Merge pull request #1866 from MicrosoftDocs/main638845456695992383sync_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/admin/region-availability.md

@@ -61,6 +61,8 @@ This table lists regions where the only available Fabric workload is Power BI.
 |                | Norway West   | UAE Central    |                   | Korea South  |
 |                | Spain Central |                |                   |              |
 
+** Copilot is not supported for regions listed in this section. 
+
 ### Public preview
 
 This table lists regions where public preview features are available, according to workload.

docs/data-engineering/fabric-notebook-selection-guide.md

@@ -35,7 +35,7 @@ Use this high-level reference to quickly determine the most suitable notebook ty
 
 Use this structured comparison table to understand the architectural and operational trade-offs between notebook types. Best suited for engineering evaluations or implementation planning. 
 
-**Execution & Performance**
+### **Execution & Performance**
 
 | Scenario | Python Notebooks (2-core VM) | PySpark Notebooks (Spark Compute) |
 | --- | --- | --- |
@@ -46,27 +46,27 @@ Use this structured comparison table to understand the architectural and operati
 | High-Concurrency Execution | Manual FIFO-style parallelism per notebook | System-managed concurrency with support for parallel execution. |
 | Resource Customization & Scaling | Fixed compute (2-core VM); does not auto scale. Users can manually scale out using %%config within the notebook. | Flexible resource allocation; supports autoscaling and custom Spark configurations. |
 
-**Workflow & Orchestration**
+### **Workflow & Orchestration**
 
 | Scenario | Python Notebooks (2-core VM) | PySpark Notebooks (Spark Compute) |
 | --- | --- | --- |
 | API Orchestration | Effective for lightweight orchestration and control flows, especially REST/gRPC-based integrations | Less optimal for basic orchestration tasks due to longer start-up and distributed overhead. |
 | Complex ETL DAGs | Supports FIFO scheduling only | Supports both FAIR and FIFO scheduling with DAG customization. |
 
-**Platform & Library Support**
+### **Platform & Library Support**
 
 | Scenario | Python Notebooks (2-core VM) | PySpark Notebooks (Spark Compute) |
 | --- | --- | --- |
 |  Library Access | Strong Python library support across multiple runtimes; however, limited access to Spark-native libraries may require manual integration. | Fully supports MLlib, Spark SQL, PySpark, and Spark Streaming. |
 | Delta Lake Handling | The Python Notebook runtime comes with pre-installed [deltas](https://delta-io.github.io/delta-rs/) and [duckdb](https://duckdb.org/) libraries, enabling both reading and writing of Delta Lake data. However, some Delta Lake features may still be unsupported. | Fully supported with native compatibility. |
 
-**Production & Enterprise Readiness**
+### **Production & Enterprise Readiness**
 
 | Scenario | Python Notebooks (2-core VM) | PySpark Notebooks (Spark Compute) |
 | --- | --- | --- |
 | Production Management | Limited production features; Does not support environment vars. | Support for production workflows with environment variables, library management through environment items, and item-based deployment. |
 
-**Cost Considerations**
+### **Cost Considerations**
 
 | Scenario | Python Notebooks (2-core VM) | PySpark Notebooks (Spark Compute) |
 | --- | --- | --- |
@@ -80,15 +80,15 @@ Use **Python Notebooks** for fast iteration, cost-effective analysis, and intera
 
 Use **PySpark Notebooks** for distributed computing, production-grade ETL workflows, or scenarios where high concurrency and Spark-native APIs are essential. 
 
-**Choose Python Notebooks When:**
+### **Choose Python Notebooks When:**
 
 - You need fast start-up (typically within seconds) on a lightweight 2-core container. 
 - If minimizing compute cost is a priority - for interactive analysis or scheduled micro-jobs. 
 - You want immediate access to pip-installable libraries and pre-installed DuckDB and Polars. 
 - You need to test across different Python runtime versions. 
 - Your data comfortably fits in the memory of a single node. 
 
-**Choose PySpark Notebooks When:**
+### **Choose PySpark Notebooks When:**
 
 - Your workloads exceed the memory or compute limits of a single node. 
 - You require high-concurrency pools to run parallel jobs across Notebooks. 
@@ -109,8 +109,6 @@ This section provides a quick reference for the fundamental technical and archit
 | Cost Profile | Lower cost; ideal for short tasks and prototyping | Higher cost; suited for scalable, long-running workloads |
 | Python/Spark Versioning | Multiple Python versions available | Tied to specific Spark runtime version |
 | Custom Libraries | pip install + resource folders | pip install + resource folders + environments item |
-| ~~Environment Variables~~ | ~~Not supported~~ | ~~Supported~~ |
-| ~~Lakehouse Integration~~ | ~~Requires Lakehouse to be explicitly attached~~ | ~~Can read/write without attachment~~ |
 | Fabric Spark Capabilities | Limited access to Spark engine features | Full access: NEE, Autotune, VORDER, Vegas Cache |
 | Delta Lake Compatibility | Partially compatible; potential performance issues | Fully supported and optimized |
 

docs/data-engineering/runtime.md

@@ -32,7 +32,7 @@ Below, you find a comprehensive comparison of key components, including Apache S
 
 |                       | **[Runtime 1.1](./runtime-1-1.md)** | **[Runtime 1.2](./runtime-1-2.md)** | **[Runtime 1.3](./runtime-1-3.md)** |
 |-----------------------|-------------------------------------|-------------------------------------|------------------------------------|
-| **Release Stage**     | EOSA                                | GA                                  | GA                                 |
+| **Release Stage**     | EOS                                    | EOSA| GA                                 |
 | **Apache Spark**      | 3.3.1                               | 3.4.1                               | 3.5.0                              |
 | **Operating System**  | Ubuntu 18.04                        | Mariner 2.0                         | Mariner 2.0                        |
 | **Java**              | 8                                   | 11                                  | 11                                 |

docs/data-factory/index.yml

@@ -11,110 +11,108 @@ metadata:
   ms.topic: landing-page # Required
   author: whhender #Required; your GitHub user alias, with correct capitalization.
   ms.author: whhender #Required; microsoft alias of author; optional team alias.
-  ms.date: 9/17/2024 #Required; mm/dd/yyyy format.
+  ms.date: 6/02/2025 #Required; mm/dd/yyyy format.
 # linkListType: architecture | concept | deploy | download | get-started | how-to-guide | tutorial | overview | quickstart | reference | sample | tutorial | video | whats-new
 
 landingContent:
 # Cards and links should be based on top customer tasks or top subjects
 # Start card title with a verb
   # Card 
-  - title: About Data Factory
+  - title: What is Data Factory?
     linkLists:
       - linkListType: overview
         links:
           - text: What is Data Factory?
             url: data-factory-overview.md
-          - text: Connector overview
-            url: connector-overview.md
+          - text: Data Factory demo
+            url: https://aka.ms/DataFactoryLab
           - text: What's new in Data Factory?
             url: whats-new.md
-
-  # Card 
-  - title: Using Data Factory
-    linkLists:
-      - linkListType: get-started
-        links:
-          - text: Create your first dataflow
-            url: create-first-dataflow-gen2.md
-          - text: Create your first data pipeline
-            url: create-first-pipeline-with-sample-data.md
-          - text: Move and transform data
-            url: transform-data.md
-          - text: Migrate to Data Factory
-            url: upgrade-paths.md
+          - text: What can I connect to?
+            url: connector-overview.md
           - text: Pricing in Data Factory
             url: pricing-overview.md
-      - linkListType: tutorial
-        links:
-          - text: Create an end-to-end data integration scenario
-            url: tutorial-end-to-end-introduction.md
+          - text: Migrate to Data Factory in Fabric
+            url: upgrade-paths.md
       - linkListType: learn
         links:
           - text: Data Factory training
             url: /training/browse/?terms=data%20factory%20fabric
-  
-  # Card 
-  - title: Working with data pipelines
+  # Card
+  - title: Connect to your data
     linkLists:
-      - linkListType: how-to-guide
+      - linkListType: get-started
         links:
-          - text: Data pipeline runs
-            url: pipeline-runs.md
-          - text: Copy data - copy activity
-            url: copy-data-activity.md
-          - text: Monitor data pipeline runs
-            url: monitor-pipeline-runs.md
-          - text: Activity Overview
-            url: activity-overview.md
-          - text: Move data with copy assistant
-            url: tutorial-move-data-lakehouse-copy-assistant.md
-          - text: Migrate from Dataflow Gen1 to Dataflow Gen2
-            url: dataflow-gen2-migrate-from-dataflow-gen1.md
+        - text: Dataflow Gen2 connectors
+          url: dataflow-support.md
+        - text: Data pipeline connectors
+          url: pipeline-support.md
 
   # Card
-  - title: Data gateway
+  - title: Connect on-premises to the cloud
     linkLists:
       - linkListType: how-to-guide
         links:
+        - text: How to access on-premises data
+          url: how-to-access-on-premises-data.md
         - text: What is an on-premises data gateway?
           url: /data-integration/gateway/service-gateway-onprem?toc=/fabric/data-factory/toc.json
-        - text: On-premises data gateway FAQ
-          url: /data-integration/gateway/service-gateway-onprem-faq?toc=/fabric/data-factory/toc.json 
         - text: What is a virtual network data gateway?
           url: /data-integration/vnet/overview?toc=/fabric/data-factory/toc.json 
-        - text: Virtual network data gateway FAQ
-          url: /data-integration/vnet/data-gateway-faqs?toc=/fabric/data-factory/toc.json 
 
   # Card 
-  - title: Working with dataflows
+  - title: Transform data
     linkLists:
       - linkListType: how-to-guide
         links:
-          - text: Data source management
+          - text: Create your first dataflow
+            url: create-first-dataflow-gen2.md
+          - text: Connect your source to your dataflow
             url: data-source-management.md
-          - text: Monitor your dataflows
-            url: dataflows-gen2-monitor.md
           - text: Save a draft of your dataflow
             url: dataflows-gen2-save-draft.md
 
-  # Card
-  - title: FAQs
+  # Card 
+  - title: Move data
     linkLists:
       - linkListType: get-started
         links:
-        - text: Frequently asked questions
-          url: frequently-asked-questions.yml
+          - text: Create your first data pipeline
+            url: create-first-pipeline-with-sample-data.md
+          - text: Move and transform data
+            url: transform-data.md
+      - linkListType: how-to-guide
+        links:
+          - text: Data pipeline runs
+            url: pipeline-runs.md
+          - text: Copy activity in data pipelines
+            url: copy-data-activity.md
+          - text: Copy job
+            url: copy-job.md
+      - linkListType: tutorial
+        links:
+          - text: Create an end-to-end data integration scenario
+            url: tutorial-end-to-end-introduction.md
+          - text: Move data with copy assistant
+            url: tutorial-move-data-lakehouse-copy-assistant.md
 
-  # Card
-  - title: Connectors
+  # Card 
+  - title: Manage your pipelines
     linkLists:
-      - linkListType: get-started
+      - linkListType: concept
         links:
-        - text: Dataflow Gen2 connectors
-          url: dataflow-support.md
-        - text: Data pipeline connectors
-          url: pipeline-support.md
+          - text: Schedule pipelines
+            url: pipeline-runs.md#scheduled-data-pipeline-runs
+          - text: Orchestrate with Apache Airflow
+            url: apache-airflow-jobs-concepts.md
       - linkListType: how-to-guide
         links:
-        - text: Connector certification
-          url: connector-certification.md
+          - text: Start a pipeline from a storage event
+            url: pipeline-storage-event-triggers.md
+          - text: Monitor your pipelines
+            url: monitor-pipeline-runs.md
+      - linkListType: tutorial
+        links:
+          - text: Run Fabric pipelines with Apache Airflow
+            url: apache-airflow-jobs-run-fabric-item-job.md
+