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...
The main question I have is why is the ALB not passing the request, I think you are correct it never reaches the serving server at all, which leads me to think the ALB is "thinking" the service is down or is not responding, wdyt?
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
time.sleep(time_sleep)
You should not call time.sleep in async functions, it should be asyncio.sleep,
None
See if that makes a difference
Hi @<1569858449813016576:profile|JumpyRaven4>
- The gunicorn logs do not show anything including any error or trace of the 502 only siege reports the 502 as well as the ALB.Is this an ALB or an ELB ?
What's the timeout its configured?
Do you have GPU instances as well? what's theclearml-serving-inference
docker version ?
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")
ACtually the request are never registered to the gunicorn app, and the ALB log show that there is no response from the target "-".
Meaning if I create a sleep endpoint that is async
Hmm are you calling "sleep" or "async.sleep"?
Also are you running the serving service with GUNICORN or UVCORN?
see here:
None
Hmm reading this: None
How are you checking the health of the serving pod ?
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
yeah I tend to agree... keep me posted hen you find the root cause 🤞
Hi Martin,
- Actually we are using ALB with a 30 seconds timeout
- we do not have GPUs instances
- docker version 1.3.0