Hi everyone, I'am using Prefect version: 3.1.1 and I’ve been encountering an intermittent issue with my Prefect deployments, and I’m hoping someone can help clarify why this might be happening and how to best address it. Here's the context: When I execute a deployment, the flow sometimes enters a

Crashed

state. The logs show the following error:

ERROR   | prefect.engine - Engine execution of flow run '<run-id>' exited with unexpected exception
FileNotFoundError: [Errno 2] No such file or directory: 'C:\\Users\\Lenovo\\AppData\\Local\\Temp\\<temp-folder>\\orchestration\\subflows_definition\\coordinador_downloads.py'

This suggests that the deployment is unable to locate the required file in the temporary directory. Interestingly, if I restart Prefect (both the Server and Workers) and rerun the same deployment, it executes successfully without issues. Logs for the successful run show:

INFO    | Task run 'run_script-f9b' - Successfully ran script ...
INFO    | Flow run '<run-id>' - Finished in state Completed()

Why might the flow enter a

Crashed

state with a

FileNotFoundError

for code stored in a temporary directory? Could this be related to my use of

LocalFileSystem

storage on Windows? What happens during a Prefect restart that resolves the issue? Is it forcing a re-synchronization of the code between the Server and Worker? Are there best practices or configurations I can apply to prevent this kind of issue in a Windows environment?

Hi Sebastian! Thanks for adding this helpful context. How are you deploying your code? Are you using

.deploy()

?

.serve()

?

prefect deploy

in the CLI?

Hi, when deploying my code, I use

serve()

after I define all my flows and the parameters for each deployment to run

Hi, when deploying my code, I use

serve()

after I define all my flows and the parameters for each deployment to run

Mind sharing a snippet of how you've setup your

.serve()?

👀

In a production environment, what are the key differences between using

.deploy()

,

.serve()

, and the

prefect deploy

CLI for managing deployments?

In short,

.serve()

is suitable for running flows on static infrastructure. Both

.deploy()

and

prefect deploy

are best for deploying flows to dynamic infrastructure, with

.deploy()

offering a more programmatic approach using the Python SDK, and

prefect deploy

using a yaml-based approach that is more static and declarative. All in all, each option is production-ready.