hey guys, I’m trying to start multiple deployment runs in a Flow using

prefect.deployments.run_deployment()

, is it possible to start these deployment runs concurrently?

Just set timeout=0

Dropping docs here, just in case.

It does the trick, thanks! the only thing is, because it returns the function immediately, there’s no way to know the result of the deployment run?

Check out this thread @James Zhang https://prefect-community.slack.com/archives/CL09KTZPX/p1670199580029429?thread_ts=1670199580.029429&cid=CL09KTZPX

I ended up using this pattern with ConcurrentTaskRunner:

@flow
def main_flow():
    for x in y:
      start_single_deployment.submit()
      ....

@task
def start_single_deployment():
    run_deployment(...)

in this way i can still get the states from the

run_deployment()

in subflows

Does it work? I remember trying it and running into some issues with async and not being able to return the state?

i’m on version 2.7.3 it works as expected… the deployment runs are somehow treated as subflows. so if a deployment run fails, hence the subflow failes, hence the mainflow is informed. only catch is, if the pod where deployment runs on somehow killed by AutoScaler, the mainflow wouldn’t know the subflow hangs… heck, even the subflow wouldn’t know the pod is killed…

Nice. Sounds like it's perfect. I'm surprised because I thought you're not returning anything from the task, so the parent flow wouldn't realise the state of the run deployment call.

the

run_deployment()

returns a Future, so I guess the task runner in mainflow will watch that

Ah, in your example code you don't have a return.

didn’t look into the source code, i’m just guessing according to the doc: https://docs.prefect.io/api-ref/prefect/deployments/#prefect.deployments.run_deployment 😛