Merge pull request #262646 from MicrosoftDocs/main

Publish to live, Monday 4 AM PST, 1/8

Author: ttorble

articles/app-service/toc.yml

@@ -497,8 +497,6 @@
           href: /troubleshoot/azure/app-service/backing-up-restoring-and-cloning-microsoft-azure-app-services?toc=/azure/app-service/toc.json
         - name: Built-in Linux containers FAQs
           href: /troubleshoot/azure/app-service/faqs-app-service-linux?toc=/azure/app-service/toc.json
-        - name: Configuration and management FAQs for Web Apps
-          href: /troubleshoot/azure/app-service/web-apps-configuration-and-management-faqs?toc=/azure/app-service/toc.json
         - name: Deployment FAQs for Web Apps
           href: /troubleshoot/azure/app-service/web-apps-deployment-faqs?toc=/azure/app-service/toc.json
         - name: FAQs about scaling web apps

articles/azure-arc/kubernetes/tutorial-gitops-flux2-ci-cd.md

@@ -245,7 +245,6 @@ For the details on installation, refer to the [GitOps Connector](https://github.
 
 | Variable | Value |
 | -------- | ----- |
-| AZ_ACR_NAME | (your Azure Container Registry instance, for example. azurearctest.azurecr.io) |
 | AZURE_SUBSCRIPTION | (your Azure Service Connection, which should be **arc-demo-acr** from earlier in the tutorial) |
 | AZ_ACR_NAME | Azure ACR name, for example arc-demo-acr |
 | ENVIRONMENT_NAME | Dev |

articles/azure-functions/migrate-dotnet-to-isolated-model.md

@@ -33,9 +33,9 @@ $AppInfo = @{}
 
 foreach ($App in $FunctionApps)
 {
-     if ($App.ApplicationSettings["FUNCTIONS_WORKER_RUNTIME"] -eq 'dotnet')
+     if ($App.Runtime -eq 'dotnet')
      {
-          $AppInfo.Add($App.Name, $App.ApplicationSettings["FUNCTIONS_WORKER_RUNTIME"])
+          $AppInfo.Add($App.Name, $App.Runtime)
      }
 }
 

articles/azure-monitor/essentials/data-collection-rule-best-practices.md

@@ -2,7 +2,7 @@
 title: Best practices for data collection rule creation and management in Azure Monitor
 description: Details on the best practices to be followed to correctly create and maintain data collection rule in Azure Monitor.
 ms.topic: conceptual
-ms.date: 12/14/2022
+ms.date: 01/08/2024
 ms.reviewer: brunoga
 
 ---

articles/azure-monitor/essentials/prometheus-grafana.md

@@ -3,7 +3,7 @@ title: Use Azure Monitor managed service for Prometheus as data source for Grafa
 description: Details on how to configure Azure Monitor managed service for Prometheus as data source for both Azure Managed Grafana and self-hosted Grafana in an Azure virtual machine.
 author: bwren 
 ms.topic: conceptual
-ms.date: 09/28/2022
+ms.date: 01/08/2024
 ---
 
 # Use Azure Monitor managed service for Prometheus as data source for Grafana using managed system identity 

articles/azure-monitor/essentials/prometheus-rule-groups.md

@@ -5,7 +5,7 @@ author: EdB-MSFT
 ms-author: edbaynash
 ms.topic: conceptual
 ms.custom: ignite-2022
-ms.date: 09/28/2022
+ms.date: 11/09/2023
 ---
 
 # Azure Monitor managed service for Prometheus rule groups

articles/backup/backup-azure-database-postgresql-support-matrix.md

@@ -15,9 +15,7 @@ You can use [Azure Backup](./backup-overview.md) to protect Azure Database for P
 
 ## Supported regions
 
-Azure Database for PostgreSQL server backup is available in the following regions:
-
-East US, East US 2, Central US, South Central US, West US, West US 2, West Central US, Brazil South, Canada Central, North Europe, West Europe, UK South, UK West, Germany West Central, Switzerland North, Switzerland West, East Asia, Southeast Asia, Japan East, Japan West, Korea Central, Korea South, India Central, Australia East, Australia Central, Australia Central 2, UAE North
+Azure Database for PostgreSQL server backup is available in all regions, except for Germany Central (Sovereign), Germany Northeast (Sovereign) and China regions.
 
 ## Support scenarios
 

articles/cosmos-db/concepts-limits.md

@@ -50,31 +50,59 @@ The actual minimum RU/s may vary depending on your account configuration. You ca
 
 #### Minimum throughput on container
 
-To estimate the minimum throughput required of a container with manual throughput, find the maximum of:
+**Manual throughput**
+
+To estimate the minimum RU/s required of a container with manual throughput, find the maximum of:
 
 * 400 RU/s 
 * Current storage in GB * 1 RU/s
 * Highest RU/s ever provisioned on the container / 100
 
 For example, you have a container provisioned with 400 RU/s and 0-GB storage. You increase the throughput to 50,000 RU/s and import 20 GB of data. The minimum RU/s is now `MAX(400, 20 * 1 RU/s per GB, 50,000 RU/s / 100)` = 500 RU/s. Over time, the storage grows to 2000 GB. The minimum RU/s is now `MAX(400, 2000 * 1 RU/s per GB, 50,000 / 100)` = 2000 RU/s.
 
+**Autoscale throughput**
+
+To estimate the minimum autoscale max RU/s required of a container with autoscale throughput, find the maximum of:
+
+* 1000 RU/s 
+* Current storage in GB * 10 RU/s
+* Highest RU/s ever provisioned on the container / 10
+
+For example, you have a container provisioned with 1000 RU/s and 0-GB storage. You increase the throughput to 50,000 RU/s and import 20 GB of data. The minimum max RU/s is now `MAX(1000, 20 * 10 RU/s per GB, 50,000 RU/s / 10)` = 5000 RU/s. Over time, the storage grows to 2000 GB. The minimum max RU/s is now `MAX(1000, 2000 * 10 RU/s per GB, 50,000 / 10)` = 20,000 RU/s.
+
 #### Minimum throughput on shared throughput database
 
-To estimate the minimum throughput required of a shared throughput database with manual throughput, find the maximum of:
+**Manual throughput**
+
+To estimate the minimum RU/s required of a shared throughput database with manual throughput, find the maximum of:
 
 * 400 RU/s 
 * Current storage in GB * 1 RU/s
 * Highest RU/s ever provisioned on the database / 100
 * 400 + MAX(Container count - 25, 0) * 100 RU/s
 
-For example, you have a database provisioned with 400 RU/s, 15 GB of storage, and 10 containers. The minimum RU/s is `MAX(400, 15 * 1 RU/s per GB, 400 / 100, 400 + 0 )` = 400 RU/s. If there were 30 containers in the database, the minimum RU/s would be `400 + MAX(30 - 25, 0) * 100 RU/s` = 900 RU/s. 
+For example, you have a database provisioned with 400 RU/s, 15 GB of storage, and 10 containers. The minimum RU/s is `MAX(400, 15 * 1 RU/s per GB, 400 / 100, 400 + 0 )` = 400 RU/s. If there were 30 containers in the database, the minimum RU/s would be `400 + MAX(30 - 25, 0) * 100 RU/s` = 900 RU/s.
 
-In summary, here are the minimum provisioned RU limits when using manual throughput.
+**Autoscale throughput**
 
-| Resource | Limit |
-| --- | --- |
-| Minimum RUs per container ([dedicated throughput provisioned mode with manual throughput](./resource-model.md#azure-cosmos-db-containers)) | 400 |
-| Minimum RUs per database ([shared throughput provisioned mode with manual throughput](./resource-model.md#azure-cosmos-db-containers)) | 400 RU/s for first 25 containers. |
+To estimate the minimum autoscale max RU/s required of a shared throughput database with autoscale throughput, find the maximum of:
+
+* 1000 RU/s 
+* Current storage in GB * 10 RU/s
+* Highest RU/s ever provisioned on the database / 10
+* 1000 + MAX(Container count - 25, 0) * 1000 RU/s
+
+For example, you have a database provisioned with 1000 RU/s, 15 GB of storage, and 10 containers. The minimum max RU/s for autoscale database is `MAX(1000, 15 * 10 RU/s per GB, 1000 / 10, 1000 + 0 )` = 1000 RU/s. If there were 30 containers in the database, the minimum max RU/s would be `1000 + MAX(30 - 25, 0) * 1000 RU/s` = 5000 RU/s. 
+ 
+
+In summary, here are the minimum provisioned RU limits when using provisioned throughput.
+
+| Provisioning Type | Resource | Limit |
+| --- | --- | --- |
+| Manual throughput | Minimum RUs per container ([dedicated throughput provisioned mode with manual throughput](./set-throughput.md#set-throughput-on-a-container)) | 400 |
+| Manual throughput | Minimum RUs per database ([shared throughput provisioned mode with manual throughput](./set-throughput.md#set-throughput-on-a-database) | 400 RU/s for first 25 containers. |
+| Autoscale throughput | Minimum max RUs per container ([dedicated throughput provisioned mode with autoscale throughput](./provision-throughput-autoscale.md#how-autoscale-provisioned-throughput-works)) | 1000 |
+| Autoscale throughput | Minimum max RUs per database ([shared throughput provisioned mode with autoscale throughput](./provision-throughput-autoscale.md#how-autoscale-provisioned-throughput-works)) | 1000 RU/s for first 25 containers. |
 
 Azure Cosmos DB supports programmatic scaling of throughput (RU/s) per container or database via the SDKs or portal.
 

articles/cosmos-db/emulator-release-notes.md

@@ -15,23 +15,27 @@ ms.date: 09/11/2023
 The Azure Cosmos DB emulator is updated at a regular cadence with release notes provided in this article.
 
 > [!div class="nextstepaction"]
-> [Download latest version (``2.14.12``)](https://aka.ms/cosmosdb-emulator)
+> [Download latest version (``2.14.16``)](https://aka.ms/cosmosdb-emulator)
 
 ## Supported versions
 
 Only the most recent version of the Azure Cosmos DB emulator is actively supported.
 
-## Latest version ``2.14.12``
+## Latest version ``2.14.16``
 
-> *Released March 20, 2023*
+> *Released January 8, 2024*
 
-- This release fixes an issue impacting Gremlin and Table endpoint API types. Prior to this fix a client application fails with a 500 status code when trying to connect to the public emulator's endpoint.
+- This release fixes an issue which was causing emulator to bind with `loopback` instead of `public interface` even after passing /AllowNetworkAccess command line option.
 
 ## Previous releases
 
 > [!WARNING]
 > Previous versions of the emulator are not supported by the product group.
 
+### ``2.14.12`` (March 20, 2023)
+
+- This release fixes an issue impacting Gremlin and Table endpoint API types. Prior to this fix a client application fails with a 500 status code when trying to connect to the public emulator's endpoint.
+
 ### ``2.14.11`` (January 27, 2023)
 
 - This release updates the Azure Cosmos DB Emulator background services to match the latest online functionality of the Azure Cosmos DB.

articles/cosmos-db/nosql/how-to-delete-by-partition-key.md

@@ -46,8 +46,8 @@ Update your Azure Cosmos DB account to enable "Delete by partition key" feature
        $capabilities = ($cosmosdb | ConvertFrom-Json).capabilities 
     ```
 - Step 3: Add "Delete items by partition key" capability in the list of capabilities if it doesn't exist already. 
-    >!Note 
-    The list of capabilities must always specify all capabilities that you want to enable, inclusively. This includes capabilities that are already enabled for the account that you want to keep. 
+    > [!NOTE]
+    > The list of capabilities must always specify all capabilities that you want to enable, inclusively. This includes capabilities that are already enabled for the account that you want to keep. 
 
     ```azurecli-interactive
        $capabilities += $DeleteByPk