Merge pull request #264272 from MicrosoftDocs/main

1/25/2024 PM Publish

Author: Taojunshen

.openpublishing.redirection.json

@@ -9194,11 +9194,6 @@
             "redirect_url": "/azure/governance/",
             "redirect_document_id": false
         },
-        {
-            "source_path_from_root": "/articles/governance/policy/samples/new-zealand-ism.md",
-            "redirect_url": "/azure/governance/",
-            "redirect_document_id": false
-        },        
         {
             "source_path_from_root": "/articles/governance/blueprints/samples/azure-security-benchmark/control-mapping.md",
             "redirect_url": "/azure/governance/blueprints/samples/azure-security-benchmark",
@@ -16709,11 +16704,6 @@
             "redirect_url": "/azure/reliability/reliability-deployment-environments",
             "redirect_document_id": false
         },
-        {
-            "source_path_from_root": "/articles/spring-apps/how-to-enable-redundancy-and-disaster-recovery.md",
-            "redirect_url": "/azure/reliability/reliability-spring-apps",
-            "redirect_document_id": false
-        },
         {
             "source_path": "articles/update-center/assessment-options.md",
             "redirect_url": "/azure/update-manager/assessment-options",

articles/ai-services/language-service/sentiment-opinion-mining/custom/quickstart.md

@@ -7,13 +7,13 @@ author: aahill
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: quickstart
-ms.date: 12/19/2023
+ms.date: 01/25/2024
 ms.author: aahi
 ms.custom: language-service-sentiment-opinion-mining
 zone_pivot_groups: usage-custom-language-features
 ---
 
-# Quickstart: Custom sentiment analysis
+# Quickstart: Custom sentiment analysis (preview)
 
 Use this article to get started with creating a Custom sentiment analysis project where you can train custom models for detecting the sentiment of text. A model is artificial intelligence software that's trained to do a certain task. For this system, the models classify text, and are trained by learning from tagged data.
 

articles/ai-services/language-service/sentiment-opinion-mining/overview.md

@@ -7,7 +7,7 @@ author: aahill
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: overview
-ms.date: 12/19/2023
+ms.date: 01/25/2024
 ms.author: aahi
 ms.custom: language-service-sentiment-opinion-mining, ignite-fall-2021
 ---
@@ -36,7 +36,7 @@ Opinion mining is a feature of sentiment analysis. Also known as aspect-based se
 
 [!INCLUDE [Developer reference](../includes/reference-samples-text-analytics.md)] 
 
-#### [Custom model](#tab/custom)
+#### [Custom model (preview)](#tab/custom)
 
 Custom sentiment analysis enables users to build custom AI models to classify text into sentiments pre-defined by the user. By creating a Custom sentiment analysis project, developers can iteratively label data, train, evaluate, and improve model performance before making it available for consumption. The quality of the labeled data greatly impacts model performance. To simplify building and customizing your model, the service offers a custom web portal that can be accessed through the [Language studio](https://aka.ms/languageStudio). You can easily get started with the service by following the steps in this [quickstart](quickstart.md). 
 

articles/ai-services/language-service/sentiment-opinion-mining/quickstart.md

@@ -7,7 +7,7 @@ author: aahill
 manager: nitinme
 ms.service: azure-ai-language
 ms.topic: quickstart
-ms.date: 12/19/2023
+ms.date: 01/25/2024
 ms.author: aahi
 ms.devlang: csharp
 # ms.devlang: csharp, java, javascript, python

articles/ai-services/language-service/toc.yml

@@ -621,7 +621,7 @@ items:
                   href: /java/api/overview/azure/ai-textanalytics-readme?view=azure-java-preview&preserve-view=true
                 - name: Node.js
                   href: /javascript/api/overview/azure/ai-language-text-readme?view=azure-node-preview&preserve-view=true
-      - name: Custom
+      - name: Custom (preview)
         items:
           - name: Quickstart
             href: sentiment-opinion-mining/custom/quickstart.md

articles/ai-services/openai/concepts/provisioned-throughput.md

@@ -62,11 +62,20 @@ az cognitiveservices account deployment create \
 
 Provisioned throughput quota represents a specific amount of total throughput you can deploy. Quota in the Azure OpenAI Service is managed at the subscription level. All Azure OpenAI resources within the subscription share this quota. 
 
-Quota is specific to a (deployment type, model, region) triplet and isn't interchangeable. Meaning you can't use quota for GPT-4 to deploy GPT-35-turbo. You can raise a support request to move quota across deployment types, models, or regions but the swap isn't guaranteed.
+Quota is specified in Provisioned throughput units and is specific to a (deployment type, model, region) triplet. Quota isn't interchangeable. Meaning you can't use quota for GPT-4 to deploy GPT-35-turbo. You can raise a support request to move quota across deployment types, models, or regions but the swap isn't guaranteed.
 
 While we make every attempt to ensure that quota is deployable, quota doesn't represent a guarantee that the underlying capacity is available. The service assigns capacity during the deployment operation and if capacity is unavailable the deployment fails with an out of capacity error.
 
 
+### Determining the number of PTUs needed for a workload
+
+PTUs represent an amount of model processing capacity. Similar to your computer or databases, different workloads or requests to the model will consume different amounts of underlying processing capacity. The conversion from call shape characteristics (prompt size, generation size and call rate) to PTUs is complex and non-linear. To simplify this process, you can use the [Azure OpenAI Capacity calculator](https://oai.azure.com/portal/calculator) to size specific workload shapes. 
+
+A few high-level considerations:
+- Generations require more capacity than prompts
+- Larger calls are progressively more expensive to compute. For example, 100 calls of with a 1000 token prompt size will require less capacity than 1 call with 100,000 tokens in the prompt. This also means that the distribution of these call shapes is important in overall throughput. Traffic patterns with a wide distribution that includes some very large calls may experience lower throughput per PTU than a narrower distribution with the same average prompt & completion token sizes. 
+
+
 ### How utilization enforcement works
 Provisioned deployments provide you with an allocated amount of model processing capacity to run a given model. The `Provisioned-Managed Utilization` metric in Azure Monitor measures a given deployments utilization on 1-minute increments. Provisioned-Managed deployments are optimized to ensure that accepted calls are processed with a consistent model processing time (actual end-to-end latency is dependent on a call's characteristics). When the workload exceeds the allocated PTU capacity, the service returns a 429 HTTP status code until the utilization drops down below 100%. 
 
@@ -94,7 +103,8 @@ We use a variation of the leaky bucket algorithm to maintain utilization below 1
 
 4.	The overall utilization is decremented down at a continuous rate based on the number of PTUs deployed. 
 
-Since calls are accepted until utilization reaches 100%, you're allowed to burst over 100% utilization when first increasing traffic. For sizeable calls and small sized deployments, you might then be over 100% utilization for up to several minutes.
+> [!NOTE]
+> Calls are accepted until utilization reaches 100%. Bursts just over 100% maybe permitted in short periods, but over time, your traffic is capped at 100% utilization.
 
 
 :::image type="content" source="../media/provisioned/utilization.jpg" alt-text="Diagram showing how subsequent calls are added to the utilization." lightbox="../media/provisioned/utilization.jpg":::

articles/aks/ingress-basic.md

@@ -35,6 +35,9 @@ This article shows you how to deploy the [NGINX ingress controller][nginx-ingres
 
 To create a basic NGINX ingress controller without customizing the defaults, you'll use Helm. The following configuration uses the default configuration for simplicity. You can add parameters for customizing the deployment, like `--set controller.replicaCount=3`.
 
+> [!NOTE]
+> If you would like to enable [client source IP preservation][client-source-ip] for requests to containers in your cluster, add `--set controller.service.externalTrafficPolicy=Local` to the Helm install command. The client source IP is stored in the request header under *X-Forwarded-For*. When you're using an ingress controller with client source IP preservation enabled, TLS pass-through won't work.
+
 ### [Azure CLI](#tab/azure-cli)
 
 ```console
@@ -46,7 +49,8 @@ helm repo update
 helm install ingress-nginx ingress-nginx/ingress-nginx \
   --create-namespace \
   --namespace $NAMESPACE \
-  --set controller.service.annotations."service\.beta\.kubernetes\.io/azure-load-balancer-health-probe-request-path"=/healthz
+  --set controller.service.annotations."service\.beta\.kubernetes\.io/azure-load-balancer-health-probe-request-path"=/healthz \
+  --set controller.service.externalTrafficPolicy=Local
 ```
 
 ### [Azure PowerShell](#tab/azure-powershell)
@@ -60,7 +64,8 @@ helm repo update
 helm install ingress-nginx ingress-nginx/ingress-nginx `
   --create-namespace `
   --namespace $Namespace `
-  --set controller.service.annotations."service\.beta\.kubernetes\.io/azure-load-balancer-health-probe-request-path"=/healthz
+  --set controller.service.annotations."service\.beta\.kubernetes\.io/azure-load-balancer-health-probe-request-path"=/healthz `
+  --set controller.service.externalTrafficPolicy=Local
 ```
 
 ---
@@ -148,6 +153,7 @@ helm install ingress-nginx ingress-nginx/ingress-nginx \
     --set controller.image.digest="" \
     --set controller.admissionWebhooks.patch.nodeSelector."kubernetes\.io/os"=linux \
     --set controller.service.annotations."service\.beta\.kubernetes\.io/azure-load-balancer-health-probe-request-path"=/healthz \
+    --set controller.service.externalTrafficPolicy=Local \
     --set controller.admissionWebhooks.patch.image.registry=$ACR_URL \
     --set controller.admissionWebhooks.patch.image.image=$PATCH_IMAGE \
     --set controller.admissionWebhooks.patch.image.tag=$PATCH_TAG \
@@ -181,6 +187,7 @@ helm install ingress-nginx ingress-nginx/ingress-nginx `
     --set controller.image.digest="" `
     --set controller.admissionWebhooks.patch.nodeSelector."kubernetes\.io/os"=linux `
     --set controller.service.annotations."service\.beta\.kubernetes\.io/azure-load-balancer-health-probe-request-path"=/healthz `
+    --set controller.service.externalTrafficPolicy=Local `
     --set controller.admissionWebhooks.patch.image.registry=$AcrUrl `
     --set controller.admissionWebhooks.patch.image.image=$PatchImage `
     --set controller.admissionWebhooks.patch.image.tag=$PatchTag `

articles/aks/supported-kubernetes-versions.md

@@ -50,7 +50,7 @@ For the past release history, see [Kubernetes history](https://github.com/kubern
 | 1.26 | Dec 2022 | Feb 2023 | Apr 2023 | Mar 2024 | Until 1.30 GA |
 | 1.27* | Apr 2023 | Jun 2023 | Jul 2023 | Jul 2024, LTS until Jul 2025 | Until 1.31 GA |
 | 1.28 | Aug 2023 | Sep 2023 | Nov 2023 | Nov 2024 | Until 1.32 GA|
-| 1.29 | Dec 2023 | Jan 2024 | Feb 2024 | | Until 1.33 GA |
+| 1.29 | Dec 2023 | Feb 2024 | Mar 2024 | | Until 1.33 GA |
 
 *\* Indicates the version is designated for Long Term Support*
 

articles/azure-arc/index.yml

@@ -162,8 +162,8 @@ additionalContent:
           summary: Run App Service, Functions, and Logic Apps on Azure Arc-enabled Kubernetes clusters.
           url: /azure/app-service/overview-arc-integration
         # Card
-        - title: AKS hybrid deployment options
-          summary: AKS hybrid simplifies on-premises Kubernetes clusters, natively connecting to Azure Arc.
+        - title: Azure Kubernetes Service (AKS) enabled by Azure Arc 
+          summary: Extend AKS to your on-premises environment.
           url: https://learn.microsoft.com/en-us/azure/aks/hybrid/aks-hybrid-options-overview
         # Card
         - title: Azure IoT Operations Preview – enabled by Azure Arc

articles/azure-arc/resource-bridge/includes/network-requirements.md

@@ -14,15 +14,14 @@ The firewall and proxy URLs below must be allowlisted in order to enable communi
 
 |**Service**|**Port**|**URL**|**Direction**|**Notes**|
 |--|--|--|--|--|
-|SFS API endpoint | 443 | `msk8s.api.cdp.microsoft.com` | Management machine & Appliance VM IPs need outbound connection. | Used when downloading product catalog, product bits, and OS images from SFS. |
+|SFS API endpoint | 443 | `msk8s.api.cdp.microsoft.com` | Management machine & Appliance VM IPs need outbound connection. | Download product catalog, product bits, and OS images from SFS. |
 |Resource bridge (appliance) Dataplane service| 443 | `https://*.dp.prod.appliances.azure.com`| Appliance VMs IP need outbound connection. | Communicate with resource provider in Azure.|
 |Resource bridge (appliance) container image download| 443 | `*.blob.core.windows.net, https://ecpacr.azurecr.io`| Appliance VM IPs need outbound connection. | Required to pull container images. |
 |Managed Identity| 443 | `*.his.arc.azure.com`| Appliance VM IPs need outbound connection. | Required to pull system-assigned Managed Identity certificates. | 
-|Resource bridge (appliance) image download| 80 | `msk8s.b.tlu.dl.delivery.mp.microsoft.com`| Management machine & Appliance VM IPs need outbound connection. |  *Only needed for Arc Appliance CLI extension version 0.2.32 and below.* Download the Arc Resource Bridge OS images.  |
 |Resource bridge (appliance) image download| 443 | `msk8s.sb.tlu.dl.delivery.mp.microsoft.com`| Management machine & Appliance VM IPs need outbound connection. |  Download the Arc Resource Bridge OS images.  |
 |Azure Arc for Kubernetes container image download| 443 | `https://azurearcfork8s.azurecr.io`|  Appliance VM IPs need outbound connection. | Required to pull container images. |
-|ADHS telemetry service | 443 | `adhs.events.data.microsoft.com`| Appliance VM IPs need outbound connection. | Used periodically to send Microsoft required diagnostic data and telemetry from within the appliance VM. |
-|Microsoft events data service | 443 |`v20.events.data.microsoft.com`| Appliance VM IPs need outbound connection. | Used periodically to send Microsoft required diagnostic data from the Azure Stack HCI or Windows Server host. Used when telemetry is coming off Windows like Windows Server or HCI. |
+|ADHS telemetry service | 443 | `adhs.events.data.microsoft.com`| Appliance VM IPs need outbound connection. | Periodically sends Microsoft required diagnostic data from appliance VM. |
+|Microsoft events data service | 443 |`v20.events.data.microsoft.com`| Appliance VM IPs need outbound connection. | Send diagnostic data from Windows, like Windows Server or Azure Stack HCI. |
 |Log collection for Arc Resource Bridge| 443 | `linuxgeneva-microsoft.azurecr.io`| Appliance VM IPs need outbound connection. | Push logs for Appliance managed components.|
 |Azure Arc for Kubernetes container image download| 443 | `https://azurearcfork8sdev.azurecr.io`|  Appliance VM IPs need outbound connection. | Pull container images. |
 |Resource bridge components download| 443 | `kvamanagementoperator.azurecr.io`| Appliance VM IPs need outbound connection. | Pull artifacts for Appliance managed components.|
@@ -31,4 +30,5 @@ The firewall and proxy URLs below must be allowlisted in order to enable communi
 |Custom Locations| 443 | `sts.windows.net`| Appliance VM IPs need outbound connection. | Required for use by the Custom Locations cluster extension.|
 |Python package| 443 | `*.pypi.org`| Management machine needs outbound connection. | Validate Kubernetes and Python versions.|
 |Azure CLI| 443 | `*.pythonhosted.org`| Management machine needs outbound connection. | Python packages for Azure CLI installation.|
-|Diagnostic data | 443 | `gcs.prod.monitoring.core.windows.net`	|	Appliance VM IPs need outbound connection. | Used periodically to send Microsoft required diagnostic data from control plane nodes.|
+|Diagnostic data | 443 | `gcs.prod.monitoring.core.windows.net`	|	Appliance VM IPs need outbound connection. | Periodically sends Microsoft required diagnostic data. |
+|Windows NTP Server| 123 | `time.windows.com` | Appliance VM & Management machine (if HyperV default is Windows NTP) need outbound connection on UDP | OS time sync in appliance VM & Management machine (Windows NTP).|