Merge pull request #7271 from vplauzon/vpl/preview-ingestion-api

Add preview for ingestion APIs

Author: prmerger-automator[bot]

data-explorer/kusto/management/data-ingestion/queued-ingest-configuration-http.md

@@ -3,10 +3,10 @@ title: Queued Ingestion Configuration via REST API
 description: Learn how to use the REST API to retrieve ingestion configuration settings for Azure Data Explorer.
 ms.reviewer: 
 ms.topic: reference
-ms.date: 10/20/2025
+ms.date: 12/11/2025
 ---
 
-# Ingestion configuration via REST API
+# Ingestion configuration via REST API (Preview)
 
 The ingestion configuration REST API allows you to programmatically retrieve configuration settings for data ingestion, including storage container URIs, Lake folder paths from the Microsoft Fabric offering, and ingestion limits. This endpoint enables integration with the Data Management storage resources used for ingestion.
 

data-explorer/kusto/management/data-ingestion/queued-ingest-status-http.md

@@ -3,10 +3,10 @@ title: Queued Ingestion Status via REST API
 description: Learn how to use the REST API to check the status of queued ingestion operations in Azure Data Explorer.
 ms.reviewer: 
 ms.topic: reference
-ms.date: 10/28/2025
+ms.date: 12/11/2025
 ---
 
-# Ingestion status via REST API
+# Ingestion status via REST API (Preview)
 
 The ingestion status REST API allows you to monitor the progress and results of queued ingestion operations. This endpoint provides detailed information about each blob in an ingestion request, including success, failure, or in-progress status.
 

data-explorer/kusto/management/data-ingestion/queued-ingest-use-http.md

@@ -3,10 +3,10 @@ title: Queued Ingestion via REST API
 description: Learn how to use the REST API to submit blobs for ingestion into Azure Data Explorer tables.
 ms.reviewer: 
 ms.topic: reference
-ms.date: 10/28/2025
+ms.date: 12/11/2025
 ---
 
-# Queued ingestion via REST API
+# Queued ingestion via REST API (Preview)
 
 The queued ingestion REST API allows you to programmatically submit one or more blobs for ingestion into a specified database and table. This method is ideal for automated workflows and external systems that need to trigger ingestion dynamically.