Merge pull request #267872 from MicrosoftDocs/repo_sync_working_branch

rmca14 · web-flow · commit 3ab35ef503f3 · 2024-03-04T10:40:09.000-08:00
Confirm merge from repo_sync_working_branch to main to sync with https://github.com/MicrosoftDocs/azure-docs (branch main)
diff --git a/articles/ai-studio/how-to/create-azure-ai-resource.md b/articles/ai-studio/how-to/create-azure-ai-resource.md
@@ -114,7 +114,7 @@ At Azure AI hub resource creation, select between the networking isolation modes
 
 At Azure AI hub resource creation in the Azure portal, creation of associated Azure AI services, Storage account, Key vault, Application insights, and Container registry is given. These resources are found on the Resources tab during creation. 
 
-To connect to Azure AI services (Azure OpenAI, Azure AI Search, and Azure AI Content Safety) or storage accounts in Azure AI Studio, create a private endpoint in your virtual network. Ensure the PNA flag is disabled when creating the private endpoint connection. For more about Azure AI services connections, follow documentation [here](../../ai-services/cognitive-services-virtual-networks.md). You can optionally bring your own (BYO) search, but this requires a private endpoint connection from your virtual network.
+To connect to Azure AI services (Azure OpenAI, Azure AI Search, and Azure AI Content Safety) or storage accounts in Azure AI Studio, create a private endpoint in your virtual network. Ensure the PNA (Public Network Access) flag is disabled when creating the private endpoint connection. For more about Azure AI services connections, follow documentation [here](../../ai-services/cognitive-services-virtual-networks.md). You can optionally bring your own (BYO) search, but this requires a private endpoint connection from your virtual network.
 
 ### Encryption
 Projects that use the same Azure AI hub resource, share their encryption configuration. Encryption mode can be set only at the time of Azure AI hub resource creation between Microsoft-managed keys and Customer-managed keys. 
diff --git a/articles/aks/concepts-sustainable-software-engineering.md b/articles/aks/concepts-sustainable-software-engineering.md
@@ -195,7 +195,7 @@ A service mesh deploys extra containers for communication, typically in a [sidec
 
 Sending and storing all logs from all possible sources (workloads, services, diagnostics, and platform activity) can increase storage and network traffic, which impacts costs and carbon emissions.
 
-* Make sure you're collecting and retaining only the necessary log data to support your requirements. [Configure data collection rules for your AKS workloads](../azure-monitor/containers/container-insights-data-collection-configmap.md#data-collection-settings) and implement design considerations for [optimizing your Log Analytics costs](/azure/architecture/framework/services/monitoring/log-analytics/cost-optimization).
+* Make sure you're collecting and retaining only the necessary log data to support your requirements. [Configure data collection rules for your AKS workloads](../azure-monitor/containers/container-insights-data-collection-configmap.md#data-collection-settings) and implement design considerations for optimizing your Log Analytics costs.
 
 ### Cache static data
 
diff --git a/articles/data-factory/concept-managed-airflow.md b/articles/data-factory/concept-managed-airflow.md
@@ -42,7 +42,7 @@ Managed Airflow in Azure Data Factory offers a range of powerful features, inclu
 - **Microsoft Entra integration** - You can enable [Microsoft Entra RBAC](concepts-roles-permissions.md) against your Airflow environment for a single sign-on experience that is secured by Microsoft Entra ID. 
 - **Managed Virtual Network integration** (coming soon) - You can access your data source via private endpoints or on-premises using ADF Managed Virtual Network that provides extra network isolation.
 - **Metadata encryption** - Managed Airflow automatically encrypts metadata using Azure-managed keys to ensure your environment is secure by default. It also supports double encryption with a [Customer-Managed Key (CMK)](enable-customer-managed-key.md).  
-- **Azure Monitoring and alerting** - All the logs generated by Managed Airflow is exported to Azure Monitor. It also provides metrics to track critical conditions and help you notify if the need be.
+- **Azure Monitoring and alerting** - All the logs generated by Managed Airflow are exported to Azure Monitor. It also provides metrics to track critical conditions and help you notify if the need be.
 
 ## Architecture
    :::image type="content" source="media/concept-managed-airflow/architecture.png" lightbox="media/concept-managed-airflow/architecture.png" alt-text="Screenshot shows architecture in Managed Airflow.":::
diff --git a/articles/healthcare-apis/fhir/fhir-service-resource-manager-template.md b/articles/healthcare-apis/fhir/fhir-service-resource-manager-template.md
@@ -119,15 +119,15 @@ You can deploy the FHIR service resource by **removing** the workspaces resource
         {
             "type": "Microsoft.HealthcareApis/workspaces",
             "name": "[parameters('workspaceName')]",
-            "apiVersion": "2020-11-01-preview",
+            "apiVersion": "2023-11-01",
             "location": "[parameters('region')]",
             "properties": {}
         },
        {          
             "type": "Microsoft.HealthcareApis/workspaces/fhirservices",
             "kind": "fhir-R4",
             "name": "[concat(parameters('workspaceName'), '/', parameters('fhirServiceName'))]",
-            "apiVersion": "2020-11-01-preview",
+            "apiVersion": "2023-11-01",
             "location": "[parameters('region')]",
             "dependsOn": [
                 "[resourceId('Microsoft.HealthcareApis/workspaces', parameters('workspaceName'))]"
@@ -205,7 +205,7 @@ You can create a new resource group, or use an existing one by skipping the step
 $resourcegroupname="your resource group"
 $location="South Central US"
 $workspacename="your workspace name"
-$servicename="your fhir service name"
+$fhirservicename="your fhir service name"
 $tenantid="xxx"
 $subscriptionid="xxx"
 $storageaccountname="storage account name"
diff --git a/articles/key-vault/managed-hsm/best-practices.md b/articles/key-vault/managed-hsm/best-practices.md
@@ -23,7 +23,7 @@ Managed HSM is a cloud service that safeguards cryptographic keys. Because these
 
 To control access to your managed HSM:
 
-- Create an [Microsoft Entra security group](../../active-directory/fundamentals/active-directory-manage-groups.md) for the HSM Administrators (instead of assigning the Administrator role to individuals) to prevent "administration lockout" if an individual account is deleted.
+- Create a [Microsoft Entra security group](../../active-directory/fundamentals/active-directory-manage-groups.md) for the HSM Administrators (instead of assigning the Administrator role to individuals) to prevent "administration lockout" if an individual account is deleted.
 - Lock down access to your management groups, subscriptions, resource groups, and managed HSMs. Use Azure role-based access control (Azure RBAC) to control access to your management groups, subscriptions, and resource groups.
 - Create per-key role assignments by using [Managed HSM local RBAC](access-control.md#data-plane-and-managed-hsm-local-rbac).
 - To maintain separation of duties, avoid assigning multiple roles to the same principals.
diff --git a/articles/logic-apps/workflow-assistant-standard.md b/articles/logic-apps/workflow-assistant-standard.md
@@ -99,7 +99,7 @@ The following table includes only some example use cases, so please share your f
 
 - Workflow size
 
-  You might experience different performance levels in the workflow assistant, based on factors such as the number of workflow operations or complexity. The assistant is trained on workflows with different complexity levels but still has limited scope and might not be able to handle very large workflows. These limitations are primarily related to token constraints in the queries sent to Azure Open AI Service. The Azure Logic Apps team is committed to continuous improvement and enhancing these limitations through iterative updates.
+  You might experience different performance levels in the workflow assistant, based on factors such as the number of workflow operations or complexity. The assistant is trained on workflows with different complexity levels but still has limited scope and might not be able to handle very large workflows. These limitations are primarily related to token constraints in the queries sent to Azure OpenAI Service. The Azure Logic Apps team is committed to continuous improvement and enhancing these limitations through iterative updates.
 
 <a name="provide-feedback"></a>
 
@@ -146,9 +146,9 @@ In the chat pane, under the workflow assistant's response, choose an option:
 
 **Q**: How does the workflow assistant use my query to generate responses?
 
-**A**: The workflow is powered by [Azure Open AI Service](../ai-services/openai/overview.md) and [ChatGPT](https://openai.com/blog/chatgpt), which use Azure Logic Apps documentation from reputable sources along with internet data that's used to train GPT 3.5-Turbo. This content is processed into a vectorized format, which is then accessible through a backend system built on Azure App Service. Queries are triggered based on interactions with the workflow designer.
+**A**: The workflow is powered by [Azure OpenAI Service](../ai-services/openai/overview.md) and [ChatGPT](https://openai.com/blog/chatgpt), which use Azure Logic Apps documentation from reputable sources along with internet data that's used to train GPT 3.5-Turbo. This content is processed into a vectorized format, which is then accessible through a backend system built on Azure App Service. Queries are triggered based on interactions with the workflow designer.
 
-When you enter your question in the assistant's chat box, the Azure Logic Apps backend performs preprocessing and forwards the results to a large language model in Azure Open AI Service. This model generates responses based on the current context in the form of the workflow definition's JSON code and your prompt. 
+When you enter your question in the assistant's chat box, the Azure Logic Apps backend performs preprocessing and forwards the results to a large language model in Azure OpenAI Service. This model generates responses based on the current context in the form of the workflow definition's JSON code and your prompt. 
 
 **Q**: What data does the workflow assistant collect?
 
@@ -172,7 +172,7 @@ When you enter your question in the assistant's chat box, the Azure Logic Apps b
 
 **Q**: What's the difference between Azure OpenAI Service and ChatGPT?
 
-**A**: [Azure Open AI Service](../ai-services/openai/overview.md) is an enterprise-ready AI technology that's powered and optimized for your business processes and your business data to meet security and privacy requirements.
+**A**: [Azure OpenAI Service](../ai-services/openai/overview.md) is an enterprise-ready AI technology that's powered and optimized for your business processes and your business data to meet security and privacy requirements.
 
 [ChatGPT](https://openai.com/blog/chatgpt) is built by [Open AI](https://openai.com) and is a general-purpose large language model (LLM) trained by OpenAI on a massive dataset of text, designed to engage in human-like conversations and answer a wide range of questions on several topics.
 
