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

Author: asudbring

articles/ai-services/openai/how-to/embeddings.md

@@ -140,6 +140,7 @@ Our embedding models may be unreliable or pose social risks in certain cases, an
 * Store your embeddings and perform vector (similarity) search using your choice of Azure service:
   * [Azure AI Search](../../../search/vector-search-overview.md)
   * [Azure Cosmos DB for MongoDB vCore](../../../cosmos-db/mongodb/vcore/vector-search.md)
+  * [Azure SQL Database](/azure/azure-sql/database/ai-artificial-intelligence-intelligent-applications?view=azuresql&preserve-view=true#vector-search)
   * [Azure Cosmos DB for NoSQL](../../../cosmos-db/vector-search.md)
   * [Azure Cosmos DB for PostgreSQL](../../../cosmos-db/postgresql/howto-use-pgvector.md)
   * [Azure Database for PostgreSQL - Flexible Server](../../../postgresql/flexible-server/how-to-use-pgvector.md)  

articles/ai-studio/includes/evaluations/from-data/python.md

@@ -128,7 +128,7 @@ For the supported scenarios mentioned previously, we provide default metrics by
 | Question Answering                                         | `qa`              | `gpt_groundedness` (requires context), `gpt_relevance` (requires context), `gpt_coherence` | `gpt_groundedness`, `gpt_relevance`, `gpt_coherence`, `gpt_fluency`, `gpt_similarity`, `f1_score`, `exact_match`, `ada_similarity` |
 | Single and multi-turn conversation (context required) | `chat`            |  `gpt_groundedness`, `gpt_relevance`, `gpt_retrieval_score`                                 |`gpt_groundedness`, `gpt_relevance`, `gpt_retrieval_score`                                 |
 
-### Set up your Azure Open AI configurations for AI-assisted metrics
+### Set up your Azure OpenAI configurations for AI-assisted metrics
 
 Before you call the `evaluate()` function, your environment needs to set up your large language model deployment configuration that's required for generating the AI-assisted metrics. 
 

articles/aks/azure-netapp-files-dual-protocol.md

@@ -42,6 +42,8 @@ AKS supports the following configuration options to manage SSH keys on cluster n
 
 ### Register the `DisableSSHPreview` feature flag
 
+To use the **Disable** SSH feature, perform the following steps to register and enable it in your subscription.
+
 1. Register the `DisableSSHPreview` feature flag using the [`az feature register`][az-feature-register] command.
 
     ```azurecli-interactive

articles/aks/manage-ssh-node-access.md

@@ -95,7 +95,7 @@ For more information, see the following resources:
 
     # Uncomment the following lines according to the authentication type.
     # For system-assigned identity.
-    # credential = DefaultAzureCredential()
+    # cred = DefaultAzureCredential()
 
     # For user-assigned identity.
     # managed_identity_client_id = os.getenv('AZURE_POSTGRESQL_CLIENTID')
@@ -155,4 +155,4 @@ For more information, see the following resources:
 
 -----
 
-For more code samples, see [Create a passwordless connection to a database service via Service Connector](/azure/service-connector/tutorial-passwordless?tabs=user%2Cappservice&pivots=postgresql#connect-to-a-database-with-microsoft-entra-authentication).
+For more code samples, see [Create a passwordless connection to a database service via Service Connector](/azure/service-connector/tutorial-passwordless?tabs=user%2Cappservice&pivots=postgresql#connect-to-a-database-with-microsoft-entra-authentication).

articles/app-service/includes/tutorial-connect-msi-azure-database/code-postgres-mi.md

@@ -31,7 +31,7 @@ If your Azure Cache for Redis client application runs on a Linux-based container
 
 ## Potential connection collision with _Istio/Envoy_
 
-Currently, Azure Cache for Redis uses ports 15000-15019 for clustered caches to expose cluster nodes to client applications. As documented [here](https://istio.io/latest/docs/ops/deployment/requirements/#ports-used-by-istio), the same ports are also used by _Istio.io_ sidecar proxy called _Envoy_ and could interfere with creating connections, especially on port 15006.
+Currently, Azure Cache for Redis uses ports 15xxx for clustered caches to expose cluster nodes to client applications. As documented [here](https://istio.io/latest/docs/ops/deployment/requirements/#ports-used-by-istio), the same ports are also used by _Istio.io_ sidecar proxy called _Envoy_ and could interfere with creating connections, especially on port 15001 and 15006.
 
 When using _Istio_ with an Azure Cache for Redis cluster, consider excluding the potential collision ports with an [istio annotation](https://istio.io/latest/docs/reference/config/annotations/).
 

articles/azure-cache-for-redis/cache-best-practices-kubernetes.md

@@ -167,6 +167,9 @@ In contrast, for clustered caches, we recommend using the metrics with the suffi
     - **Export** – when there's an issue related to Export RDB
     - **AADAuthenticationFailure** (preview) - when there's an authentication failure using Microsoft Entra access token
     - **AADTokenExpired** (preview) - when a Microsoft Entra access token used for authentication isn't renewed and it expires.
+> [!NOTE]
+> Metrics for errors aren't available when using the Enterprise Tiers.
+
 - Evicted Keys
   - The number of items evicted from the cache during the specified reporting interval because of the `maxmemory` limit.
   - This number maps to `evicted_keys` from the Redis INFO command.

articles/azure-cache-for-redis/cache-how-to-monitor.md

@@ -12,7 +12,7 @@ ms.date: 01/08/2024
 
 # Tutorial: Use Azure Cache for Redis as a semantic cache
 
-In this tutorial, you use Azure Cache for Redis as a semantic cache with an AI-based large language model (LLM). You use Azure Open AI Service to generate LLM responses to queries and cache those responses using Azure Cache for Redis, delivering faster responses and lowering costs.
+In this tutorial, you use Azure Cache for Redis as a semantic cache with an AI-based large language model (LLM). You use Azure OpenAI Service to generate LLM responses to queries and cache those responses using Azure Cache for Redis, delivering faster responses and lowering costs.
 
 Because Azure Cache for Redis offers built-in vector search capability, you can also perform  _semantic caching_. You can return cached responses for identical queries and also for queries that are similar in meaning, even if the text isn't the same.
 
@@ -78,7 +78,7 @@ See [Deploy a model](/azure/ai-services/openai/how-to/create-resource?pivots=web
 
 To successfully make a call against Azure OpenAI, you need an **endpoint** and a **key**. You also need an **endpoint** and a **key** to connect to Azure Cache for Redis.
 
-1. Go to your Azure Open AI resource in the Azure portal.
+1. Go to your Azure OpenAI resource in the Azure portal.
 
 1. Locate **Endpoint and Keys** in the **Resource Management** section of your Azure OpenAI resource. Copy your endpoint and access key because you need both for authenticating your API calls. An example endpoint is: `https://docs-test-001.openai.azure.com`. You can use either `KEY1` or `KEY2`.
 

articles/azure-cache-for-redis/cache-tutorial-semantic-cache.md

@@ -1,7 +1,7 @@
 ---
 title: Create a JavaScript function from the command line - Azure Functions
 description: Learn how to create a JavaScript function from the command line, then publish the local Node.js project to serverless hosting in Azure Functions.
-ms.date: 12/15/2023
+ms.date: 02/26/2024
 ms.topic: quickstart
 ms.devlang: javascript
 ms.custom: devx-track-azurecli, devx-track-azurepowershell, mode-api, devx-track-js
@@ -50,19 +50,20 @@ In Azure Functions, a function project is a container for one or more individual
 
 ::: zone pivot="nodejs-model-v3" 
 1. In a suitable folder, run the [`func init`](functions-core-tools-reference.md#func-init) command, as follows, to create a JavaScript Node.js v3 project in the current folder:
-
+   
     ```console
     func init --javascript --model V3
     ```
+    
     This folder now contains various files for the project, including configurations files named [local.settings.json](functions-develop-local.md#local-settings-file) and [host.json](functions-host-json.md). Because *local.settings.json* can contain secrets downloaded from Azure, the file is excluded from source control by default in the *.gitignore* file.
 
 1. Add a function to your project by using the following command, where the `--name` argument is the unique name of your function (HttpExample) and the `--template` argument specifies the function's trigger (HTTP).
-
+   
     ```console
     func new --name HttpExample --template "HTTP trigger" --authlevel "anonymous"
     ```
-
-     [`func new`](functions-core-tools-reference.md#func-new)  creates a subfolder matching the function name that contains a code file appropriate to the project's chosen language and a configuration file named *function.json*.
+    
+    The [`func new`](functions-core-tools-reference.md#func-new) command creates a subfolder matching the function name that contains a code file appropriate to the project's chosen language and a configuration file named *function.json*.
 
 You may find the [Azure Functions Core Tools reference](functions-core-tools-reference.md) helpful.
 

articles/azure-functions/create-first-function-cli-node.md

@@ -258,10 +258,9 @@ The Azure Monitoring Agent for Linux now officially supports various hardening s
 Currently supported hardening standards:
 - SELinux
 - CIS Lvl 1 and 2<sup>1</sup>
-
-On the roadmap
 - STIG
 - FIPs
+- FedRamp
 
 | Operating system | Azure Monitor agent <sup>1</sup> | Log Analytics agent (legacy) <sup>1</sup> | Diagnostics extension <sup>2</sup>|
 |:---|:---:|:---:|:---:|