<@U02H1A95XDW> or <@U01QEJ9PP53> Any update on thi...
# prefect-community
@Anna Geller or @Kevin Kho Any update on this issue? We’re running into the same issues with no logs appearing when using Prefect with LocalDaskExecutors on a Docker Agent in “processes” mode https://github.com/PrefectHQ/prefect/issues/5769
We haven’t had bandwidth to investigate this thoroughly yet as we get 2.0 out of beta. Can try digging myself today and seeing what I find.
Ping me tom if I don’t get back to you
🙏 1
I am still looking and am still clueless, but a good workaround is Dask LocalCluster though if you’re open to using that. Example below:
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from prefect import task, Flow
from prefect.run_configs import ECSRun, DockerRun
from prefect.storage import S3
from prefect.executors import LocalDaskExecutor, DaskExecutor
import prefect
import time

def abc(x):
    return "hello"

with Flow("ecs_test", run_config=DockerRun(image="prefecthq/prefect:1.2.0-python3.7", env={"PREFECT__LOGGING__LOG_LEVEL": "DEBUG"}), 
                      executor = DaskExecutor(cluster_kwargs={"n_workers": 4, "threads_per_worker": 1})) as flow:

flow.storage = S3(bucket="coiled-prefect")
Is it possible to have n_workers or threader per worker to be set dynamically at flow run time based on agent env variables?
Actually that is only possible for DaskExecutor and not LocalDaskExecutor. You can see this