Hi, I am trying to gauge Prefect for our workflow management needs. I had a question regarding self-hosted Prefect server but couldn’t find supported documentation for this : Is there a way to scale the Prefect Server k8s deployment to more than 1 replica on increased load? An analogy to Airflow scheduler scaling introduced in 2.0 - https://airflow.apache.org/docs/apache-airflow/stable/concepts/scheduler.html#running-more-than-one-scheduler

how can I access the prefect cloud graphql api using an api key? Do I somehow create a jwt token from the api key?

Hi all, we're testing out running prefect server with an ECS Agent and Docker Containers for flow storage. Everything is working great so long as we use the LocalExecutor or LocalDaskExecutor for our flows. However, when we try to use the DaskExecutor to launch a temporary Fargate dask cluster, the worker nodes on that temporary dask cluster start complaining about not being authenticated with the cloud service. Any ideas about what is going wrong here? Has anyone else attempted this kind of setup before?

Hi everyone — I have a flow that runs every 10 minutes and it’s been pretty consistent, however every now and then the flow throws an exception 502:

502 Server Error: Bad Gateway for url: <http://prefect.landbay.internal:8081/api/graphql/graphql>

however I’m not sure there’s an issue with how I’ve configured the URLs as the flow runs 99% of time without raising this….. For reference, these are the only 2 URLS I set:

PREFECT__SERVER__ENDPOINT=<https://prefect.prodenv.landbay.co.uk/api/graphql>
PREFECT__API__HOST=<https://prefect.prodenv.landbay.co.uk/api/graphql>

I now have a working Prefect Server with flows running within a

DockerRun

run config. However, since I deployed to the server the runs are not very reliable. I keep getting random errors in a totally non-deterministic way (cf. image). The flows all run fine on my machine and were also running fine when executed in a Docker container I was managing myself (on cloud infrastructure). Some of the errors include: •

HTTPConnectionPool(host='host.docker.internal', port=4200): Read timed out. (read timeout=15)

•

sqlalchemy.exc.NoSuchTableError

(I am writing to Postgres tables - the table does exist and sometimes the run even succeeds) •

TypeError: 'NoneType' object is not subscriptable

•

No heartbeat detected from the remote task; retrying the run.This will be retry 1 of 3.

I believe most of the errors are related to some time out issue / the state of the task can’t be monitored but I am confused as to why this happens. My VM has sufficient resources (I checked the monitoring) but I am thinking it might be worth scaling it up? I know the question might be a bit broad but would be happy to know if anyone experienced something similar and / or knows the reasons / a fix.

We got this error also in the local dev machine version (on-prem):

Expected type UUID!

see here: https://github.com/PrefectHQ/prefect/issues/4687 Can you fix this also in the server edition?

Is there a simple way to disable the

Task 'xy[z]': Finished task run…

messages?

Is there a way to retrigger a failed task run via the graphql api?

I saw this on Prefect Core website:

COMING SOON - Task Affinity Run each of a flow's tasks in a completely different environment, including new dependencies or platforms.

How far this feature is and will this mean that we could define a Docker image per task for example?

[SOLVED]~Has anyone had trouble getting the server to start on a mac?~

subprocess.CalledProcessError: Command '['docker-compose', 'pull']' returned non-zero exit status 15.

and later

subprocess.CalledProcessError: Command '['docker-compose', 'down']' returned non-zero exit status 15.

Tasks execution when one of the task fails. if I have a situation:

@task(timeout=60)
def task_1():
    x = func1(...)
    return x == 0

@task(timeout=60)
def task_2(r):
    y = func2(...)
    return y == 0

@task(timeout=60)
def task_3():
    z = func3(...)
    return z == 0

def main():
    with Flow("my-flow", executor=LocalDaskExecutor()) as flow:
        r = task_1()
        r = task_2(r)

        r2 = task_3()

if

task_1

times out and fail,

task_2

will not run. What can I change so that I can still use the

LocalDaskExecutor

but allow

task_2

to run even if

task_1

failed ?

Hey everyone, on my local agent everything works fine. But if i want to use 

DockerRun(image="prefecthq/prefect")

  with

prefect agent docker start

 i´m getting this Error:

Failed to load and execute Flow's environment: ModuleNotFoundError("No module named 'C'")

I know that i can´t import other dependencies but i only import following modules from prefect in the script:

from prefect import Flow, task

from prefect.run_configs import LocalRun,DockerRun

Or is it possible to run 

DockerRun()

 in an existing Container?

Hello everyone, is there a way to manually run a Prefect flow from the middle of the schematic in Prefect Server(Prefect Cloud)? Sometimes my flow fails and I need to skip tasks and run from the middle.

When you register your flows from code (Python), using e.g.

Module

storage with

stored_as_script=True

, why do all the flows and their dependencies need to be resolved? e.g. all my flows import

db

which is an instance of

sqlalchemy.create_engine()

that I setup with an environment variable. If I try to register e.g. from a CI pipeline, I have to set all those variables just to be able to register a script that will be stored as a file anyway? (NB: can’t use the CLI

prefect register

because it is not able to resolve any of the dependencies of my flows (they are in a folder), spitting

ModuleNotFoundError

)

I deployed the server on a VPS and am trying to start a local agent, but it seems to expect an API key. When I run locally, this doesn’t happen. Is there a config I’m missing to tell it to run locally?

Hello. I'm upgrading to 0.15.4 and it seems that we're receiving an error message from Alembic when graphql tries to run migrations

Could not upgrade the database!
Error: Can't load plugin: sqlalchemy.dialects:postgres

Hi all - could someone point me to a document which goes over, in some detail, what happens to a workflow running on an agent if the agent is stopped in the middle of the workflow?

I see in Dask that there's a priority parameter for "when there's more work than workers [and] Dask has to decide which tasks to prioritize over others." Is this exposed to Prefect? More specifically, let's say I have a collection of flows and my system is running low on resources, is there a way to tell Prefect to prioritize completing one flow over another? Thanks in advance!

Sorry for mentioning this again, but I’m still grappling with this error. Does this look familiar to anyone?

ERROR:asyncio:Fatal error on SSL transport

Hey folks, I’m trying to set up a workflow where we spin up a GKE cluster on demand, run a Kubernetes + Dask workflow on it, and then tear down the GKE cluster when the flow is finished. Is this the kind of thing that I’d want to do with a flow inside of a flow? In other words, have a parent flow that manages the cluster, while the child flow handles the data ETL work I’m performing on K8S+Dask? If so, are there any drawbacks to this approach I should be aware of (e.g. visibility into potential errors in the child flow)?

Something went wrong while trying to fetch failed flow information. Please try refreshing your page. If this error persists, return to this page after a few minutes.

latest prefect-server deployment via helm - We get this error after 2 weeks of flows runs - now we cantt see our flows 😞

Hey folks, apologies if this is a rookie question, as I’m just getting started with Prefect. What I’m aiming to do is set up a flow where each task is a container run on a separate google cloud compute instance (where the instance is spun up on task start and destroyed on task end, instance type & config depends on the task). It seems like this lies somewhere between the purpose of the Docker agent and the Kubernetes agent, where the former runs task as containers but only locally, while the latter can create new instances but requires a full Kubernetes setup (which we currently don’t use). Am I understanding this correctly? Is the workflow I described similar to what someone has built with Prefect?

Is it possible to programmatically archive a flow? I found this but

mutation { archive_flow(...) { ... } }

doesn't appear to be valid anymore, I only see

delete

mutations.

Hi everyone. Does anybody have some practice example of using Google Cloud Tasks? (Google and GitHub didn’t help me, unfortunately).

I am having trouble passing sensitive information to my flow's run configuration. Having:

secret = PrefectSecret("SOME_SECRET")
flow.storage = S3(bucket="some-bucket", secrets=["AWS_CREDENTIALS"])

flow.run_config = KubernetesRun(
    image="<http://registry.gitlab.com/<some_image>|registry.gitlab.com/<some_image>>",
    labels=["prefect-14"],
    env={
        "PREFECT__LOGGING__LEVEL": "DEBUG",
        "SECRET": secret
    },
    image_pull_secrets=["image-puller"],
)

and then running:

flow.register("ProjectName")

I get:

TypeError: Object of type PrefectSecret is not JSON serializable

Any thoughts on this?

Hi Everyone 👋 I have setup the prefect server in a kubernetes cluster using Helm Chart (https://github.com/PrefectHQ/server/tree/master/helm/prefect-server) I have also set up ingress rules for the UI and apollo components. Unfortunately the UI page is not loading, i am able to access apollo though. I have created the tenant as mentioned in the docs using '--set jobs.createTenant.enabled=true' and also directly using graphql mutation. Any idea what might be the issue?

Hello 👋 I would love to use Parameter and mypy together. However currently when I do;

var: str = Parameter('var')

mypy complains with

Incompatible types in assignment (expression has type "Parameter", variable has type "str")

Even though after calling this will be a string 🤔 Any thoughts on how to achieve this?

Hello everyone , I am running my prefect on K8 cluster using helm charts. I have a separate postgres stateful database attached to persist states. I have 2 questions here :

1.) I have flow which gets data from an api and i want to publish it to slack directly, how should i do it without writing it anywhere. 
2.) If i want to save my flow/task results on a machine from where I am registering my flows despite flow running on pods on k8 ,how should i do it.

Hello everyone, I am looking for a way to make my flow dependent on another one. In Airflow I used externalTaskSensor: in DAG "B" check DAG "A" status, if it's not a success then retry later. I've tried StartFlowRun, but it starts a new run of DAG "A" every time. I have some heavy computation in "A" and don't want it to be run multiple times. Is there a way to do it without kicking off parent flow?