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

Author: Learn Build Service GitHub App

.openpublishing.redirection.json

@@ -11792,6 +11792,17 @@
             "source_path_from_root": "/articles/orbital/overview-analytics.md",
             "redirect_url": "/azure/orbital/overview",
             "redirect_document_id": false
+        },
+        {
+            "source_path_from_root": "/articles/azure-health-insights/request-info.md",
+            "redirect_url": "/azure/azure-health-insights/overview",
+            "redirect_document_id": false
+           
+        },
+        {
+            "source_path_from_root": "/articles/azure-health-insights/response-info.md",
+            "redirect_url": "/azure/azure-health-insights/overview",
+            "redirect_document_id": false
         }
     ]
 }

articles/ai-services/computer-vision/how-to/blob-storage-search.md

@@ -1,5 +1,5 @@
 ---
-title: Configure your blob storage container for image retrieval and video search
+title: Configure your blob storage container for image retrieval
 titleSuffix: Azure AI services
 description: Configure your Azure storage account to get started with the **Search photos image retrieval** experience in Vision Studio.
 #services: cognitive-services
@@ -13,14 +13,14 @@ ms.author: pafarley
 
 ---
 
-# Configure your blob storage for image retrieval and video search in Vision Studio
+# Configure your blob storage for image retrieval in Vision Studio
 
-To get started with the **Search photos image retrieval** scenario in Vision Studio, you need to select or create a new Azure storage account. Your storage account can be in any region, but creating it in the same region as your Vision resource is more efficient and reduces cost. 
+To get started with the **Search photos with image retrieval** scenario in Vision Studio, you need to select or create a new Azure storage account. Your storage account can be in any region, but creating it in the same region as your Vision resource is more efficient and reduces cost. 
 
 > [!IMPORTANT]
-> You need to create your storage account on the same Azure subscription as the Vision resource you're using in the **Search photos image retrieval** scenario as shown below.
-
-:::image type="content" source="../media/storage-instructions/subscription.png" alt-text="Screenshot of resource selection.":::
+> You need to create your storage account on the same Azure subscription as the Vision resource you're using in the **Search photos with image retrieval** scenario.
+>
+> :::image type="content" source="../media/storage-instructions/subscription.png" alt-text="Screenshot of resource selection.":::
 
 ## Create a new storage account
 
@@ -53,13 +53,9 @@ In the Allowed Methods field, select the `GET` checkbox to allow an authenticate
 :::image type="content" source="../media/storage-instructions/cors-rule.png" alt-text="Screenshot of completed CORS screen.":::
 
 
-This allows Vision Studio to access images and videos in your blob storage container to extract insights on your data.
-
-## Upload images and videos in Vision Studio
-
-In the **Try with your own video** or **Try with your own image** section in Vision Studio, select the storage account that you configured with the CORS rule. Select the container in which your images or videos are stored. If you don't have a container, you can create one and upload the images or videos from your local device. If you have updated the CORS rules on the storage account, refresh the Blob container or Video files on container sections.
-
+This allows Vision Studio to access images in your blob storage container to extract insights on your data.
 
-:::image type="content" source="../media/storage-instructions/video-selection.png" alt-text="Screenshot of image upload in Vision Studio.":::
+## Upload images in Vision Studio
 
+In the **Search photos with image retrieval** section in Vision Studio, select the storage account that you configured with the CORS rule. Select the container in which your images are stored. If you don't have a container, you can create one and upload the images from your local device. If you have updated the CORS rules on the storage account, refresh the Blob container or Video files on container sections.
 

articles/ai-services/computer-vision/how-to/image-retrieval.md

@@ -8,7 +8,7 @@ manager: nitinme
 
 ms.service: azure-ai-vision
 ms.topic: how-to
-ms.date: 01/19/2024
+ms.date: 01/30/2024
 ms.author: pafarley
 ms.custom: references_regions
 ---
@@ -90,7 +90,9 @@ The API call returns a **vector** JSON object, which defines the text string's c
 
 Cosine similarity is a method for measuring the similarity of two vectors. In an image retrieval scenario, you'll compare the search query vector with each image's vector. Images that are above a certain threshold of similarity can then be returned as search results.
 
-The following example C# code calculates the cosine similarity between two vectors. It's up to you to decide what similarity threshold to use for returning images as search results.
+The following example code calculates the cosine similarity between two vectors. It's up to you to decide what similarity threshold to use for returning images as search results.
+
+#### [C#](#tab/csharp)
 
 ```csharp
 public static float GetCosineSimilarity(float[] vector1, float[] vector2)
@@ -108,6 +110,17 @@ public static float GetCosineSimilarity(float[] vector1, float[] vector2)
 }
 ```
 
+#### [Python](#tab/python)
+
+```python
+import numpy as np
+
+def cosine_similarity(vector1, vector2):
+    return np.dot(vector1, vector2) / (np.linalg.norm(vector1) * np.linalg.norm(vector2))
+```
+
+---
+
 ## Next steps
 
 [Image retrieval concepts](../concept-image-retrieval.md)

articles/ai-services/computer-vision/includes/identity-curl-quickstart.md

@@ -52,7 +52,7 @@ Get started with facial recognition using the Face REST API. The Face service pr
 
     Save the IDs of each **Person** created; it's important to keep track of which person name has which ID.
 
-1. Next you'll need to detect new faces and associate them with the **Person** objects that exist. The following command detects a face from the image *Family1-Dad.jpg* and adds it to the corresponding person. You need to specify the `personId` as the ID that was returned when you created the "Family1-Dad" **Person** object. The image name corresponds to the name of the created **Person**. Also enter the **LargePersonGroup** ID and your key in the appropriate fields.
+1. Next you'll need to detect new faces and associate them with the **Person** objects that exist. The following command detects a face from the image *Family1-Dad1.jpg* and adds it to the corresponding person. You need to specify the `personId` as the ID that was returned when you created the "Family1-Dad" **Person** object. The image name corresponds to the name of the created **Person**. Also enter the **LargePersonGroup** ID and your key in the appropriate fields.
 
     :::code source="~/cognitive-services-quickstart-code/curl/face/detect.sh" ID="identify_add_face":::
 

articles/ai-services/openai/includes/dall-e-python.md

@@ -13,7 +13,7 @@ ms.date: 11/06/2023
 
 Use this guide to get started generating images with the Azure OpenAI SDK for Python.
 
-[Library source code](https://github.com/openai/openai-python/tree/main/openai) | [Package](https://github.com/openai/openai-python) | [Samples](https://github.com/openai/openai-python/tree/main/examples)
+[Library source code](https://github.com/openai/openai-python/tree/main/src/openai) | [Package](https://github.com/openai/openai-python) | [Samples](https://github.com/openai/openai-python/tree/main/examples)
 
 ## Prerequisites
 

articles/aks/TOC.yml

@@ -646,8 +646,12 @@
           href: events.md
         - name: Monitor kube-audit events
           href: monitor-apiserver.md
+        - name: Monitor control plane metrics
+          href: monitor-control-plane-metrics.md
         - name: Monitor reference
           href: monitor-aks-reference.md
+        - name: Control plane metrics reference
+          href: control-plane-metrics-default-list.md
         - name: View the kubelet logs
           href: kubelet-logs.md
         - name: View container data real-time

articles/aks/app-routing-dns-ssl.md

@@ -57,9 +57,11 @@ az keyvault create -g <ResourceGroupName> -l <Location> -n <KeyVaultName> --enab
 
 ### Create and export a self-signed SSL certificate
 
-> [!NOTE]
-> If you already have a certificate, you can skip this step.
-> 
+For testing, you can use a self-signed public certificate instead of a Certificate Authority (CA)-signed certificate. If you already have a certificate, you can skip this step.
+
+> [!CAUTION]
+> Self-signed certificates are digital certificates that are not signed by a trusted third-party CA. Self-signed certificates are created, issued, and signed by the company or developer who is responsible for the website or software being signed. This is why self-signed certificates are considered unsafe for public-facing websites and applications. Azure Key Vault has a [trusted partnership with the some Certificate Authorities](../key-vault/certificates/how-to-integrate-certificate-authority.md).
+
 1. Create a self-signed SSL certificate to use with the Ingress using the `openssl req` command. Make sure you replace *`<Hostname>`* with the DNS name you're using.
 
     ```bash

articles/aks/control-plane-metrics-default-list.md

@@ -0,0 +1,116 @@
+---
+title: List of control plane metrics in Azure Monitor managed service for Prometheus (preview)
+description: This article describes the minimal ingestion profile metrics for Azure Kubernetes Service (AKS) control plane metrics.
+ms.topic: conceptual
+ms.date: 01/31/2024
+ms.reviewer: aritraghosh
+---
+
+# Minimal ingestion profile for control plane Metrics in Managed Prometheus
+
+Azure Monitor metrics addon collects many Prometheus metrics by default. `Minimal ingestion profile` is a setting that helps reduce ingestion volume of metrics, as only metrics used by default dashboards, default recording rules and default alerts are collected. This article describes how this setting is configured specifically for control plane metrics. This article also lists metrics collected by default when `minimal ingestion profile` is enabled.
+
+> [!NOTE]
+> For addon based collection, `Minimal ingestion profile` setting is enabled by default. The discussion here is focused on control plane metrics. The current set of default targets and metrics is listed [here][azure-monitor-prometheus-metrics-scrape-config-minimal].
+
+Following targets are **enabled/ON** by default - meaning you don't have to provide any scrape job configuration for scraping these targets, as metrics addon scrapes these targets automatically by default:
+
+- `controlplane-apiserver` (job=`controlplane-apiserver`)
+- `controlplane-etcd` (job=`controlplane-etcd`)
+
+Following targets are available to scrape, but scraping isn't enabled (**disabled/OFF**) by default. Meaning you don't have to provide any scrape job configuration for scraping these targets, and you need to turn **ON/enable** scraping for these targets using the [ama-metrics-settings-configmap][ama-metrics-settings-configmap-github] under the `default-scrape-settings-enabled` section.
+
+- `controlplane-cluster-autoscaler`
+- `controlplane-kube-scheduler`
+- `controlplane-kube-controller-manager`
+
+> [!NOTE]
+> The default scrape frequency for all default targets and scrapes is `30 seconds`. You can override it for each target using the [ama-metrics-settings-configmap][ama-metrics-settings-configmap-github] under `default-targets-scrape-interval-settings` section.
+
+### Minimal ingestion for default ON targets
+
+The following metrics are allow-listed with `minimalingestionprofile=true` for default **ON** targets. The below metrics are collected by default, as these targets are scraped by default.
+
+**controlplane-apiserver**
+
+- `apiserver_request_total`
+- `apiserver_cache_list_fetched_objects_total`
+- `apiserver_cache_list_returned_objects_total`
+- `apiserver_flowcontrol_demand_seats_average`
+- `apiserver_flowcontrol_current_limit_seats`
+- `apiserver_request_sli_duration_seconds_bucket`
+- `apiserver_request_sli_duration_seconds_sum`
+- `apiserver_request_sli_duration_seconds_count`
+- `process_start_time_seconds`
+- `apiserver_request_duration_seconds_bucket`
+- `apiserver_request_duration_seconds_sum`
+- `apiserver_request_duration_seconds_count`
+- `apiserver_storage_list_fetched_objects_total`
+- `apiserver_storage_list_returned_objects_total`
+- `apiserver_current_inflight_requests`
+
+**controlplane-etcd**
+
+- `etcd_server_has_leader`
+- `rest_client_requests_total`
+- `etcd_mvcc_db_total_size_in_bytes`
+- `etcd_mvcc_db_total_size_in_use_in_bytes`
+- `etcd_server_slow_read_indexes_total`
+- `etcd_server_slow_apply_total`
+- `etcd_network_client_grpc_sent_bytes_total`
+- `etcd_server_heartbeat_send_failures_total`
+
+### Minimal ingestion for default OFF targets
+
+The following are metrics that are allow-listed with `minimalingestionprofile=true` for default **OFF** targets. These metrics aren't collected by default. You can turn **ON** scraping for these targets using `default-scrape-settings-enabled.<target-name>=true` using the [ama-metrics-settings-configmap][ama-metrics-settings-configmap-github] under the `default-scrape-settings-enabled` section.
+
+**controlplane-kube-controller-manager**
+
+- `workqueue_depth `
+- `rest_client_requests_total`
+- `rest_client_request_duration_seconds `
+
+**controlplane-kube-scheduler**
+
+- `scheduler_pending_pods`
+- `scheduler_unschedulable_pods`
+- `scheduler_queue_incoming_pods_total`
+- `scheduler_schedule_attempts_total`
+- `scheduler_preemption_attempts_total`
+
+**controlplane-cluster-autoscaler**
+
+- `rest_client_requests_total`
+- `cluster_autoscaler_last_activity`
+- `cluster_autoscaler_cluster_safe_to_autoscale`
+- `cluster_autoscaler_failed_scale_ups_total`
+- `cluster_autoscaler_scale_down_in_cooldown`
+- `cluster_autoscaler_scaled_up_nodes_total`
+- `cluster_autoscaler_unneeded_nodes_count`
+- `cluster_autoscaler_unschedulable_pods_count`
+- `cluster_autoscaler_nodes_count`
+- `cloudprovider_azure_api_request_errors`
+- `cloudprovider_azure_api_request_duration_seconds_bucket`
+- `cloudprovider_azure_api_request_duration_seconds_count`
+
+> [!NOTE]
+> The CPU and memory usage metrics for all control-plane targets are not exposed irrespective of the profile.
+
+## References
+
+- [Kubernetes Upstream metrics list][kubernetes-metrics-instrumentation-reference]
+
+- [Cluster autoscaler metrics list][kubernetes-metrics-autoscaler-reference]
+
+## Next steps
+
+- [Learn more about control plane metrics in Managed Prometheus](monitor-control-plane-metrics.md)
+
+<!-- EXTERNAL LINKS -->
+[ama-metrics-settings-configmap-github]: https://github.com/Azure/prometheus-collector/blob/89e865a73601c0798410016e9beb323f1ecba335/otelcollector/configmaps/ama-metrics-settings-configmap.yaml
+[kubernetes-metrics-instrumentation-reference]: https://kubernetes.io/docs/reference/instrumentation/metrics/
+(https://github.com/kubernetes/autoscaler/blob/master/cluster-autoscaler/proposals/metrics.md)
+[kubernetes-metrics-autoscaler-reference]: https://github.com/kubernetes/autoscaler/blob/master/cluster-autoscaler/proposals/metrics.md
+
+<!-- INTERNAL LINKS -->
+[azure-monitor-prometheus-metrics-scrape-config-minimal]: ../azure-monitor/containers/prometheus-metrics-scrape-configuration-minimal.md