• 2 min read

Azure Data Factory Updates: Monitoring and Management Enhancements

We have released a powerful set of updates to enhance the user experience in Azure Data Factory!

Activity View- Zoom into the pipelines

Customers now have the ability  to right click a pipeline, click ‘Open pipeline’ and navigate inside the pipeline. This will allow customers to look at the activities inside the pipeline and the connections between the corresponding input and output datasets.

This is very helpful when customers have a pipeline with more than 1 activity and want to see the operational lineage for just that single pipeline.

Example: Right click on ‘AnalyzeMarketingCampaignPipeline’ to see ‘Open Pipeline’.


Clicking ‘Open Pipeline’ will showcase the activities inside the ‘AnalyzeMarketingCampaignPipeline’ along with input and output datasets corresponding to each activity in the pipeline. You will also see a breadcrumb on the top left corner notifying that you are currently looking at the activities inside the ‘AnalyzeMarketingCampaignPipeline’.


You can navigate back to the ‘Diagram View’ by clicking ‘Data Factory’ in the breadcrumb on the top left corner.


Upstream Slices that are Not Ready:

Customers can now determine why their slices are stuck in ‘Pending Execution’ state. We have enabled a new feature that allows customers to determine the upstream dependencies due to which the current slice is not ‘Ready’ and still in ‘Pending Execution’ state.

This is very useful for customers who are monitoring the last produced dataset in their Azure Data Factory workflow and are continuously seeing the slices in ‘Pending Execution’ state.

Example: Clicking a slice entry in the ‘Recently Updated Slices’ tab opens up the details about the slice execution. This includes a new section named ‘Upstream Slices that are not ready’, which lists all the upstream dependencies that are not ready for the currently selected slice.


Monitor Slices by Last Update Time:

Customers can now see the slices by ‘Last Updated Time’ in addition to the slice time.

This is useful when customers have re-run a slice produced in the past. Now the re-run slice will appear on the top of the list since it was updated last.

Example: The 05/26/2015 09:00 PM-10:00 PM slice is at the top of the list in the below screenshot as it was updated last at 05/26/2015 10:16:03 PM UTC.


You can still see the slices by slice time by clicking ‘Data Slices (by slice time)’.



By adding these enhancements, we are continuously trying to make the Azure Data Factory Monitoring and Management experience easy for our customers . If you are missing a specific functionality or encounter any issues, please visit the Azure Data Factory Forums and provide your feedback.