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

Author: KumudD

articles/app-service/operating-system-functionality.md

@@ -61,7 +61,7 @@ It is important to monitor your disk utilization as your application grows. If t
 
 - The app may throw an error indicating not enough space on the disk.
 - You may see disk errors when browsing to the Kudu console.
-- Deployment from VSTS or Visual Studio may fail with `ERROR_NOT_ENOUGH_DISK_SPACE: Web deployment task failed. (Web Deploy detected insufficient space on disk)`.
+- Deployment from Azure DevOps or Visual Studio may fail with `ERROR_NOT_ENOUGH_DISK_SPACE: Web deployment task failed. (Web Deploy detected insufficient space on disk)`.
 - Your app may suffer slow performance.
 
 <a id="NetworkDrives"></a>

articles/azure-cache-for-redis/cache-faq.md

@@ -247,7 +247,7 @@ You can use any of the commands listed at [Redis commands](https://redis.io/comm
 * `redis-cli -h <Azure Cache for Redis name>.redis.cache.windows.net -a <key>`
 
 > [!NOTE]
-> The Redis command-line tools do not work with the SSL port, but you can use a utility such as `stunnel` to securely connect the tools to the SSL port by following the directions in the [Announcing ASP.NET Session State Provider for Redis Preview Release](https://blogs.msdn.com/b/webdev/archive/2014/05/12/announcing-asp-net-session-state-provider-for-redis-preview-release.aspx) blog post.
+> The Redis command-line tools do not work with the SSL port, but you can use a utility such as `stunnel` to securely connect the tools to the SSL port by following the directions in the [How to use the Redis command-line tool with Azure Cache for Redis](https://docs.microsoft.com/en-us/azure/azure-cache-for-redis/cache-how-to-redis-cli-tool) article.
 >
 >
 

articles/azure-maps/how-to-request-real-time-data.md

@@ -110,9 +110,9 @@ Let's use "522" as our metro ID, which is the metro ID for "Seattle–Tacoma–B
     }
 
 
-## Real-time availability and vacancy information for bike docking station
+## Real-time data for bike docking station
 
-The [Get Transit Dock Info API](https://aka.ms/AzureMapsMobilityTransitDock) of the Azure Maps Mobility Service, allows to request static and real-time information for a given bike or scooter docking station. We will make a request to get real-time data for a docking station for bikes. 
+The [Get Transit Dock Info API](https://aka.ms/AzureMapsMobilityTransitDock) of the Azure Maps Mobility Service, allows to request static and real-time information such as availability and vacancy information for a given bike or scooter docking station. We will make a request to get real-time data for a docking station for bikes.
 
 In order to make a request to the Get Transit Dock Info API, you will need the **dockId** for that station. You can get the dock ID by making a search request to the [Get Nearby Transit API](https://aka.ms/AzureMapsMobilityNearbyTransit) and setting the **objectType** parameter to "bikeDock". Follow the steps below to get real-time data of a docking station for bikes.
 

articles/azure-monitor/app/correlation.md

@@ -9,7 +9,7 @@ ms.service: application-insights
 ms.workload: TBD
 ms.tgt_pltfrm: ibiza
 ms.topic: conceptual
-ms.date: 02/14/2019
+ms.date: 06/07/2019
 ms.reviewer: sergkanz
 ms.author: lagayhar
 ---
@@ -29,7 +29,7 @@ Every outgoing operation, such as an HTTP call to another component, is represen
 
 You can build a view of the distributed logical operation by using `operation_Id`, `operation_parentId`, and `request.id` with `dependency.id`. These fields also define the causality order of telemetry calls.
 
-In a microservices environment, traces from components can go to different storage items. Every component can have its own instrumentation key in Application Insights. To get telemetry for the logical operation, you must query data from every storage item. When the number of storage items is huge, you'll need a hint about where to look next. The Application Insights data model defines two fields to solve this problem: `request.source` and `dependency.target`. The first field identifies the component that initiated the dependency request, and the second identifies which component returned the response of the dependency call.
+In a microservices environment, traces from components can go to different storage items. Every component can have its own instrumentation key in Application Insights. To get telemetry for the logical operation, the Application Insights UX queries data from every storage item. When the number of storage items is huge, you'll need a hint about where to look next. The Application Insights data model defines two fields to solve this problem: `request.source` and `dependency.target`. The first field identifies the component that initiated the dependency request, and the second identifies which component returned the response of the dependency call.
 
 ## Example
 

articles/azure-monitor/platform/activity-logs-overview.md

@@ -24,7 +24,7 @@ There is a single Activity Log for each Azure subscription. It provides data abo
 
 
 > [!NOTE]
-> The Azure Activity Log is primarily for activities that occur in Azure Resource Manager. It does not track ugresources using the Classic/RDFE model. Some Classic resource types have a proxy resource provider in Azure Resource Manager (for example, Microsoft.ClassicCompute). If you interact with a Classic resource type through Azure Resource Manager using these proxy resource providers, the operations appear in the Activity Log. If you interact with a Classic resource type outside of the Azure Resource Manager proxies, your actions are only recorded in the Operation Log. The Operation Log can be browsed in a separate section of the portal.
+> The Azure Activity Log is primarily for activities that occur in Azure Resource Manager. It does not track resources using the Classic/RDFE model. Some Classic resource types have a proxy resource provider in Azure Resource Manager (for example, Microsoft.ClassicCompute). If you interact with a Classic resource type through Azure Resource Manager using these proxy resource providers, the operations appear in the Activity Log. If you interact with a Classic resource type outside of the Azure Resource Manager proxies, your actions are only recorded in the Operation Log. The Operation Log can be browsed in a separate section of the portal.
 
 ## Activity Log retention
 Activity Log events are stored for 90 days. To store this data for longer periods, [collect it in Azure Monitor](activity-log-collect.md) or [export it to storage or Event Hubs](activity-log-export.md).

articles/cognitive-services/Anomaly-Detector/tutorials/anomaly-detection-streaming-databricks.md

@@ -14,7 +14,7 @@ ms.author: aahi
 
 # Tutorial: Anomaly detection on streaming data using Azure Databricks
 
-[Azure Databricks](https://azure.microsoft.com/en-us/services/databricks/) is a fast, easy, and collaborative Apache Spark–based analytics service. The Anomaly Detector API, part of Azure Cognitive Services, provides a way of monitoring your time series data. Use this tutorial to run anomaly detection on a stream of data in near real-time using Azure Databricks. You'll ingest twitter data using Azure Event Hubs, and import them into Azure Databricks using the Spark Event Hubs connector. Afterwards, you'll use the API to detect anomalies on the streamed data. 
+[Azure Databricks](https://azure.microsoft.com/services/databricks/) is a fast, easy, and collaborative Apache Spark–based analytics service. The Anomaly Detector API, part of Azure Cognitive Services, provides a way of monitoring your time series data. Use this tutorial to run anomaly detection on a stream of data in near real-time using Azure Databricks. You'll ingest twitter data using Azure Event Hubs, and import them into Azure Databricks using the Spark Event Hubs connector. Afterwards, you'll use the API to detect anomalies on the streamed data. 
 
 The following illustration shows the application flow:
 

articles/cognitive-services/Face/ReleaseNotes.md

@@ -9,14 +9,18 @@ manager: nitinme
 ms.service: cognitive-services
 ms.subservice: face-api
 ms.topic: conceptual
-ms.date: 04/28/2019
+ms.date: 06/06/2019
 ms.author: yluiu
 ---
 
 # Face API Release Notes
 
 This article pertains to Face API Service version 1.0.
 
+### Release changes in June 2019
+
+* Added a new face detection model with improved accuracy on small, side-view, occluded and blurry faces. Use it through [Face - Detect](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236), [FaceList - Add Face](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395250), [LargeFaceList - Add Face](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/5a158c10d2de3616c086f2d3), [PersonGroup Person - Add Face](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f3039523b) and [LargePersonGroup Person - Add Face](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/599adf2a3a7b9412a4d53f42) by specifying the new face detection model name `detection_02` in `detectionModel` parameter. More details in [How to specify a detection model](Face-API-How-to-Topics/specify-detection-model.md).
+
 ### Release changes in April 2019
 
 * Improved overall accuracy of the `age` and `headPose` attributes. The `headPose` attribute is also updated with the `pitch` value enabled now. Use these attributes by specifying them in the `returnFaceAttributes` parameter of [Face - Detect](https://westus.dev.cognitive.microsoft.com/docs/services/563879b61984550e40cbbe8d/operations/563879b61984550f30395236) `returnFaceAttributes` parameter. 

articles/cognitive-services/Speech-Service/ship-application.md

@@ -25,8 +25,8 @@ The Cognitive Services Speech SDK is tested on Windows 10 and on Windows Server
 
 The Cognitive Services Speech SDK requires the [Microsoft Visual C++ Redistributable for Visual Studio 2019](https://support.microsoft.com/help/2977003/the-latest-supported-visual-c-downloads) on the system. You can download installers for the latest version of the `Microsoft Visual C++ Redistributable for Visual Studio 2019` here:
 
-- [Win32](https://aka.ms/vs/15/release/vc_redist.x86.exe)
-- [x64](https://aka.ms/vs/15/release/vc_redist.x64.exe)
+- [Win32](https://aka.ms/vs/16/release/vc_redist.x86.exe)
+- [x64](https://aka.ms/vs/16/release/vc_redist.x64.exe)
 
 If your application uses managed code, the `.NET Framework 4.6.1` or later is required on the target machine.
 

articles/digital-twins/how-to-diagnose-user-defined-functions.md

@@ -29,7 +29,7 @@ A variety of logging, analytics, and diagnostic tools are provided to that end.
 Azure Digital Twins supports robust logging, monitoring, and analytics. Solutions developers can use Azure Monitor logs, diagnostic logs, activity logs, and other services to support the complex monitoring needs of an IoT app. Logging options can be combined to query or display records across several services and to provide granular logging coverage for many services.
 
 * For logging configuration specific to Azure Digital Twins, read [How to configure monitoring and logging](./how-to-configure-monitoring.md).
-* Consult the the [Azure Monitor](../azure-monitor/overview.md) overview to learn about powerful log settings enabled through Azure Monitor.
+* Consult the [Azure Monitor](../azure-monitor/overview.md) overview to learn about powerful log settings enabled through Azure Monitor.
 * Review the article [Collect and consume log data from your Azure resources](../azure-monitor/platform/diagnostic-logs-overview.md) for configuring diagnostic log settings in Azure Digital Twins through the Azure Portal, Azure CLI, or PowerShell.
 
 Once configured, you'll be able to select all log categories, metrics, and use powerful Azure Monitor log analytics workspaces to support your debugging efforts.

articles/frontdoor/waf-front-door-configure-ip-restriction.md

@@ -58,7 +58,7 @@ az network waf-policy custom-rule create \
   --name IPAllowListRule \
   --priority 1 \
   --rule-type MatchRule \
-  --match-condition RemoteAddr IPMatch "<ip-address-range-1>","<ip-address-range-2>" \
+  --match-condition RemoteAddr IPMatch ("<ip-address-range-1>","<ip-address-range-2>") \
   --action Allow \
   --resource-group <resource-group-name> \
   --policy-name IPAllowPolicyExampleCLI
@@ -134,7 +134,7 @@ In the following example, replace *ip-address-range-1*, *ip-address-range-2* wit
 $IPMatchCondition = New-AzFrontDoorWafMatchConditionObject `
 -MatchVariable  RemoteAddr `
 -OperatorProperty IPMatch `
--MatchValue ["ip-address-range-1", "ip-address-range-2"]
+-MatchValue "ip-address-range-1", "ip-address-range-2"
 ```
 Create an IP *match all condition* rule by using the following command:
 ```powershell