potiuk commented on PR #35026:
URL: https://github.com/apache/airflow/pull/35026#issuecomment-1770749079

   > Also, I don't have the feeling that your [CI is using cache 
layers](https://github.com/apache/airflow/actions/runs/6572143194/job/17852736374#step:6:697)
 even though [it 
should?](https://github.com/apache/airflow/blob/5c2dc53bcb17ae515f9565c41d15cc6d1693382c/dev/breeze/src/airflow_breeze/utils/docker_command_utils.py#L445).
 As @hussein-awala said, once buildkit will have implemented a way to use 
`binded cache` in CI, it would also help to improve build speed
   
   It's because you were extremely unlucky when checking it. Python **just** 
released a new base image 4 hours ago, and our cache will refresh with the new 
base image after we merge something to main and the build in `main` succeeds:
   
   
![image](https://github.com/apache/airflow/assets/595491/f748289c-d3e2-4a31-a504-1243d2751655)
   
   The way how we are using remote caching is specifically designed to 
automatically handle such cache refreshes. The whole CI of ourse is designed to 
automatically upgrade to latest versions of the base images, apt dependencies 
and Python dependencies as soon as:
   
   * they are released
   * all our tests pass in main (also called `canary`)  run
   
   This allows us to automtically upgrade and test our software and test suite 
to "latest", "most secure" and "consistent" set of dependencies (including base 
dependencies for the image), while our PRs keeps on using the "stable and 
confirmed to work in the past"  set of python dependencies. 
   
   This way we can detect breaking changes in incoming dependencies. We 
detected many breaking changes this way "early" - hence `canary` name 
(including even couple of breaking changes in Python patchlevel releases) 
   
   Indeed the build you see does not use the cache that corresponds to the 
latest pyhon version that's why it takes 14 minutes. Because cache is not yet 
refreshed. But it still works (which is great) while the cache is being rebuilt 
and refreshed. 
   
   You can see the same job from 5 hours ago 
https://github.com/apache/airflow/actions/runs/6565914251/job/17835531939#step:6:1070
 which lasted 1 minute and actually used the cache.
   


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