Editing Debug Mode Docs

Author: djpmsft

articles/data-factory/concepts-data-flow-debug-mode.md

@@ -25,19 +25,16 @@ In most cases, it is a good practice to build your Data Flows in debug mode so t
 > [!NOTE]
 > While the debug mode light is green on the Data Factory toolbar, you will be charged at the Data Flow debug rate of 8 cores/hr of general compute with a 60 minute time-to-live 
 
-## Debug mode on
-When you switch on debug mode, you will be prompted with a side-panel form that will request you to point to your interactive Azure Databricks cluster and select options for the source sampling. You must use an interactive cluster from Azure Databricks and select either a sampling size from each your Source transforms, or pick a text file to use for your test data.
-
-<img src="media/data-flow/upload.png" width="400">
-
 > [!NOTE]
 >When running in Debug Mode in Data Flow, your data will not be written to the Sink transform. A Debug session is intended to serve as a test >harness for your transformations. Sinks are not required during debug and are ignored in your data flow. If you wish to test writing the data >in your Sink, execute the Data Flow from an Azure Data Factory Pipeline and use the Debug execution from a pipeline.
 
 ## Debug settings
-Debug settings can be Each Source from your Data Flow will appear in the side panel and can also be edited by selecting "source settings" on the Data Flow designer toolbar. You can select the limits and/or file source to use for each your Source transformation here. The row limits in this setting are only for the current debug session. You can also use the Sampling setting in the source for limiting rows into the Source transformation.
+Debug settings can be edited by clicking "Debug Settings" on the Data Flow canvas toolbar. You can select the limits and/or file source to use for each of your Source transformations here. The row limits in this setting are only for the current debug session. You can also select the staging linked service to be used for a SQL DW source. 
+
+<img src="media/data-flow/debug-settings.png" width="400">
 
 ## Cluster status
-There is a cluster status indicator at the top of the design surface that will turn green when the cluster is ready for debug. If your cluster is already warm, then the green indicator will appear almost instantly. If your cluster was not already running when you entered debug mode, then you will have to wait 5-7 minutes for the cluster to spin up. The indicator light will be yellow until it is ready. Once your cluster is ready for Data Flow debug, the indicator light will turn green.
+There is a cluster status indicator at the top of the design surface that will turn green when the cluster is ready for debug. If your cluster is already warm, then the green indicator will appear almost instantly. If your cluster was not already running when you entered debug mode, then you will have to wait 5-7 minutes for the cluster to spin up. The indicator will spin until it is ready.
 
 When you are finished with your debugging, turn the Debug switch off so that your Azure Databricks cluster can terminate and you will no longer be billed for debug activity.