@Marvin till when will prefect 2 be supported?

@Marvin Why am I getting the following error when I try to execute the following code:

from prefect.deployments import run_deployment
run_deployment(name="my_function/My Sample Deployment", parameters={}, job_variables={"image": image})

The error is: pydantic.errors.PydanticUserError:

State

is not fully defined; you should define all referenced types, then call

State.model_rebuild()

.

Hi everybody, im having an issue with Ray. Its creating multiple db connections (server db) but its not closing them. I have 100 connections that stay idle. How can i clean these connections from prefect server. One solution is to have a job that cleans these connections every N minutes but im wondering if there is an existing setting that takes care of this. Thank you

@Marvin In my server I've set PREFECT_RESULTS_PERSIST_BY_DEFAULT to be True. Why is the state.data still None when awaiting the result?

I'm pretty puzzled by a good way to create logging from tasks that run inside Docker containers (that reflects correctly in the Cloud UI). I have a flow spinning up a bunch of different docker containers as part of a deployment. However I am not sure what is a good way to handle logging for the individual containers through Prefect. Right now everything is running on the same machine, with a worker on Docker that runs a flow that has various tasks where docker containers are created and run using the prefect.infrastructure.container package. The logging from the containers is piped through to Prefect UI using log_prints=True. However that means there is no proper error handling as everything has the same severity, and errors are not propagated from the containers. It seems there are a few ways to handle this: • Parse the logs after a task is finished. This could work but it's not real-time and any unexpected crashes might prevent this from running as expected • Parse the logs while the container is running by running and connecting to the containers using the python docker package. This might work but I'm introducing another dependency (docker package) and this would not work when the machine is remote. It does not seem this is possible by only using the default prefect python package. • Somehow setup logging inside the container that gets parsed the relevant flow/task information from the worker, so that it can recreate a prefect logger and log everything directly to Prefect It feels like this should be easier and a ready solution should be available however after searching a lot online and trying various options I still haven't found a satisfying solution. Maybe I'm missing something about how Prefect is supposed to be set up and what the philosophy behind it is.

@Marvin howdo i send metrics from selfhosted server to prometheus in kubernetes

@Marvin how to get task input in on_failure hook?

@Marvin what exactly is prefect task introspection?

Hello, has anyone seen this warning before? Basically one of my tasks is taking long time to even run. There is nothing special about this task and I've used it in other scripts /projects and have not had this issue before. Could it be because I recently upgraded to

2.18.0

?

Task parameter introspection took 65.871 seconds , exceeding `PREFECT_TASK_INTROSPECTION_WARN_THRESHOLD` of 10.0. Try wrapping large task parameters with `prefect.utilities.annotations.quote` for increased performance, e.g. `my_task(quote(param))`. To disable this message set `PREFECT_TASK_INTROSPECTION_WARN_THRESHOLD=0`

If it matters, this task just takes in a list returned from another task, creates a dataframe out of it and does something with it.

I'm trying to trigger a cli dbt command in prefect but getting this error

[0m20:39:10  Encountered an error:
Compilation Error
  dbt found 3 package(s) specified in packages.yml, but only 0 package(s) installed in dbt_packages. Run "dbt deps" to install package dependencies.

here's my command

trigger_dbt_cli_command.with_options(name=f"transform").submit(
        command=f"dbt run --models some_model",
        profiles_dir=dir,
        project_dir=dir,
    )

I see the dbt deps get installed when I build my docker container so not quite sure what's happening