Merge pull request #2410 from MicrosoftDocs/main638983951558048173sync_temp

For protected branch, push strategy should use PR and merge to target branch method to work around git push error

Author: learn-build-service-prod[bot]

docs/data-engineering/api-livy-overview.md

@@ -1,22 +1,20 @@
 ---
 title: Livy API overview
 description: Learn about the Microsoft Fabric Livy API for submitting jobs to Spark
-ms.reviewer: sngun
+ms.reviewer: avinandac
 ms.author: eur
 author: eric-urban
 ms.topic: overview
 ms.search.form: Livy API Overview for Data Engineering
-ms.date: 11/19/2024
+ms.date: 11/05/2025
 ---
 
-# What is the Livy API for Data Engineering? (Preview)
+# What is the Livy API for Data Engineering? 
 
 **Applies to:** [!INCLUDE[fabric-de-and-ds](includes/fabric-de-ds.md)]
 
 Microsoft Fabric Livy API lets users submit and execute Spark code within Spark compute associated with a Fabric Lakehouse, eliminating the need to create any Notebook or Spark Job Definition artifacts. This integration with the Lakehouse ensures straightforward access to data stored on OneLake.
 
-[!INCLUDE [preview-note](../includes/feature-preview-note.md)]
-
 ## Features
 
 The Fabric Livy API allows submitting jobs in two different modes:
@@ -30,7 +28,9 @@ The Fabric Livy API allows submitting jobs in two different modes:
 
 ## Get started with the Livy API
 
-Learn how to [Create and run Spark jobs using the Livy API in Fabric](get-started-api-livy.md) by choosing either a [Submit Spark session jobs using the Livy API](get-started-api-livy-session.md) or a [Submit Spark batch jobs using the Livy API](get-started-api-livy-batch.md).
+Learn how to [Create and run Spark jobs using the Livy API in Fabric](get-started-api-livy.md):
+- [Submit Spark session jobs using the Livy API](get-started-api-livy-session.md)
+- [Submit Spark batch jobs using the Livy API](get-started-api-livy-batch.md).
 
 ## Related content
 

docs/data-engineering/get-started-api-livy-batch.md

@@ -1,12 +1,12 @@
 ---
 title: Create and run Spark Session jobs using the Livy API
 description: Learn how to submit and run Spark session jobs in Fabric using the Livy API.
-ms.reviewer: sngun
+ms.reviewer: avinandac
 ms.author: eur
 author: eric-urban
 ms.topic: conceptual
 ms.search.form: Get started with the Livy API for Data Engineering
-ms.date: 04/30/2025
+ms.date: 11/05/2025
 ---
 
 # Use the Livy API to submit and execute Spark session jobs with user credentials
@@ -15,8 +15,6 @@ ms.date: 04/30/2025
 
 Get started with Livy API for Fabric Data Engineering by creating a Lakehouse; authenticating with a Microsoft Entra token; discover the Livy API endpoint; submit either batch or session jobs from a remote client to Fabric Spark compute; and monitor the results.
 
-[!INCLUDE [preview-note](../includes/feature-preview-note.md)]
-
 ## Prerequisites
 
 * Fabric Premium or Trial capacity with a LakeHouse

docs/data-engineering/get-started-api-livy-session.md

@@ -1,21 +1,18 @@
 ---
-title: Create and Manage a Warehouse Snapshot (Preview)
+title: Create and Manage a Warehouse Snapshot
 description: Learn how to create, use, and manage warehouse snapshots in Fabric Data Warehouse.
 author: WilliamDAssafMSFT
 ms.author: wiassaf
 ms.reviewer: twcyril
-ms.date: 05/08/2025
+ms.date: 11/10/2025
 ms.service: fabric
 ms.topic: how-to
 ms.search.form: Manage warehouse snapshots
 ---
-# Create and manage a warehouse snapshot (preview)
+# Create and manage a warehouse snapshot
 
 This article includes steps to create and manage warehouse snapshots using the Fabric portal, T-SQL queries, or the [Fabric API](/rest/api/fabric/articles/).
 
-> [!NOTE]
-> Warehouse snapshots are currently a [preview feature](../fundamentals/preview.md).
-
 ## Prerequisites
 
 - A Fabric workspace with an active capacity or trial capacity.
@@ -124,6 +121,8 @@ The `ALTER DATABASE` SQL statement uses the system time of the warehouse as the
    SET TIMESTAMP = '2025-04-27T18:10:00.00';
    ```
 
+Warehouse snapshots can also be updated via the Fabric portal. In the ribbon, under **Management**, select **Manage warehouse snapshot**.
+
 ## Rename
 
 You can rename a warehouse snapshot item via REST API and in the Fabric portal.

docs/data-engineering/get-started-api-livy.md

@@ -1,23 +1,20 @@
 ---
-title: Warehouse Snapshots (Preview)
+title: Warehouse Snapshots
 description: Learn about warehouse snapshots in Fabric Data Warehouse.
 author: WilliamDAssafMSFT
 ms.author: wiassaf
 ms.reviewer: twcyril
-ms.date: 05/09/2025
+ms.date: 11/10/2025
 ms.service: fabric
 ms.topic: conceptual
 ms.search.form: Warehouse snapshot overview
 ---
-# Warehouse snapshots (preview)
+# Warehouse snapshots
 
 **Applies to:** [!INCLUDE [fabric-dw](includes/applies-to-version/fabric-dw.md)]
 
 A warehouse snapshot is a read-only representation of a warehouse item at a specific point in time, retained to up to 30 days. To get started, [create a warehouse snapshot](create-manage-warehouse-snapshot.md).
 
-> [!NOTE]
-> Warehouse snapshots are currently a [preview feature](../fundamentals/preview.md).
-
 Warehouse snapshots can be seamlessly "rolled forward" on demand, allowing consumers to connect to the same snapshot or use a consistent warehouse connection string to access a past version of the data. When the snapshot timestamp is rolled forward, updates are applied immediately, as if in a single, atomic transaction. Warehouse snapshot ensures that data engineers can provide analytical users with a consistent dataset, even as real-time updates occur. Analysts can run `SELECT` queries based on the snapshot without any ETL interference.
 
 A snapshot can be useful in scenarios where an ETL process might have created data corruption. This read only child item provides stability and consistency for data that could otherwise be modified by some ETL processes.
@@ -72,10 +69,8 @@ When a T-SQL query is run, information about the current version of the data bei
 - Warehouse snapshots don't exist without the source warehouse. When the warehouse is deleted, all snapshots are deleted. Warehouse snapshots must be recreated if the warehouse is restored.
 - Warehouse snapshots are valid for up to 30 days in the past. Snapshot datetime can be set to any date in the past up to 30 days or database creation time (whichever is later).
 
-## Limitations
+## Remarks
 
-- Warehouse snapshots can only be created against new warehouse items created after March 2025.
-- Warehouse snapshots don't appear in SSMS Object Explorer but do show up in the database selection dropdown list.
 - Modified tables, views, and stored procedures after the snapshot timestamp become invalid in the snapshot.
 - Warehouse snapshots require Direct Query or Import mode in Power BI, and don't support [Direct Lake](../fundamentals/direct-lake-overview.md) mode.
 - Warehouse snapshots aren't supported on the SQL analytics endpoint of the Lakehouse.
@@ -89,4 +84,4 @@ When a T-SQL query is run, information about the current version of the data bei
 ## Related content
 
 - [Query data as it existed in the past](time-travel.md)
-- [Create a sample Warehouse in Microsoft Fabric](create-warehouse-sample.md)
+- [Create a sample Warehouse in Microsoft Fabric](create-warehouse-sample.md)

docs/data-warehouse/create-manage-warehouse-snapshot.md

@@ -4,7 +4,7 @@ description: Learn about the new features and documentation improvements for Mic
 author: WilliamDAssafMSFT
 ms.author: wiassaf
 ms.reviewer: sngun
-ms.date: 11/06/2025
+ms.date: 11/10/2025
 ms.update-cycle: 30-days
 ms.topic: whats-new
 ms.collection:
@@ -133,7 +133,6 @@ The following table lists the features of Microsoft Fabric that are currently in
 |**Tabbed navigation for multitasking and other UI improvements** |Fabric now supports tabs to open multiple items and easily switch between them. It offers an object explorer that lets you browse and open items across all your open workspaces. To learn more, see [tabbed navigation in Fabric portal](./fabric-home.md#multitask-with-tabs-and-object-explorer) and [New Multitasking Features coming to Fabric (Preview)](https://blog.fabric.microsoft.com/blog/supercharge-your-workflow-new-multitasking-features-coming-to-fabric?ft=All).|
 |**Upsert to delta table with Lakehouse connector (Preview)**|We've added upsert support to the Lakehouse connector, allowing direct writes to Delta tables, in both Copy job and Copy activity within Pipeline. For more information, see [Configure Lakehouse in a copy activity](../data-factory/connector-lakehouse-copy-activity.md#destination).|
 |**varchar(max) and varbinary(max) support in preview**|Support for the **varchar(max)** and **varbinary(max)** [data types](../data-warehouse/data-types.md) in Fabric Data Warehouse is now in preview. For more information, see [Announcing public preview of VARCHAR(MAX) and VARBINARY(MAX) types in Fabric Data Warehouse](https://blog.fabric.microsoft.com/blog/announcing-public-preview-of-varcharmax-and-varbinarymax-types-in-fabric-datawarehouse/).|
-|**Warehouse snapshots (preview)**| [Warehouse snapshots](https://blog.fabric.microsoft.com/blog/warehouse-snapshots-in-microsoft-fabric-public-preview?ft=All) are a point-in-time, read-only representation of your data warehouse. You can create a [snapshot of your warehouse](../data-warehouse/warehouse-snapshot.md) at any point in the past 30 days, connect to it and query it just like a warehouse, and "roll forward" your snapshot regularly. To get started, see [Create and manage a warehouse snapshot](../data-warehouse/create-manage-warehouse-snapshot.md). |
 |**Warehouse source control (preview)**|Using [Source control with Warehouse (preview)](../data-warehouse/source-control.md), you can manage development and deployment of versioned warehouse objects. You can use [SQL Database Projects extension](/sql/azure-data-studio/extensions/sql-database-project-extension) available inside of [Azure Data Studio](/sql/azure-data-studio/download-azure-data-studio) and [Visual Studio Code](https://visualstudio.microsoft.com/downloads/). For more information on warehouse source control, see [CI/CD with Warehouses in Microsoft Fabric](https://blog.fabric.microsoft.com/blog/ci-cd-with-warehouses-in-microsoft-fabric/).|
 |**Warehouse SQL Audit Logs**|[SQL Audit Logs](../data-warehouse/sql-audit-logs.md) in Fabric Data Warehouse provide a comprehensive and immutable record of all database activities, capturing critical details such as the event timestamp, the user or process that triggered the action, and the executed T-SQL statements. For more information, see [Introducing SQL Audit Logs for Fabric Data Warehouse](https://blog.fabric.microsoft.com/blog/introducing-sql-audit-logs-for-fabric-datawarehouse?ft=All).|
 |**Workspace-level workload assignment (Preview)**|[Workspace admins can now add additional workloads directly to their workspaces](https://blog.fabric.microsoft.com/blog/new-in-microsoft-fabric-empowering-workspace-admins-with-direct-workload-assignment?ft=All), eliminating the need for tenant or capacity-level setup. In the [Workloads Hub](https://app.fabric.microsoft.com/workloadhub), admins can [add workloads directly to a workspace](../workload-development-kit/more-workloads-add.md).|
@@ -145,6 +144,7 @@ The following table lists the features of Microsoft Fabric that have recently tr
 
 |**Month** | **Feature** | **Learn more** |
 |:-- |:-- | :-- |
+|November 2025|**Warehouse snapshots**| [Warehouse snapshots](https://blog.fabric.microsoft.com/blog/warehouse-snapshots-in-microsoft-fabric-freeze-data-unlock-reliable-reporting/), now generally available, are a point-in-time, read-only representation of your data warehouse. You can create a [snapshot of your warehouse](../data-warehouse/warehouse-snapshot.md) at any point in the past 30 days, connect to it and query it just like a warehouse, and "roll forward" your snapshot regularly. To get started, see [Create and manage a warehouse snapshot](../data-warehouse/create-manage-warehouse-snapshot.md). |
 |November 2025|**ArcGIS GeoAnalytics for Microsoft Fabric Spark (Generally Available)**|[ArcGIS GeoAnalytics for Microsoft Fabric Spark (Generally Available)](https://blog.fabric.microsoft.com/blog/arcgis-geoanalytics-for-microsoft-fabric-spark-generally-available?ft=All), now generally available, brings spatial analytics to Fabric Spark. For more information, see [ArcGIS GeoAnalytics for Microsoft Fabric](../data-engineering/spark-arcgis-geoanalytics.md).|
 |October 2025|**Query and ingest JSONL files (Generally Available)**|You can [query and ingest JSONL files in a warehouse or a SQL analytics endpoint](https://blog.fabric.microsoft.com/blog/query-and-ingest-jsonl-files-in-data-warehouse-and-sql-endpoint-for-lakehouse-general-availability?ft=All), now generally available. [OPENROWSET(BULK)](/sql/t-sql/functions/openrowset-bulk-transact-sql?view=fabric&preserve-view=true) enables scalable reading and ingestion of JSONL files. |
 |October 2025|**Outbound Access Protection for Warehouse, SQL analytics endpoint**|[Outbound Access Protection (OAP)](https://blog.fabric.microsoft.com/blog/extending-outbound-access-protection-to-fabric-warehouse-and-sql-analytics-endpoint?ft=All) now applies to Fabric Warehouse (in Preview) and SQL analytics endpoint (GA) items, enforcing workspace-level rules for outbound connections. This strengthens governance, reduces risk, and ensures only trusted sources are used for data loads and queries. For more information, see [Workspace outbound access protection](../security/workspace-outbound-access-protection-overview.md).|
@@ -432,6 +432,7 @@ This section summarizes recent improvements and features for [Fabric Data Wareho
 
 |**Month** | **Feature** | **Learn more** |
 |:-- |:-- | :-- |
+|November 2025|**Warehouse snapshots**| [Warehouse snapshots](https://blog.fabric.microsoft.com/blog/warehouse-snapshots-in-microsoft-fabric-freeze-data-unlock-reliable-reporting/), now generally available, are a point-in-time, read-only representation of your data warehouse. You can create a [snapshot of your warehouse](../data-warehouse/warehouse-snapshot.md) at any point in the past 30 days, connect to it and query it just like a warehouse, and "roll forward" your snapshot regularly. To get started, see [Create and manage a warehouse snapshot](../data-warehouse/create-manage-warehouse-snapshot.md). |
 |November 2025|**Default Semantic Models retirement**|[!INCLUDE [default-semantic-model-retirement](../includes/default-semantic-model-retirement.md)] |
 |October 2025|**SSMS 22 + Fabric Data Warehouse**|The new [SSMS 22 Preview adds improved Fabric Data Warehouse integration](https://blog.fabric.microsoft.com/blog/ssms-22-meets-fabric-data-warehouse-evolving-the-developer-experiences?ft=All) with workspace-based connection names, schema-based object grouping, warehouse snapshots support, and context-aware menus.|
 |October 2025|**Query and ingest JSONL files (Generally Available)**|You can [query and ingest JSONL files in a warehouse or a SQL analytics endpoint](https://blog.fabric.microsoft.com/blog/query-and-ingest-jsonl-files-in-data-warehouse-and-sql-endpoint-for-lakehouse-general-availability?ft=All), now generally available. [OPENROWSET(BULK)](/sql/t-sql/functions/openrowset-bulk-transact-sql?view=fabric&preserve-view=true) enables scalable reading and ingestion of JSONL files. |