I have the following flow:

@flow
def test():
    print("hello world")

And it will fail retro-actively from time to time:

15:18:12.953 | INFO    | prefect.agent - Submitting flow run '8b6a74ba-6dbe-49bd-b303-d5e9c863a087'
15:18:13.097 | INFO    | prefect.infrastructure.process - Opening process 'dangerous-ostrich'...
15:18:13.104 | INFO    | prefect.agent - Completed submission of flow run '8b6a74ba-6dbe-49bd-b303-d5e9c863a087'
15:18:30.922 | ERROR   | Flow run 'dangerous-ostrich' - Crash detected! Execution was interrupted by an unexpected exception.
15:18:30.954 | INFO    | prefect.engine - Engine execution of flow run '8b6a74ba-6dbe-49bd-b303-d5e9c863a087' aborted by orchestrator: This run has already terminated.
hello world
15:18:35.274 | INFO    | prefect.infrastructure.process - Process 'dangerous-ostrich' exited cleanly.

As you can see above, it completed successfully but at the same time it didn’t. Furthermore, the code clearly ran (

hello world

was printed), but it was still marked as an error. Shouldn’t the flow just be marked as completed?

which version of Prefect are you in?

@Khuyen Tran

Version:             2.1.0
API version:         0.8.0
Python version:      3.8.9
Git commit:          30ca715c
Built:               Wed, Aug 17, 2022 5:13 PM
OS/Arch:             darwin/x86_64
Profile:             default
Server type:         hosted

I recommend upgrading to 2.1.1, which fixes some issues in 2.1.0

Alright, will do!

Did this get resolved? I am running into the same error with prefect 2.3.2

@Rio McMahon After the update, I haven’t ran into the issue again

Hello @Khuyen Tran, i'mrunning my flows using 2.3.1 version and still having the same issue from time to time it crashs for no apparent reason even when the flow did his job and completed it

Hi Naila. If you update to 2.4.1 does the issue go away?

Hi Jeff , didn't test it , but i'll try , thank you

@Naila Chennit In my case it ended up being operator error on my part; I had an agent running locally and in the cloud - both were polling for the same work queue tag. Removing the local agent fixed it.

Thank you @Rio McMahon in my case, i solved the issue by seting the number of pod replicas to 1 instead of 2 as i'm using k8 job as infrastructure but i gess it was the same problem as yours as the two pods were polling from the same work queue