There is a section called “landing time” in the DAG view on the web console of airflow.

An example screen shot taken from airbnb’s blog:

But what does it mean? There is no definition in the documents or in their repository.

Since the existing answer here wasn’t totally clear, and this is the top hit for “airflow landing time” I went to the chat archives and found the original answer being referenced here:

Maxime Beauchemin @mistercrunch Jun 09 2016 11:12 
it's the number of hours after the time the scheduling period ended
take a schedule_interval="@daily" run for 2016-01-01 that finishes at 2016-01-02 03:52:00
landing time is 3:52

It seems the Y axis is in hours, and the negative landing times are a result of running jobs manually so they finish hours before they “should have finished” based on the schedule.

I directly asked the author Maxime. His answer was landing_time is when the job completes minus when the job should have started (for airflow, it’s the end of the scheduled period).

It is a good place to get help and Maxine is very nice and helpful. But the answers are not persistent..

For me its easier to understand landing_time using an example.
So let’s say we have a dag scheduled to run daily at 0 0 * * *. This dag has 2 tasks that execute sequentially:

first_task >> second_task

The first_task starts at 00:00 and 10 seconds and finishes after 5 minutes.
The landing_time for first_task will be 10 seconds.

The second_task starts execution at 00:07 minute and finishes after 2 minutes. The landing_time for the second_task would be 7 minutes.

So we just delete from the task start time the dag execution_date.
I usually use landing_time as a measure – metric of the performance of the whole airflow system. For example increase in loading_times in the first tasks seems to mean that scheduler is under heavy load or we should adapt task parallelization (through airflow.cfg).

Landing Times: Total time spent including retries.