services/azure-media-player/azure-media-player-writing-plugins.md b/articles/media-services/azure-media-player/azure-media-player-writing-plugins.md
@@ -82,8 +82,8 @@ For inspiration and more examples on creating a plugin take a look at our [galle
 
 ### Plugin Gallery ###
 
-The [plugin gallery](http//:aka.ms/ampplugins) has several plugins that the community has already contributed for features like time-line markers, zoom, analytics and more. The page provides accesses to the plugins and instructions on how to set it up as well as a demo that shows the plugin in action. If you create a cool plugin that you think should be included in our gallery, feel free to submit it so we can check it out.
+The [plugin gallery](https://aka.ms/ampplugins) has several plugins that the community has already contributed for features like time-line markers, zoom, analytics and more. The page provides accesses to the plugins and instructions on how to set it up as well as a demo that shows the plugin in action. If you create a cool plugin that you think should be included in our gallery, feel free to submit it so we can check it out.
 
 ## Next steps ##
 
-- [Azure Media Player Quickstart](azure-media-player-quickstart.md)
+- [Azure Media Player Quickstart](azure-media-player-quickstart.md)
diff --git a/articles/migrate/tutorial-migrate-hyper-v.md b/articles/migrate/tutorial-migrate-hyper-v.md
@@ -49,7 +49,7 @@ Before you begin this tutorial, you should:
 
 Add the Azure Migrate:Server Migration tool.
 
-- If you followed the second tutorial to [assess VMware VMs](/tutorial-assess-hyper-v.md), you have already set up an Azure Migrate project, and can go ahead and add the tool now.
+- If you followed the second tutorial to [assess VMware VMs](tutorial-assess-hyper-v.md), you have already set up an Azure Migrate project, and can go ahead and add the tool now.
 - If you didn't follow the second tutorial[, follow these instructions](how-to-add-tool-first-time.md) to set up an Azure Migrate project. You add the Azure Migrate:Server Migration tool when you create the project.
 
 If you have a project set up, add the tool as follows:
diff --git a/articles/network-watcher/toc.yml b/articles/network-watcher/toc.yml
@@ -173,7 +173,7 @@
   - name: .NET
     href: /dotnet/api/overview/azure/virtual-network
   - name: Node.js
-    href: /javascript/api/azure-arm-network
+    href: /javascript/api/@azure/arm-network
   - name: REST
     href: /rest/api/network-watcher/
 - name: Resources
diff --git a/articles/private-link/toc.yml b/articles/private-link/toc.yml
