Merge branch 'master' of https://github.com/MicrosoftDocs/azure-docs-pr into work01

Author: Virginia001

.openpublishing.redirection.json

@@ -51144,6 +51144,11 @@
       "source_path": "articles/healthcare-apis/configure-local-rbac.md",
       "redirect_url": "/azure/healthcare-apis/azure-api-for-fhir-additional-settings",
       "redirect_document_id": false
+    },
+    {
+      "source_path": "articles/media-services/previous/media-services-configure-tricaster-live-encoder.md",
+      "redirect_url": "/azure/media-services",
+      "redirect_document_id": false
     }
   ]
 }

articles/active-directory/managed-identities-azure-resources/overview.md

@@ -48,8 +48,12 @@ There are two types of managed identities:
 - A **user-assigned managed identity** is created as a standalone Azure resource. Through a create process, Azure creates an identity in the Azure AD tenant that's trusted by the subscription in use. After the identity is created, the identity can be assigned to one or more Azure service instances. The lifecycle of a user-assigned identity is managed separately from the lifecycle of the Azure service instances to which it's assigned.
 
 Internally, managed identities are service principals of a special type, which are locked to only be used with Azure resources. When the managed identity is deleted, the corresponding service principal is automatically removed.
+Also, when a User-Assigned or System-Assigned Identity is created, the Managed Identity Resource Provider (MSRP) issues a certificate internally to that identity. 
 
-Your code can use a managed identity to request access tokens for services that support Azure AD authentication. Azure takes care of rolling the credentials that are used by the service instance.
+Your code can use a managed identity to request access tokens for services that support Azure AD authentication. Azure takes care of rolling the credentials that are used by the service instance. 
+
+## Credential Rotation
+Credential rotation is controlled by the resource provider that hosts the Azure resource. The default rotation of the credential occurs every 46 days. It's up to the resource provider to call for new credentials, so the resource provider could wait longer than 46 days.
 
 The following diagram shows how managed service identities work with Azure virtual machines (VMs):
 

articles/cognitive-services/text-analytics/includes/quickstarts/java-sdk.md

@@ -13,7 +13,7 @@ ms.reviewer: tasharm, assafi, sumeh
 
 <a name="HOLTop"></a>
 
-[Reference documentation](https://aka.ms/azsdk-java-textanalytics-ref-docs) | [Library source code](https://github.com/Azure/azure-sdk-for-java/blob/master/sdk/textanalytics/azure-ai-textanalytics) | [Package](https://mvnrepository.com/artifact/com.azure/azure-ai-textanalytics/1.0.0-beta.3) | [Samples](https://github.com/Azure/azure-sdk-for-java/tree/master/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics)
+[Reference documentation](https://aka.ms/azsdk-java-textanalytics-ref-docs) | [Library source code](https://github.com/Azure/azure-sdk-for-java/blob/master/sdk/textanalytics/azure-ai-textanalytics) | [Package](https://mvnrepository.com/artifact/com.azure/azure-ai-textanalytics/1.0.0-beta.4) | [Samples](https://github.com/Azure/azure-sdk-for-java/tree/master/sdk/textanalytics/azure-ai-textanalytics/src/samples/java/com/azure/ai/textanalytics)
 
 ## Prerequisites
 
@@ -27,14 +27,14 @@ ms.reviewer: tasharm, assafi, sumeh
 
 ### Add the client library
 
-Create a Maven project in your preferred IDE or development environment. Then add the following dependency to your project's *pom.xml* file. You can find the implementation syntax [for other build tools](https://mvnrepository.com/artifact/com.azure/azure-ai-textanalytics/1.0.0-beta.3) online.
+Create a Maven project in your preferred IDE or development environment. Then add the following dependency to your project's *pom.xml* file. You can find the implementation syntax [for other build tools](https://mvnrepository.com/artifact/com.azure/azure-ai-textanalytics/1.0.0-beta.4) online.
 
 ```xml
 <dependencies>
      <dependency>
         <groupId>com.azure</groupId>
         <artifactId>azure-ai-textanalytics</artifactId>
-        <version>1.0.0-beta.3</version>
+        <version>1.0.0-beta.4</version>
     </dependency>
 </dependencies>
 ```
@@ -45,6 +45,7 @@ Create a Maven project in your preferred IDE or development environment. Then ad
 Create a Java file named `TextAnalyticsSamples.java`. Open the file and add the following `import` statements:
 
 ```java
+import com.azure.core.credential.AzureKeyCredential;
 import com.azure.ai.textanalytics.models.*;
 import com.azure.ai.textanalytics.TextAnalyticsClientBuilder;
 import com.azure.ai.textanalytics.TextAnalyticsClient;
@@ -71,7 +72,6 @@ public static void main(String[] args) {
     sentimentAnalysisExample(client);
     detectLanguageExample(client);
     recognizeEntitiesExample(client);
-    recognizePIIEntitiesExample(client);
     recognizeLinkedEntitiesExample(client);
     extractKeyPhrasesExample(client);
 }
@@ -97,7 +97,7 @@ Create a method to instantiate the `TextAnalyticsClient` object with the key and
 ```java
 static TextAnalyticsClient authenticateClient(String key, String endpoint) {
     return new TextAnalyticsClientBuilder()
-        .apiKey(new TextAnalyticsApiKeyCredential(key))
+        .apiKey(new AzureKeyCredential(key))
         .endpoint(endpoint)
         .buildClient();
 }
@@ -201,34 +201,6 @@ Recognized entity: Seattle, entity category: Location, entity sub-category: GPE,
 Recognized entity: last week, entity category: DateTime, entity sub-category: DateRange, score: 0.8.
 ```
 
-## Using NER to recognize personal information
-
-Create a new function called `recognizePIIEntitiesExample()` that takes the client that you created earlier, and call its `recognizePiiEntities()` function. The returned `RecognizePiiEntitiesResult` object will contain a list of `NamedEntity` if successful, or an `errorMessage` if not. 
-
-```java
-static void recognizePIIEntitiesExample(TextAnalyticsClient client)
-{
-    // The text that need be analyzed.
-    String text = "Insurance policy for SSN on file 123-12-1234 is here by approved.";
-
-    for (PiiEntity entity : client.recognizePiiEntities(text)) {
-        System.out.printf(
-            "Recognized personal identifiable information entity: %s, entity category: %s, %nentity sub-category: %s, score: %s.%n",
-            entity.getText(),
-            entity.getCategory(),
-            entity.getSubCategory(),
-            entity.getConfidenceScore());
-    }
-}
-```
-
-### Output
-
-```console
-Recognized personal identifiable information entity: 123-12-1234, entity category: U.S. Social Security Number (SSN), 
-entity sub-category: null, score: 0.85.
-```
-
 ## Entity linking
 
 Create a new function called `recognizeLinkedEntitiesExample()` that takes the client that you created earlier, and call its `recognizeLinkedEntities()` function. The returned `RecognizeLinkedEntitiesResult` object will contain a list of `LinkedEntity` if successful, or an `errorMessage` if not. Since linked entities are uniquely identified, occurrences of the same entity are grouped under a `LinkedEntity` object as a list of `LinkedEntityMatch` objects.

articles/cognitive-services/text-analytics/includes/quickstarts/nodejs-sdk.md

@@ -56,7 +56,7 @@ npm init
 Install the `@azure/ai-text-analytics` NPM packages:
 
 ```console
-npm install --save @azure/[email protected].3
+npm install --save @azure/[email protected].4
 ```
 
 > [!TIP]
@@ -83,7 +83,7 @@ Create a file named `index.js` and add the following:
 ```javascript
 "use strict";
 
-const { TextAnalyticsClient, TextAnalyticsApiKeyCredential } = require("@azure/ai-text-analytics");
+const { TextAnalyticsClient, AzureKeyCredential } = require("@azure/ai-text-analytics");
 ```
 
 #### [Version 2.1](#tab/version-2)
@@ -128,7 +128,7 @@ The response object is a list containing the analysis information for each docum
 Create a new `TextAnalyticsClient` object with your key and endpoint as parameters.
 
 ```javascript
-const textAnalyticsClient = new TextAnalyticsClient(endpoint,  new TextAnalyticsApiKeyCredential(key));
+const textAnalyticsClient = new TextAnalyticsClient(endpoint,  new AzureKeyCredential(key));
 ```
 
 #### [Version 2.1](#tab/version-2)
@@ -261,7 +261,6 @@ Document ID: 3 , Language: Chinese_Simplified
 
 > [!NOTE]
 > In version `3.0-preview`:
-> * NER includes separate methods for detecting personal information. 
 > * Entity linking is a separate request than NER.
 
 Create an array of strings containing the document you want to analyze. Call the client's `recognizeEntities()` method and get the `RecognizeEntitiesResult` object. Iterate through the list of results, and print the entity name, type, subtype, offset, length, and score.
@@ -315,40 +314,6 @@ Document ID: 1
         Score: 0.31
 ```
 
-## Using NER to detect personal information
-
-Create an array of strings containing the document you want to analyze. Call the client's `recognizePiiEntities()` method and get the `EntitiesBatchResult` object. Iterate through the list of results, and print the entity name, type, subtype, offset, length, and score.
-
-
-```javascript
-async function entityPiiRecognition(client){
-
-    const entityPiiInput = [
-        "Insurance policy for SSN on file 123-12-1234 is here by approved."
-    ];
-    const entityPiiResults = await client.recognizePiiEntities(entityPiiInput);
-
-    entityPiiResults.forEach(document => {
-        console.log(`Document ID: ${document.id}`);
-        document.entities.forEach(entity => {
-            console.log(`\tName: ${entity.text} \tCategory: ${entity.category} \tSubcategory: ${entity.subCategory ? entity.subCategory : "N/A"}`);
-            console.log(`\tScore: ${entity.score}`);
-        });
-    });
-}
-entityPiiRecognition(textAnalyticsClient);
-```
-
-Run your code with `node index.js` in your console window.
-
-### Output
-
-```console
-Document ID: 0
-        Name: 123-12-1234       Category: U.S. Social Security Number (SSN)     Subcategory: N/A
-        Score: 0.85
-```
-
 ## Entity Linking
 
 Create an array of strings containing the document you want to analyze. Call the client's `recognizeLinkedEntities()` method and get the `RecognizeLinkedEntitiesResult` object. Iterate through the list of results, and print the entity name, ID, data source, url, and matches. Every object in `matches` array will contain offset, length, and score for that match.

articles/lab-services/devtest-lab-manage-formulas.md

@@ -13,7 +13,7 @@ ms.workload: na
 ms.tgt_pltfrm: na
 ms.devlang: na
 ms.topic: article
-ms.date: 01/24/2020
+ms.date: 04/17/2020
 ms.author: spelluru
 
 ---
@@ -126,7 +126,7 @@ To delete a formula, follow these steps:
 [!INCLUDE [devtest-lab-try-it-out](../../includes/devtest-lab-try-it-out.md)]
 
 ## Related blog posts
-* [Custom images or formulas?](https://blogs.msdn.microsoft.com/devtestlab/2016/04/06/custom-images-or-formulas/)
+* [Custom images or formulas?](devtest-lab-faq.md#what-is-the-difference-between-a-custom-image-and-a-formula)
 
 ## Next steps
 Once you have created a formula for use when creating a VM, the next step is to [add a VM to your lab](devtest-lab-add-vm.md).

articles/media-services/latest/recommended-on-premises-live-encoders.md

@@ -63,7 +63,6 @@ When streaming via RTMPS, check firewall and/or proxy settings to confirm that o
 - Telestream Wirecast (version 13.0.2 or higher due to the TLS 1.2 requirement)
 - Telestream Wirecast S (only RTMP is supported)
 - Teradek Slice 756
-- TriCaster 8000
 - VMIX
 - xStream
 - [Ffmpeg](https://www.ffmpeg.org)

articles/media-services/previous/TOC.yml

@@ -257,8 +257,6 @@
       items:
       - name: Haivision KB encoder
         href: media-services-configure-kb-live-encoder.md
-      - name: NewTek TriCaster encoder
-        href: media-services-configure-tricaster-live-encoder.md
       - name: Wirecast encoder
         href: media-services-configure-wirecast-live-encoder.md
     - name: Handle long-running operations

articles/media-services/previous/media-services-concepts.md

@@ -107,7 +107,7 @@ For information about supported encoders, see [Encoders](media-services-encode-a
 ## Live Streaming
 In Azure Media Services, a Channel represents a pipeline for processing live streaming content. A Channel receives live input streams in one of two ways:
 
-* An on-premises live encoder sends multi-bitrate RTMP or Smooth Streaming (Fragmented MP4) to the Channel. You can use the following live encoders that output multi-bitrate Smooth Streaming: MediaExcel, Ateme, Imagine Communications, Envivio, Cisco and Elemental. The following live encoders output RTMP: Adobe Flash Live Encoder, [Telestream Wirecast](media-services-configure-wirecast-live-encoder.md), Teradek, Haivision and Tricaster encoders. The ingested streams pass through Channels without any further transcoding and encoding. When requested, Media Services delivers the stream to customers.
+* An on-premises live encoder sends multi-bitrate RTMP or Smooth Streaming (Fragmented MP4) to the Channel. You can use the following live encoders that output multi-bitrate Smooth Streaming: MediaExcel, Ateme, Imagine Communications, Envivio, Cisco and Elemental. The following live encoders output RTMP: Adobe Flash Live Encoder, [Telestream Wirecast](media-services-configure-wirecast-live-encoder.md), Teradek, Haivision encoders. The ingested streams pass through Channels without any further transcoding and encoding. When requested, Media Services delivers the stream to customers.
 * A single bitrate stream (in one of the following formats: RTMP, or Smooth Streaming (Fragmented MP4)) is sent to the Channel that is enabled to perform live encoding with Media Services. The Channel then performs live encoding of the incoming single bitrate stream to a multi-bitrate (adaptive) video stream. When requested, Media Services delivers the stream to customers.
 
 ### Channel

articles/media-services/previous/media-services-configure-kb-live-encoder.md

@@ -19,7 +19,6 @@ ms.author: juliako
 # Use the Haivision KB live encoder to send a single bitrate live stream  
 > [!div class="op_single_selector"]
 > * [Haivision](media-services-configure-kb-live-encoder.md)
-> * [Tricaster](media-services-configure-tricaster-live-encoder.md)
 > * [Wirecast](media-services-configure-wirecast-live-encoder.md)
 
 This topic shows how to configure the [Havision KB live encoder](https://www.haivision.com/products/kb-series/) encoder to send a single bitrate stream to AMS channels that are enabled for live encoding. For more information, see [Working with Channels that are Enabled to Perform Live Encoding with Azure Media Services](media-services-manage-live-encoder-enabled-channels.md).