np

hey Marin real quick actually, on your update to the requirements.txt file isn't that constraint on fastapi inconsistent?

so i still can't figure out what sets the task status to aborted

ok so I haven't looked at the latest changes after the sync this morning but the ones we put in yesterday seems to have fixed the issue, the service is still running this morning at least.

no requests are being served as in there is no traffic indeed

Hi Martin, thanks a lot for looking into this so quickly. Will you let me know the version number once it's pushed? Thanks!

ok I see that now. Everything is there on the UI and webserver though so we went ahead and implemented ourselves on the clearml-serving piece.

oh

any timeline on this that you are aware of?

how can you be >= 0.109.1 and lower than 0.96

Hey Martin, I will, but it's a bit more tricky because we have modifications in the code that I have to merge on our side

my understanding was that the deamon thread was deserializing the task of the control plane every 300 seconds by default

so they ping the werb server?

what is actually setting the task status to Aborted ?

I will actually write here what I found. trigger_on_tags and trigger_required are actually the same and concatenated with OR. You need to make sure you are using the "__$all" before if that's the behavior you want.
there is a bug in my opinion on the deserialization process because the triggers get de-dupped by trigger name or when using trigger_project there are dozens of triggers being created with the same name (one per dataset in the project). This leads to random behavior dependi...

Hi Alex,
thanks for your answer. I'm curious about your third point using OutputModel. I could not figure out from the documentation how do you actually use it. I constructed the OutputModel object as such:

• out = OutputModel(task, name="my_model", framework="xgboost")
  However, I could not find any method in the doc that would allow me to pass the model object to that instance or said otherwise, I can't understand how to use that Output model to register my model which would be stored in a...

Hi Martin,

• Actually we are using ALB with a 30 seconds timeout
• we do not have GPUs instances
• docker version 1.3.0

alright, so actually we noticed that the problem disappears if we use only sync requests. Meaning if I create a sleep endpoint that is async we get the 502 but if it's sync we don't

that's a fair point. Actually we have switched from using siege because we believe it is causing the issues and are using Locust now instead. We have been running for days at the same rate and don't see any errors being reported...

thanks for your reply!

we have tried both and got the same issue (gunicorn vs uvcorn).
No I meant creating a

@router.post(
    "/sleep",
    tags=["temp"],
    response_description="Return HTTP Status Code 200 (OK)",
    status_code=status.HTTP_200_OK,
    response_model=TestResponse,
)
# def here instead of async def
def post_sleep(time_sleep: float) -> TestResponse:
    """ """
    time.sleep(time_sleep)
    return TestResponse(status="OK")

We put back the additional changes and so far it seems that this has solved our issue. Thanks a lot for the quick turnaround on this.

I can't be sure of the version I can't check at the moment, I have 1.3.0 from the top of my head but could be way off

Geez, I have been looking for this for a while, thanks for saving my day...again.

was allow_archived removed from Task.query_tasks?

yeah I don't know I think we are probably just trying to fit to high a throughput for that box but it's weird that the packet just get dropped i would have assumed the response time should degrade and requests be queued.

I'm not sure what to do with that info I must say since the serve_model is async for good reasons I guess

This being said, now I'm running into another issue that this seems to be "erasing" all the packages that had been set in the base task I'm cloning from. I can't find a method that would return these packages so that I could add to it?

I have tested with an endpoint that basically add two numbers and never managed to trigger the 502. I'm starting to wonder if we are not running just too many workers. I had it wrong that 2 vcpus should mean 5 workers should be good but I think i should probably be closer to 2 but I m not sure why that would lead requests being dropped

Hi @<1523701087100473344:profile|SuccessfulKoala55> ,
I'm running in almost the same error (see below) but I want to connect the the free clearml server version at None so I have set up the corresponding env variables in example.env:

CLEARML_WEB_HOST="

"
CLEARML_API_HOST="

"
CLEARML_FILES_HOST="

"
CLEARML_API_ACCESS_KEY="---"
CLEARML_API_SECRET_KEY="---"
CLEARML_SERVING_TASK_ID="---"

I have set up the right values from...