Merge branch 'master' of https://github.com/MicrosoftDocs/azure-docs-pr into march31updates

Author: KumudD

articles/azure-cache-for-redis/cache-best-practices.md

@@ -63,7 +63,7 @@ Unfortunately, there's no easy answer.  Each application needs to decide what op
 If you would like to test how your code works under error conditions, consider using the [Reboot feature](cache-administration.md#reboot). Rebooting allows you to see how connection blips affect your application.
 
 ## Performance testing
- * **Start by using `redis-benchmark.exe`** to get a feel for possible throughput/latency before writing your own perf tests.  Redis-benchmark documentation can be [found here](https://redis.io/topics/benchmarks).  Note that redis-benchmark doesn't support SSL, so you'll have to [enable the Non-SSL port through the Portal](cache-configure.md#access-ports) before you run the test.  [A windows compatible version of redis-benchmark.exe can be found here](https://github.com/MSOpenTech/redis/releases)
+ * **Start by using `redis-benchmark.exe`** to get a feel for possible throughput/latency before writing your own perf tests.  Redis-benchmark documentation can be [found here](https://redis.io/topics/benchmarks).  Note that redis-benchmark doesn't support TLS, so you'll have to [enable the Non-TLS port through the Portal](cache-configure.md#access-ports) before you run the test.  [A windows compatible version of redis-benchmark.exe can be found here](https://github.com/MSOpenTech/redis/releases)
  * The client VM used for testing should be **in the same region** as your Redis cache instance.
  * **We recommend using Dv2 VM Series** for your client as they have better hardware and will give the best results.
  * Make sure the client VM you use has **at least as much compute and bandwidth* as the cache being tested. 

articles/cognitive-services/QnAMaker/troubleshooting.md

@@ -26,7 +26,7 @@ Learn more about [pricing tiers](Concepts/azure-resources.md).
 <summary><b>How to get the QnAMaker service endpoint</b></summary>
 
 **Answer**:
-QnAMaker service endpoint is useful for debugging purposes when you contact QnAMaker Support or UserVoice. The endpoint is a URL in this form: https://your-resource-name.azurewebsites.net.
+QnAMaker service endpoint is useful for debugging purposes when you contact QnAMaker Support or UserVoice. The endpoint is a URL in this form: `https://your-resource-name.azurewebsites.net`.
 
 1. Go to your QnAMaker service (resource group) in the [Azure portal](https://portal.azure.com)
 

articles/iot-hub/iot-hub-devguide-messages-read-builtin.md

@@ -19,7 +19,7 @@ By default, messages are routed to the built-in service-facing endpoint (**messa
 | **Partition count** | Set this property at creation to define the number of [partitions](../event-hubs/event-hubs-features.md#partitions) for device-to-cloud event ingestion. |
 | **Retention time**  | This property specifies how long in days messages are retained by IoT Hub. The default is one day, but it can be increased to seven days. |
 
-IoT Hub allows data retention in the built-in Event Hubs for a maximum of 7 days. You can set the retention time during creation of your IoT Hub. Data retention time in IoT Hub depends on your IoT hub tier and unit type. In terms of size, the built-in Event Hubs can retain messages of the maximum message size up to at least 24 hours of quota. For example, for 1 S1 unit IoT Hub provides enough storage to retain at least 400K messages of 4k size each. If your devices are sending smaller messages, they may be retained for longer (up to 7 days) depending on how much storage is consumed. We guarantee retaining the data for the specified retention time as a minimum.
+IoT Hub allows data retention in the built-in Event Hubs for a maximum of 7 days. You can set the retention time during creation of your IoT Hub. Data retention time in IoT Hub depends on your IoT hub tier and unit type. In terms of size, the built-in Event Hubs can retain messages of the maximum message size up to at least 24 hours of quota. For example, for 1 S1 unit IoT Hub provides enough storage to retain at least 400K messages of 4k size each. If your devices are sending smaller messages, they may be retained for longer (up to 7 days) depending on how much storage is consumed. We guarantee retaining the data for the specified retention time as a minimum. Messages will expire and will not be accessible after the retention time has passed. 
 
 IoT Hub also enables you to manage consumer groups on the built-in device-to-cloud receive endpoint. You can have up to 20 consumer groups for each IoT Hub.
 

articles/machine-learning/how-to-deploy-and-where.md

@@ -533,9 +533,9 @@ The classes for local, Azure Container Instances, and AKS web services can be im
 from azureml.core.webservice import AciWebservice, AksWebservice, LocalWebservice
 ```
 
-### Securing deployments with SSL
+### Securing deployments with TLS
 
-For more information on how to secure a web service deployment, see [Use SSL to secure a web service](how-to-secure-web-service.md#enable).
+For more information on how to secure a web service deployment, see [Enable TLS and deploy](how-to-secure-web-service.md#enable).
 
 ### <a id="local"></a> Local deployment
 
@@ -1169,7 +1169,7 @@ def run(request):
 
 * [How to deploy a model using a custom Docker image](how-to-deploy-custom-docker-image.md)
 * [Deployment troubleshooting](how-to-troubleshoot-deployment.md)
-* [Secure Azure Machine Learning web services with SSL](how-to-secure-web-service.md)
+* [Use TLS to secure a web service through Azure Machine Learning](how-to-secure-web-service.md)
 * [Consume an Azure Machine Learning model deployed as a web service](how-to-consume-web-service.md)
 * [Monitor your Azure Machine Learning models with Application Insights](how-to-enable-app-insights.md)
 * [Collect data for models in production](how-to-enable-data-collection.md)

articles/machine-learning/how-to-deploy-azure-container-instance.md

@@ -89,7 +89,7 @@ See [deploy your models with VS Code](tutorial-train-deploy-image-classification
 
 * [How to deploy a model using a custom Docker image](how-to-deploy-custom-docker-image.md)
 * [Deployment troubleshooting](how-to-troubleshoot-deployment.md)
-* [Secure Azure Machine Learning web services with SSL](how-to-secure-web-service.md)
+* [Use TLS to secure a web service through Azure Machine Learning](how-to-secure-web-service.md)
 * [Consume a ML Model deployed as a web service](how-to-consume-web-service.md)
 * [Monitor your Azure Machine Learning models with Application Insights](how-to-enable-app-insights.md)
 * [Collect data for models in production](how-to-enable-data-collection.md)

articles/machine-learning/how-to-deploy-azure-kubernetes-service.md

@@ -126,7 +126,7 @@ If you set `cluster_purpose = AksCompute.ClusterPurpose.DEV_TEST`, then the clus
 > [!WARNING]
 > Do not create multiple, simultaneous attachments to the same AKS cluster from your workspace. For example, attaching one AKS cluster to a workspace using two different names. Each new attachment will break the previous existing attachment(s).
 >
-> If you want to re-attach an AKS cluster, for example to change SSL or other cluster configuration setting, you must first remove the existing attachment by using [AksCompute.detach()](https://docs.microsoft.com/python/api/azureml-core/azureml.core.compute.akscompute?view=azure-ml-py#detach--).
+> If you want to re-attach an AKS cluster, for example to change TLS or other cluster configuration setting, you must first remove the existing attachment by using [AksCompute.detach()](https://docs.microsoft.com/python/api/azureml-core/azureml.core.compute.akscompute?view=azure-ml-py#detach--).
 
 For more information on creating an AKS cluster using the Azure CLI or portal, see the following articles:
 
@@ -343,7 +343,7 @@ print(token)
 * [Secure experimentation and inference in a virtual network](how-to-enable-virtual-network.md)
 * [How to deploy a model using a custom Docker image](how-to-deploy-custom-docker-image.md)
 * [Deployment troubleshooting](how-to-troubleshoot-deployment.md)
-* [Secure Azure Machine Learning web services with SSL](how-to-secure-web-service.md)
+* [Use TLS to secure a web service through Azure Machine Learning](how-to-secure-web-service.md)
 * [Consume a ML Model deployed as a web service](how-to-consume-web-service.md)
 * [Monitor your Azure Machine Learning models with Application Insights](how-to-enable-app-insights.md)
 * [Collect data for models in production](how-to-enable-data-collection.md)

articles/storage/blobs/TOC.yml

@@ -13,7 +13,7 @@
       href: storage-blobs-introduction.md
   - name: Quickstarts
     items:
-    - name: Manage blobs without code
+    - name: Work with blobs
       items:
       - name: Azure portal
         href: storage-quickstart-blobs-portal.md
@@ -23,8 +23,6 @@
         href: storage-quickstart-blobs-powershell.md
       - name: CLI
         href: storage-quickstart-blobs-cli.md
-    - name: Develop with blobs
-      items:
       - name: .NET
         items:
           - name: .NET (v12 SDK)