fixed merge conflict

Author: HeidiSteen

articles/connectors/connectors-sftp-ssh.md

@@ -6,7 +6,7 @@ ms.suite: integration
 author: divyaswarnkar
 ms.reviewer: estfan, logicappspm, azla
 ms.topic: conceptual
-ms.date: 08/05/2021
+ms.date: 01/12/2022
 tags: connectors
 ---
 
@@ -34,6 +34,8 @@ For differences between the SFTP-SSH connector and the SFTP connector, review th
   * MessageWay
   * OpenText Secure MFT
   * OpenText GXS
+  * Globalscape
+  * SFTP for Azure Blob Storage
 
 * SFTP-SSH actions that support [chunking](../logic-apps/logic-apps-handle-large-messages.md) can handle files up to 1 GB, while SFTP-SSH actions that don't support chunking can handle files up to 50 MB. The default chunk size is 15 MB. However, this size can dynamically change, starting from 5 MB and gradually increasing to the 50-MB maximum. Dynamic sizing is based on factors such as network latency, server response time, and so on.
 

articles/logic-apps/secure-single-tenant-workflow-virtual-network-private-endpoint.md

@@ -5,7 +5,7 @@ services: logic-apps
 ms.suite: integration
 ms.reviewer: estfan, azla
 ms.topic: how-to
-ms.date: 01/06/2022
+ms.date: 01/15/2022
 
 # As a developer, I want to connect to my single-tenant logic app workflows with virtual networks using private endpoints and VNet integration.
 ---
@@ -117,6 +117,12 @@ For more information, review [Create single-tenant logic app workflows in Azure
 
 To secure outbound traffic from your logic app, you can integrate your logic app with a virtual network. First, create and test an example workflow. You can then set up VNet integration.
 
+> [!IMPORTANT]
+> You can't change the subnet size after assignment, so use a subnet that's large enough to accommodate 
+> the scale that your app might reach. To avoid any issues with subnet capacity, use a `/26` subnet with 64 addresses. 
+> If you create the subnet for virtual network integration with the Azure portal, you must use `/27` as the minimum subnet size.
+
+
 ### Create and test the workflow
 
 1. If you haven't already, in the [Azure portal](https://portal.azure.com), create a single-tenant based logic app, and a blank workflow.
@@ -150,8 +156,9 @@ To secure outbound traffic from your logic app, you can integrate your logic app
 > [!IMPORTANT]
 > For the Azure Logic Apps runtime to work, you need to have an uninterrupted connection to the backend storage. 
 > For Azure-hosted managed connectors to work, you need to have an uninterrupted connection to the managed API service.
+> With VNet integration, you need to make sure no firewall or network security policy is blocking these connections. 
 
-### Considerations for outbound traffic through private endpoints
+### Considerations for outbound traffic through VNet integration
 
 Setting up virtual network integration affects only outbound traffic. To secure inbound traffic, which continues to use the App Service shared endpoint, review [Set up inbound traffic through private endpoints](#set-up-inbound).
 

articles/logic-apps/single-tenant-overview-compare.md

@@ -144,6 +144,22 @@ With the **Logic App (Standard)** resource type, you can create these workflow t
   > unavailable, or unsupported triggers, actions, and connectors, see 
   > [Changed, limited, unavailable, or unsupported capabilities](#limited-unavailable-unsupported).
 
+### Summary differences between stateful and stateless workflows
+
+<center>
+
+| Stateless                                                    | Stateful                                                    |
+|--------------------------------------------------------------|-------------------------------------------------------------|
+| Doesn't store run history, inputs, or outputs by default     | Stores run history, inputs, and outputs                     |
+| Managed connector triggers are unavailable or not allowed    | Managed connector triggers are available and allowed        |
+| No support for chunking                                      | Supports chunking                                           |
+| No support for asynchronous operations                       | Supports asynchronous operations                            |
+| Best for workflows with max duration under 5 minutes         | Edit default max run duration in host configuration         |
+| Best for handling small message sizes (under 64K)            | Handles large messages                                      |
+|||
+
+</center>
+
 <a name="nested-behavior"></a>
 
 ### Nested behavior differences between stateful and stateless workflows

articles/search/cognitive-search-concept-intro.md

@@ -15,7 +15,7 @@ ms.custom: references_regions
 
 In Azure Cognitive Search, AI enrichment refers to a pipeline process that adds machine learning to [indexer-based indexing](search-indexer-overview.md). Steps in the pipeline create new information where none previously existed: extracting information from images, detecting sentiment or key phrases from chunks of text, and recognizing entities, to name a few. All of these processes result in making previously unsearchable content available to full text search and knowledge mining scenarios.
 
-[**Azure Blob Storage**](../storage/blobs/storage-blobs-overview.md) is the most commonly used input, but any indexer-supported data source can provide the initial content. A [**skillset**](cognitive-search-working-with-skillsets.md), attached to an indexer, adds the AI processing. The indexer extracts content and sets up the pipeline, while the skillset identifies, analyzes, and creates new information out of blobs, images, and raw text. Output is a [**search index**](search-what-is-an-index.md) or optional [**knowledge store**](knowledge-store-concept-intro.md).
+[**Azure Blob Storage**](../storage/blobs/storage-blobs-overview.md)) is the most commonly used input, but any indexer-supported data source can provide the initial content. A [**skillset**](cognitive-search-working-with-skillsets.md), attached to an indexer, adds the AI processing. The indexer extracts content and sets up the pipeline, while AI processing identifies, analyzes, and creates new information out of blobs, images, and raw text. Output is a [**search index**](search-what-is-an-index.md) or optional [**knowledge store**](knowledge-store-concept-intro.md).
 
 ![Enrichment pipeline diagram](./media/cognitive-search-intro/cogsearch-architecture.png "enrichment pipeline overview")