Merging changes synced from https://github.com/MicrosoftDocs/azure-docs-pr (branch live)

Author: Banani-Rath

.openpublishing.redirection.json

@@ -14968,6 +14968,11 @@
       "redirect_url": "/azure/defender-for-iot/organizations/tutorial-qradar",
       "redirect_document_id": false
     },
+    {
+      "source_path_from_root": "/articles/iot-edge/how-to-devops-starter.md",
+      "redirect_url": "/azure/iot-edge/how-to-continuous-integration-continuous-deployment-classic/",
+      "redirect_document_id": false
+    },
     {
       "source_path_from_root": "/articles/ansible/index.yml",
       "redirect_url": "/azure/developer/ansible/",

articles/active-directory/authentication/how-to-certificate-based-authentication.md

@@ -2,7 +2,6 @@
 title: How to configure Azure AD certificate-based authentication without federation (Preview) - Azure Active Directory
 description: Topic that shows how to configure Azure AD certificate-based authentication in Azure Active Directory
 
-services: active-directory
 ms.service: active-directory
 ms.subservice: authentication
 ms.topic: how-to
@@ -79,7 +78,7 @@ You can validate the crlDistributionPoint value you provide in the above PowerSh
 
 The below table and graphic indicate how to map information from the CA Certificate to the attributes of the downloaded CRL.
 
-| CA Certificate Info | |Downloaded CRL Info|
+| CA Certificate Info |= |Downloaded CRL Info|
 |----|:-:|----|
 |Subject |=|Issuer |
 |Subject Key Identifier |=|Authority Key Identifier (KeyID) |

articles/active-directory/develop/mark-app-as-publisher-verified.md

@@ -11,7 +11,7 @@ ms.workload: identity
 ms.date: 09/27/2021
 ms.author: ryanwi
 ms.custom: aaddev
-ms.reviewer: jesakowi
+ms.reviewer: ardhanap, jesakowi
 ---
 
 # Mark your app as publisher verified

articles/active-directory/develop/publisher-verification-overview.md

@@ -11,7 +11,7 @@ ms.workload: identity
 ms.date: 06/01/2021
 ms.author: ryanwi
 ms.custom: aaddev
-ms.reviewer: jesakowi
+ms.reviewer: ardhanap, jesakowi
 ---
 
 # Publisher verification
@@ -58,7 +58,7 @@ There are a few pre-requisites for publisher verification, some of which will ha
 
     -  In Partner Center this user must have of the following [roles](/partner-center/permissions-overview): MPN Admin, Accounts Admin, or a Global Admin (this is a shared role mastered in Azure AD).
 
--  The user performing verification must sign in using [multifactor authentication](../authentication/howto-mfa-getstarted.md).
+-  The user performing verification must sign in using [multi-factor authentication](../authentication/howto-mfa-getstarted.md).
 
 -  The publisher agrees to the [Microsoft identity platform for developers Terms of Use](/legal/microsoft-identity-platform/terms-of-use).
 

articles/active-directory/develop/troubleshoot-publisher-verification.md

@@ -44,6 +44,7 @@ Resource Health receives signals for your managed cluster to determine the clust
 
 - **Degraded**: When there is a health issue requiring your action, Resource Health reports your cluster as *Degraded*.
 
+Note that the Resource Health for an AKS cluster is different than the Resource Health of its individual resources (*Virtual Machines, ScaleSet Instances, Load Balancer, etc...*).
 For additional details on what each health status indicates, visit [Resource Health overview](../service-health/resource-health-overview.md#health-status).
 
 ### View historical data
@@ -52,4 +53,4 @@ You can also view the past 30 days of historical Resource Health information in
 
 ## Next steps
 
-Run checks on your cluster to further troubleshoot cluster issues by using [AKS Diagnostics](./concepts-diagnostics.md).
+Run checks on your cluster to further troubleshoot cluster issues by using [AKS Diagnostics](./concepts-diagnostics.md).

articles/aks/aks-resource-health.md

@@ -23,7 +23,9 @@ Custom models can be one of two types, [**custom template**](concept-custom-temp
 
 ### Custom template model
 
- The custom template or custom form model relies on a consistent visual template to extract the labeled data. The accuracy of your model is affected by variances in the visual structure of your documents. Structured  forms such as questionnaires or applications are examples of consistent visual templates. Your training set will consist of structured documents where the formatting and layout are static and constant from one document instance to the next. Custom template  models support key-value pairs, selection marks, tables, signature fields and regions and can be trained on documents in any of the [supported languages](language-support.md). For more information, *see* [custom template models](concept-custom-template.md ).
+The custom template or custom form model relies on a consistent visual template to extract the labeled data. The accuracy of your model is affected by variances in the visual structure of your documents. Structured  forms such as questionnaires or applications are examples of consistent visual templates.
+
+Your training set will consist of structured documents where the formatting and layout are static and constant from one document instance to the next. Custom template models support key-value pairs, selection marks, tables, signature fields, and regions. Template models and can be trained on documents in any of the [supported languages](language-support.md). For more information, *see* [custom template models](concept-custom-template.md ).
 
 > [!TIP]
 >
@@ -33,15 +35,15 @@ Custom models can be one of two types, [**custom template**](concept-custom-temp
 
 ### Custom neural model
 
-The custom neural (custom document) model is a deep learning model type that relies on a base model trained on a large collection of documents. This model is then fine-tuned or adapted to your data when you train the model with a labeled dataset. Custom neural models support structured, semi-structured, and unstructured documents to extract fields. Custom neural models currently support English-language documents. When you're choosing between the two model types, start with a neural model if it meets your functional needs. See [neural models](concept-custom-neural.md) to learn more about custom document models.
+The custom neural (custom document) model uses deep learning models and  base model trained on a large collection of documents. This model is then fine-tuned or adapted to your data when you train the model with a labeled dataset. Custom neural models support structured, semi-structured, and unstructured documents to extract fields. Custom neural models currently support English-language documents. When you're choosing between the two model types, start with a neural model if it meets your functional needs. See [neural models](concept-custom-neural.md) to learn more about custom document models.
 
 ## Build mode
 
 The build custom model operation has added support for the *template* and *neural* custom models. Previous versions of the REST API and SDKs only supported a single build mode that is now known as the *template* mode.
 
 * Template models only accept documents that have the same basic page structure—a uniform visual appearance—or the same relative positioning of elements within the document.
 
-* Neural models support documents that have the same information, but different page structures. Examples of these documents include United States W2 forms, which share the same information, but may vary in appearance by the company that created the document. Neural models currently only support English text.
+* Neural models support documents that have the same information, but different page structures. Examples of these documents include United States W2 forms, which share the same information, but may vary in appearance across companies. Neural models currently only support English text.
 
 This table provides links to the build mode programming language SDK references and code samples on GitHub:
 
@@ -68,15 +70,15 @@ The table below compares custom template and custom neural features:
 
 The following tools are supported by Form Recognizer v2.1:
 
-| Feature | Resources |
-|----------|-------------------------|
-|Custom model| <ul><li>[Form Recognizer labeling tool](https://fott-2-1.azurewebsites.net)</li><li>[REST API](quickstarts/try-sdk-rest-api.md?pivots=programming-language-rest-api#analyze-forms-with-a-custom-model)</li><li>[Client library SDK](quickstarts/try-sdk-rest-api.md)</li><li>[Form Recognizer Docker container](containers/form-recognizer-container-install-run.md?tabs=custom#run-the-container-with-the-docker-compose-up-command)</li></ul>|
+| Feature | Resources | Model ID|
+|---|---|:---|
+|Custom model| <ul><li>[Form Recognizer labeling tool](https://fott-2-1.azurewebsites.net)</li><li>[REST API](quickstarts/try-sdk-rest-api.md?pivots=programming-language-rest-api#analyze-forms-with-a-custom-model)</li><li>[Client library SDK](quickstarts/try-sdk-rest-api.md)</li><li>[Form Recognizer Docker container](containers/form-recognizer-container-install-run.md?tabs=custom#run-the-container-with-the-docker-compose-up-command)</li></ul>|***custom-model-id***|
 
 The following tools are supported by Form Recognizer v3.0:
 
-| Feature | Resources |
-|----------|-------------|
-|Custom model| <ul><li>[Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio/customform/projects)</li><li>[REST API](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v3-0-preview-2/operations/AnalyzeDocument)</li><li>[C# SDK](quickstarts/try-v3-csharp-sdk.md)</li><li>[Python SDK](quickstarts/try-v3-python-sdk.md)</li></ul>|
+| Feature | Resources | Model ID|
+|---|---|:---|
+|Custom model| <ul><li>[Form Recognizer Studio](https://formrecognizer.appliedai.azure.com/studio/customform/projects)</li><li>[REST API](https://westus.dev.cognitive.microsoft.com/docs/services/form-recognizer-api-v3-0-preview-2/operations/AnalyzeDocument)</li><li>[C# SDK](quickstarts/try-v3-csharp-sdk.md)</li><li>[Python SDK](quickstarts/try-v3-python-sdk.md)</li></ul>|***custom-model-id***|
 
 ### Try Form Recognizer
 

articles/applied-ai-services/form-recognizer/concept-custom.md

@@ -152,7 +152,7 @@ Analyze and extract text, tables, structure, key-value pairs, and named entities
 > * We've added the file URI value to the `Uri fileUri` variable at the top of the script.
 > * For simplicity, all the entity fields that the service returns are not shown here. To see the list of all supported fields and corresponding types, see the [General document](../concept-general-document.md#named-entity-recognition-ner-categories) concept page.
 
-### Add the following code to the Program.cs file:
+**Add the following code sample to the Program.cs file:**
 
 ```csharp
 using Azure;
@@ -268,7 +268,7 @@ for (int i = 0; i < result.Tables.Count; i++)
 ### General document model output
 
 Visit the Azure samples repository on GitHub to  view the [general document model output](https://github.com/Azure-Samples/cognitive-services-quickstart-code/blob/master/dotnet/FormRecognizer/v3-csharp-sdk-general-document-output.md).
-
+___
 
 ## Layout model
 
@@ -280,7 +280,7 @@ Extract text, selection marks, text styles, table structures, and bounding regio
 > * We've added the file URI value to the `Uri fileUri` variable at the top of the script.
 > * To extract the layout from a given file at a URI, use the `StartAnalyzeDocumentFromUri` method and pass `prebuilt-layout` as the model ID. The returned value is an `AnalyzeResult` object containing data from the submitted document.
 
-#### Add the following code to the Program.cs file:
+**Add the following code sample to the Program.cs file:**
 
 ```csharp
 using Azure;
@@ -383,7 +383,7 @@ Analyze and extract common fields from specific document types using a prebuilt
 > * To analyze a given file at a URI, use the `StartAnalyzeDocumentFromUri` method and pass `prebuilt-invoice` as the model ID. The returned value is an `AnalyzeResult` object containing data from the submitted document.
 > * For simplicity, all the key-value pairs that the service returns are not shown here. To see the list of all supported fields and corresponding types, see our [Invoice](../concept-invoice.md#field-extraction) concept page.
 
-#### Add the following code to your Program.cs file:
+**Add the following code sample to your Program.cs file:**
 
 ```csharp