Hi. We use KubernetesRun and see debug logs like this in Prefect Cloud Logs:

Event: 'FailedScheduling' on pod 'prefect-job-79c82cd5-w6nfd'
	Message: 0/7 nodes are available: 2 node(s) had taint {<http://dask.corp.com/component|dask.corp.com/component>: scheduler}, that the pod didn't tolerate, 5 node(s) didn't match Pod's node affinity/selector

Do you have ideas how to disable them?

I can't seem to get tasks running concurrently or in parallel with dask in prefect 2 without using task.submit() Is that expected behaviour? It doesn't seem to be reflected in the docs.

Hello 🙋 is there a default limit for concurrent flows or something in the Cloud? we have currently a flow that was run ad-hoc and is still running, and a flow that was scheduled to run now, and it’s stuck in

Submitted

and nothing seems to be happening with it

Hi all, I am trying to run a flow with VertexRun. I created a GitLab repo, configured the Gitlab storage. Run a agent locally with vertex and the prefect cloud api key. However on run I keep getting the same error. Failed to load and execute flow run: ModuleNotFoundError. It keeps refering to a local path.

Why do I keep seeing this error while I am using the gitlab storage...

Hi prefect team, I had a question about deployment pausing in prefect 2.0. I am little confused by this concept. If a work queue is filtering by deployment and the deployment is paused do all flow runs based on said deployment get paused and go into a "pending" state? I don't see a way "pause" deployment programatically via either the cli or the api. It seems like this is a UI only feature am i missing something here?

Shameless plug: I made a meta-package linking different packages for different use cases. https://github.com/prassanna-ravishankar/python-productivity-stack Under the

mlops

section, I've added prefect -

pip install productivity-stack[mlops]

Hi, anyone knows how can I send params which contain mapped and unmapped parameters to create_flow_run? (More in the thread)

Hey all. Our flow isn't able to spin up more than 180 jobs. We can't determine the root cause exactly but at a certain point there's a connection aborted and prefect starts to remove jobs and then marks the entire flow as failed. We are using a daskexecutor on the cloud. Looking into the dask repos, we aren't able to set some debug level logging as an attempt to retrieve some info on what’s really causing the

Connection aborted

issue. Even if there are some failures, we do want the flow to continue and the task triggers are set accordingly. Thank you

Hi all, does anyone have experience integrating prefect alerts/failures with opsgenie?

Hi is it possible to clear all data from Prefect (2.0b12) on the hosted version? Similar to locally doing

prefect orion database reset -y

?

also, i am no longer able to see

Deployments

in Orion UI locally. If i inspect the network, I see it will successfully return my deployments, but they are never rendered in the UI.

Hi, I’m curious about how robust is Prefect operation w/

Kubernetes Agent

,

KubernetesRun

and

DaskExecutor

in the face of various components outages. E.g. what will Prefect be able to recover on its own, and which case would require a manual intervention, if during a flow execution one of the following dies: prefect server (I suppose it’s ok as it’s stateless), kubernetes agent,

KubernetesRun

job executing a flow, dask scheduler, dask workers.

Hi y'all I am developing a flow and have come across an error that neither me or my team understands. When trying to register the flow, we get:

ValueError: Flow could not be deserialized successfully. Error was: ValueError('A task with the slug "Parameter" already exists in this flow.')

This shows up after the step:

[2022-07-25 17:27:11-0700] INFO - prefect.Docker | Pushing image to the registry..

Parameters are currently in their own params.py file, and are referenced in the main flow file with:

import <main_directory>.tasks.params as params

is it possible to add back the UUID on the

prefect deployment create

command? we use it to compare created deployments with existing deployments to clean out unused deployments.

Hey y'all--happy Monday! I'm looking for guidance on writing credentials from Prefect Secrets to files, or alternatively for best practices using DBT profiles in Prefect flows in this Discourse topic, would love to hear from other Prefect community users: https://discourse.prefect.io/t/creating-volume-mounts-or-files-from-prefect-secrets/1243

Hello, After running the

prefect orion start.

It stops running quickly as below: Please let me know how do I troubleshoot this. Is it because of the windows machine that I am using?

Quick question: For prefect 1.0, should the env vars set in the agent's deployment manifests be present in executed flow's job environment? ?

Hello 🙋 Today i introduced our data-scientists to Prefect, and their main question was - what would be the easiest way for them to run their custom code (with all its various dependencies) from the flows they create Is containerizing their code in a docker image and pushing it to a remote repository (like ECR) the only reasonable way to achieve that? or could we conceivably just fetch the code from Github, and install the necessary dependencies as actual tasks in the flow, before executing it? (obviously it adds complexity and run-time to the flow, but are there any other reasons this might not work or be a bad idea?) (the main reason dockerizing and pushing to ECR is inconvenient for them is because they can't do it themselves, and we don't have a lot of DevOps resources that can easily provide them with a complete CI/CD pipeline for every new project they wanna test out)

can we use localdaskexecutor for parallel flows managed by k8s agent when moving to production?

I am having trouble with an error message I am receiving. I believe it has to do with the engine analyzing domain model classes i provide as input to a

@flow

. I will attach a micro example of what i am trying to accomplish... would someone mind helping me understanding the error message:

FAILED my-prefect-project/tests/flows.py::test_pipeline - TypeError: __init__() missing 2 required positional arguments: 'host' and 'port'

After installed Prefect on Windows10, I got a error message when run 'prefect version'

Version:             2.0b12
API version:         0.7.0
Python version:      3.9.1
Git commit:          18d44c8c
Built:               Fri, Jul 22, 2022 4:23 PM
OS/Arch:             win32/AMD64
Profile:             default
Server type:         <client error>

Hey community! Thank you for your software 🙂 I have an issue with setting up my orion workflow on kubernetes. I am following this doc, but stuck at Configure storage part for my GCP bucket. The doc suggests to call

prefect storage create

in cli, but my 2.0b13 doesn’t have no such command returning the error Error: No such command ‘storage’. Should I create the storage using this doc ? There is no example for GCP, i found this one in the community. But there is no

from prefect.blocks.storage import GoogleCloudStorageBlock

import in my venv 😞

can one agent run multiple work-queues in prefect 2.0

I have a task which will return a list, is it possible to use case based on the length of the returned list? e.g.

data = returns_list()
with case(data, len(data) > 1):
    do_stuff_with_data(data)

with case(data, len(data) == 0):
    do_stuff_with_no_data()

Hi 🙂 Does prefect 2.0 export some metrics through an open-telemetry exporter for example ? 🙂 And more globally what is the best way to be alerted when a job fails ? (I have already an alert in my kubernetes cluster if a pod fails but maybe it’s possible to have something more prefect related/high level)

Hi Community, I am facing issue while scheduling prefect flows (v 1.2.2). issue screenshot attached. looking for help. Thanks !

Prefect 2.0 | Accessing current flow state Hi! 👋 Possibly simple question which I can’t seem to find an answer for: Can I access the state of the current flow from within that flow? In particular I’d like to check if the flow is retrying, and if so pass an extra argument to my task(s) i.e.

@flow
def my_flow():
  if <somehow_get_state_of_this_flow?> == "Retrying":
    do_something()