Change title and rename file.

Author: Owen Duncan

articles/analysis-services/TOC.yml

@@ -39,8 +39,8 @@
     href: analysis-services-connect.md
   - name: High availability
     href: analysis-services-bcdr.md
-  - name: Understanding node movements
-    href: analysis-services-node-movement.md
+  - name: Long running operations
+    href: analysis-services-long-operations.md
   - name: Supported data sources
     href: analysis-services-datasource.md
 - name: How-to

articles/analysis-services/analysis-services-async-refresh.md

@@ -4,14 +4,14 @@ description: Describes how to use the Azure Analysis Services REST API to code a
 author: minewiskan
 ms.service: azure-analysis-services
 ms.topic: conceptual
-ms.date: 01/14/2020
+ms.date: 04/15/2020
 ms.author: owend
 ms.reviewer: minewiskan
 
 ---
 # Asynchronous refresh with the REST API
 
-By using any programming language that supports REST calls, you can  perform asynchronous data-refresh operations on your Azure Analysis Services tabular models. This includes synchronization of read-only replicas for query scale-out. 
+By using any programming language that supports REST calls, you can perform asynchronous data-refresh operations on your Azure Analysis Services tabular models. This includes synchronization of read-only replicas for query scale-out. 
 
 Data-refresh operations can take some time depending on a number of factors including data volume, level of optimization using partitions, etc. These operations have traditionally been invoked with existing methods such as using [TOM](https://docs.microsoft.com/analysis-services/tom/introduction-to-the-tabular-object-model-tom-in-analysis-services-amo) (Tabular Object Model), [PowerShell](https://docs.microsoft.com/analysis-services/powershell/analysis-services-powershell-reference) cmdlets, or [TMSL](https://docs.microsoft.com/analysis-services/tmsl/tabular-model-scripting-language-tmsl-reference) (Tabular Model Scripting Language). However, these methods can require often unreliable, long-running HTTP connections.
 
@@ -203,18 +203,18 @@ Here's a C# code sample to get you started, [RestApiSample on GitHub](https://gi
 
 ### To use the code sample
 
-1.	Clone or download the repo. Open the RestApiSample solution.
-2.	Find the line **client.BaseAddress = …** and provide your [base URL](#base-url).
+1.    Clone or download the repo. Open the RestApiSample solution.
+2.    Find the line **client.BaseAddress = …** and provide your [base URL](#base-url).
 
 The code sample uses [service principal](#service-principal) authentication.
 
 ### Service principal
 
 See [Create service principal - Azure portal](../active-directory/develop/howto-create-service-principal-portal.md) and [Add a service principal to the server administrator role](analysis-services-addservprinc-admins.md) for more info on how to set up a service principal and assign the necessary permissions in Azure AS. Once you've completed the steps, complete the following additional steps:
 
-1.	In the code sample, find **string authority = …**, replace **common** with your organization’s tenant ID.
-2.	Comment/uncomment so the ClientCredential class is used to instantiate the cred object. Ensure the \<App ID> and \<App Key> values are accessed in a secure way or use certificate-based authentication for service principals.
-3.	Run the sample.
+1.    In the code sample, find **string authority = …**, replace **common** with your organization's tenant ID.
+2.    Comment/uncomment so the ClientCredential class is used to instantiate the cred object. Ensure the \<App ID> and \<App Key> values are accessed in a secure way or use certificate-based authentication for service principals.
+3.    Run the sample.
 
 
 ## See also

articles/analysis-services/analysis-services-node-movement.md renamed to articles/analysis-services/analysis-services-long-operations.md

@@ -1,16 +1,16 @@
 ---
-title: Understanding node movements in Azure Analysis Services | Microsoft Docs
-description: This article describes assuring reliable refresh operations during node movement.
+title: Best practices for long running operations in Azure Analysis Services | Microsoft Docs
+description: This article describes best practices for long running operations.
 author: minewiskan
 ms.service: analysis-services
 ms.topic: conceptual
 ms.date: 04/14/2020
 ms.author: owend
 
 ---
-# Understanding node movements
+# Best practices for long running operations
 
-In Azure Analysis Services, a *node* represents a set amount of processor, memory, and storage resources. A server resource runs within the context of a node. Some operations such as long running queries, refresh operations, and query scale-out synchronization can fail if a server resource moves to a different node. Common error messages in this scenario include:
+In Azure Analysis Services, a *node* represents a host virtual machine where a server resource is running. Some operations such as long running queries, refresh operations, and query scale-out synchronization can fail if a server resource moves to a different node. Common error messages in this scenario include:
 
 - "An error has occurred while trying to locate a long running XMLA request. The request might have been interrupted by service upgrade or server restart."
 - "Job with ID '<guid>for model '<database>' was canceled due to service error (inactivity) with message 'Cancelling the refresh request since it was stuck without any updates. This is an internal service issue. Please resubmit the job or file a ticket to get help if this issue happens repeatedly."
@@ -27,7 +27,7 @@ In addition to node movements, there are other failures that can occur. For exam
 
 ## Refresh REST API
 
-Service interruptions can be challenging for long running operations like data refresh. Azure Analysis Services includes a REST API to help mitigate negative impacts from service interruptions. To learn more, see [Asynchronous refresh with the REST API](analysis-services-async-refresh.md) .
+Service interruptions can be challenging for long running operations like data refresh. Azure Analysis Services includes a REST API to help mitigate negative impacts from service interruptions. To learn more, see [Asynchronous refresh with the REST API](analysis-services-async-refresh.md).
 
 Besides the REST API, there are other approaches you can use to minimize potential issues during long running refresh operations. The main goal is to avoid having to restart the refresh operation from the beginning, and instead perform refreshes in smaller batches that can be committed in stages.