Ha, good point!
That is actually the way to go.

Thanks Ash.

- Eugene

On Fri, Sep 19, 2025 at 10:52 AM Ash Berlin-Taylor <[email protected]> wrote:

> The correct fix for this on Airflow 3 is to write a GCS Dag bundle
> backend, to use versioned buckets, so that when a worker requests a version
> to run it the Bundle manager can pull down the specific object version out
> of the bucket — i.e. don’t rely on a separate gustil sync process.
>
> > On 17 Sep 2025, at 12:29, Eugen Kosteev <[email protected]> wrote:
> >
> > Hello.
> >
> > I would like to discuss the following issue that we face in Cloud
> Composer
> > (and probably others face too).
> > We deploy Airflow components running in separate GKE pods, and DAG files
> > are synced from GCS (Google Cloud Storage) to each component separately -
> > we do not use any NFS-type disks mounted to each component,
> > the DAG files are continuously synced to each pod (i.e. something like
> > ~"gsutil rsync ..." in a loop).
> >
> > Since all components are in such a distributed environment, DAG files can
> > be out of sync between components, and this results in the following
> issue:
> > 1. new DAG file is synced to DAG processor
> > 2. new DAG is scheduled by scheduler
> > 3. Celery worker starts execution of the task (scheduled DAG) and fails
> > (can't parse file) because DAG file is not yet synced to worker
> > 4. new DAG file is synced to Celery worker
> >
> > The parsing of the DAG file in task runner happens here:
> >
> https://github.com/apache/airflow/blob/eabe6b8dd77204f7c0d117c9d9ad1f4166869671/task-sdk/src/airflow/sdk/execution_time/task_runner.py#L634
> >
> > So far, we were trying different hacks to address this issue in Cloud
> > Composer.
> >
> > *Question:*
> > Would it make sense/is it possible to have some retry logic in the
> "parse"
> > method of task runner? For example, ~implementation:
> > - DAG is parsed
> > *- if DAG is not found -> sleep + retry parsing (loop)*
> > *- if timeout reached, exit with message "Dag not found ..."*
> > - if DAG is found, continue
> >
> > Having any value >0 for timeout has its own downside, that failure of the
> > tasks which DAG files really disappear will now take more time.
> >
> > The timeout can be configurable, and we can have "0" as default value,
> > which means that the implementation will be completely backward
> compatible.
> > And Airflow administrators can override this value, knowing that they
> have
> > the issue described above, and downsides of having this timeout
> increased.
> >
> > Any thoughts?
> >
> > --
> > Eugene
>
>
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-- 
Eugene

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