Discrepancy in ADF Data flow Activity Execution Time and Sink Processing Time in ADF Jobs

I've been observing a significant time difference between the execution duration of my Azure Data Factory (ADF) dataflow activities and the actual completion time of the sink processing including Cluster startup time within the activity. For instance, in a recent example, the dataflow activity started at 11:00:07, and its duration was recorded as 1 minute and 28 seconds, indicating an end time of 11:01:35. However, while monitoring the data flow details, I noticed that the sink processing had already completed within 1 sec 301 ms with cluster startup time of 1 s 263 ms.

The below snapshot shows the Dataflow status as “Success” at 11:00:29 but the actual pipeline is still in process.

Given this discrepancy, I am curious to understand why the dataflow activity remains in progress at the pipeline level even after the sink processing has been completed. This issue becomes particularly pertinent as I am running multiple pipelines with Data flows in my project, leading to a substantial accumulation of time differences. I am utilising a managed vnet IR with a memory-optimised 16 (+16 driver cores) and have set the Time To Live to 30 minutes.

I would appreciate any insights or guidance on potential causes for this discrepancy and any recommendations on how to address it effectively.

Thanks,