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

Author: normesta

articles/aks/aks-planned-maintenance-weekly-releases.md

@@ -10,7 +10,7 @@ author: kaarthis
 
 ---
 
-#  Use Planned Maintenance to schedule maintenance windows for your Azure Kubernetes Service (AKS) cluster exclusively for weekly releases (preview)
+# Use Planned Maintenance window for scheduling exclusive Azure Kubernetes Service (AKS) weekly releases (Preview)
 
  Planned Maintenance allows you to schedule weekly maintenance windows that will ensure the weekly releases [releases] are controlled. Maintenance Windows are configured using the Azure CLI, allowing you to select from a set of pre-available configurations.
 
@@ -22,17 +22,15 @@ This article assumes that you have an existing AKS cluster. If you need an AKS c
 
 ### Limitations
 
-When using Planned Maintenance, the following restrictions apply:
+When you use Planned Maintenance, the following restrictions apply:
 
 - AKS reserves the right to break these windows for unplanned/reactive maintenance operations that are urgent or critical.
 - Currently, performing maintenance operations are considered *best-effort only* and are not guaranteed to occur within a specified window.
 - Updates cannot be blocked for more than seven days.
 
-
-
 ## Available pre-created public maintenance configurations for you to pick
 
-There are 2 general kinds of pre-created public maintenance configurations:
+There are two general kinds of pre-created public maintenance configurations:
 
 - For Weekday (Monday, Tuesday, Wednesday, Thursday), from 10 pm to 6 am next morning.
 - For Weekend (Friday, Saturday, Sunday), from 10 pm to 6 am next morning.

articles/cognitive-services/LUIS/app-schema-definition.md

@@ -9,6 +9,9 @@ ms.date: 08/22/2020
 
 # App schema definition
 
+[!INCLUDE [deprecation notice](./includes/deprecation-notice.md)]
+
+
 The LUIS app is represented in either the `.json` or `.lu` and includes all intents, entities, example utterances, features, and settings.
 
 ## Format
@@ -141,4 +144,4 @@ When you import and export the app, choose either `.json` or `.lu`.
 
 ## Next steps
 
-* Migrate to the [V3 authoring APIs](luis-migration-authoring-entities.md)
+* Migrate to the [V3 authoring APIs](luis-migration-authoring-entities.md)

articles/cognitive-services/LUIS/choose-natural-language-processing-service.md

@@ -9,8 +9,11 @@ ms.date: 10/20/2020
 
 # Use Cognitive Services with natural language processing (NLP) to enrich chat bot conversations
 
+[!INCLUDE [deprecation notice](./includes/deprecation-notice.md)]
+
+
 [!INCLUDE [QnA and LUIS - concepts](../includes/luis-qnamaker-shared-concept.md)]
 
 ## Next steps
 
-* Learn [enterprise design strategies](luis-concept-enterprise.md)
+* Learn [enterprise design strategies](luis-concept-enterprise.md)

articles/cognitive-services/LUIS/client-libraries-rest-api.md

@@ -15,8 +15,7 @@ zone_pivot_groups: programming-languages-set-luis
 ---
 # Quickstart: Language Understanding (LUIS) client libraries and REST API
 
-> [!NOTE]
-> A newer version of Language Understanding capabilities are now available as part of Azure Cognitive Service for Language. For more information see [Azure Cognitive Service for Language Documentation](../language-service/index.yml). For language understanding capabilities within the Language Service, see [Conversational Language Understanding](../language-service/conversational-language-understanding/overview.md), [Custom Named Entity Recognition](../language-service/custom-named-entity-recognition/overview.md), and [Custom Classification](../language-service/custom-classification/overview.md).
+[!INCLUDE [deprecation notice](./includes/deprecation-notice.md)]
 
 Create and query an Azure LUIS artificial intelligence (AI) app with the LUIS SDK client libraries with this quickstart using C#, Python, or JavaScript. You can also use cURL to send requests using the REST API.
 

articles/cognitive-services/LUIS/concepts/application-design.md

@@ -16,6 +16,9 @@ ms.date: 01/10/2022
 
 # Plan your LUIS app
 
+[!INCLUDE [deprecation notice](../includes/deprecation-notice.md)]
+
+
 A Language Understanding (LUIS) app schema contains [intents](../luis-glossary.md#intent) and [entities](../luis-glossary.md#entity) relevant to your subject [domain](../luis-glossary.md#domain). The intents classify user [utterances](../luis-glossary.md#utterance), and the entities extract data from the user utterances. Intents and entities relevant to your subject domain. The intents classify user utterances.
 
 A LUIS app learns and performs most efficiently when you iteratively develop it. Here's a typical iteration cycle:

articles/cognitive-services/LUIS/concepts/entities.md

@@ -16,6 +16,9 @@ ms.date: 07/19/2022
 
 # Entity types
 
+[!INCLUDE [deprecation notice](../includes/deprecation-notice.md)]
+
+
 An entity is an item or an element that is relevant to the user's intent. Entities define data that can be extracted from the utterance and is essential to complete a user's required action. For example:
 
 
@@ -47,9 +50,9 @@ Matching list entities is both case sensitive and it has to be an exact match. N
 
 | Normalized value | Synonyms |
 |--|--|
-| Small | sm, sml, tiny, smallest |
-| Medium | md, mdm, regular, average, middle |
-| Large | lg, lrg, big |
+| Small | `sm`, `sml`, `tiny`, `smallest` |
+| Medium | `md`, `mdm`, `regular`, `average`, `middle` |
+| Large | `lg`, `lrg`, `big` |
 
 See the [list entities reference article](../reference-entity-list.md) for more information.
 
@@ -59,8 +62,8 @@ A regular expression entity extracts an entity based on a regular expression pat
 
 | Entity | Regular expression | Example |
 |--|--|--|
-| Flight Number | flight [A-Z]{2} [0-9]{4} | flight AS 1234 |
-| Credit Card Number | [0-9]{16} | 5478789865437632 |
+| Flight Number | `flight [A-Z]{2} [0-9]{4}` | `flight AS 1234` |
+| Credit Card Number | `[0-9]{16}` | `5478789865437632` |
 
 See the [regex entities reference article](../reference-entity-regular-expression.md) for more information.
 
@@ -74,7 +77,7 @@ When a prebuilt entity is included in your application, its predictions are incl
 | Prebuilt entity | Example value |
 |--|--|
 | PersonName | James, Bill, Tom |
-| DatetimeV2 | 2019-05-02, May 2nd, 8am on May 2nd 2019 |
+| DatetimeV2 | `2019-05-02`, `May 2nd`, `8am on May 2nd 2019` |
 
 See the [prebuilt entities reference article](../luis-reference-prebuilt-entities.md) for more information.
 
@@ -85,9 +88,9 @@ A pattern.Any entity is a variable-length placeholder used only in a pattern's t
 
 | Example utterance | Pattern | Entity |
 |--|--|--|
-| Can I have a burger please? | Can I have a {meal} [please][?] | burger |
-| Can I have a pizza? | Can I have a {meal} [please][?] | pizza |
-| Where can I find The Great Gatsby? | Where can I find {bookName}? | The Great Gatsby |
+| Can I have a burger please? | `Can I have a {meal} [please][?]` | burger |
+| Can I have a pizza? | `Can I have a {meal} [please][?]` | pizza |
+| Where can I find The Great Gatsby? | `Where can I find {bookName}?` | The Great Gatsby |
 
 See the [Pattern.Any entities reference article](../reference-entity-pattern-any.md) for more information.
 

articles/cognitive-services/LUIS/concepts/intents.md

@@ -14,6 +14,9 @@ ms.date: 07/19/2022
 ---
 # Intents 
 
+[!INCLUDE [deprecation notice](../includes/deprecation-notice.md)]
+
+
 An intent represents a task or action the user wants to perform. It is a purpose or goal expressed in a user's [utterance](utterances.md).
 
 Define a set of intents that corresponds to actions users want to take in your application. For example, a travel app would have several intents:

articles/cognitive-services/LUIS/concepts/patterns-features.md

@@ -15,6 +15,9 @@ ms.date: 07/19/2022
 
 # Patterns in LUIS apps
 
+[!INCLUDE [deprecation notice](../includes/deprecation-notice.md)]
+
+
 Patterns are designed to improve accuracy when multiple utterances are very similar. A pattern allows you to gain more accuracy for an intent without providing several more utterances.
 
 ## Patterns solve low intent confidence

articles/cognitive-services/LUIS/concepts/utterances.md

@@ -11,6 +11,9 @@ ms.date: 07/19/2022
 ---
 # Utterances
 
+[!INCLUDE [deprecation notice](../includes/deprecation-notice.md)]
+
+
 Utterances are inputs from users that your app needs to interpret. To train LUIS to extract intents and entities from these inputs, it's important to capture various different example utterances for each intent. Active learning, or the process of continuing to train on new utterances, is essential to the machine-learning intelligence that LUIS provides.
 
 Collect utterances that you think users will enter. Include utterances, which mean the same thing but are constructed in various ways:

articles/cognitive-services/LUIS/data-collection.md

@@ -9,6 +9,9 @@ ms.date: 05/06/2020
 
 # Data collection for your app
 
+[!INCLUDE [deprecation notice](./includes/deprecation-notice.md)]
+
+
 A Language Understanding (LUIS) app needs data as part of app development.
 
 ## Data used in LUIS