im using asgi_redis, and somehow it's better since i changed settings to:
channel_layer = RedisChannelLayer(
capacity=1000,
expiry=5,
)
but i still dont have idea whats correct. I would like to explain what im
trying to achiev. I have website for matchmaking of dota 2 lobby games.
When 10 players are finding match, ready check is sent and when everyone is
ready then Steam bot starts and hosts the game...Bot must run entire time
when players are playing so it needs one worker for each game played...Its
why i cannot have only 2 workers or so i guess...because when there is more
than one game workers are busy.
Dne neděle 5. března 2017 20:14:55 UTC+1 Andrew Godwin napsal(a):
>
> Python threads are not that great at sharing I/O - I'd recommend you run
> at most one or two per physical CPU core in your machine. 500 is just going
> to suffocate Python in context switching.
>
> We have loadtests that definitely got above 10 messages a second - what
> ASGI backend are you using? What size messages are you sending? Have you
> tried running workers in separate processes?
>
> Andrew
>
> On Sun, Mar 5, 2017 at 5:26 AM, Avraham Serour <tov...@gmail.com
> <javascript:>> wrote:
>
>> I don't think you need 500 workers, the number of workers depends on how
>> long will message will take to be processed not the number of concurrent
>> connections.
>>
>> The worker job is to get a message and send to a bunch of clients, the
>> ASGI server, meaning the process actually holding the websocket, in your
>> case daphne, will actually upload the data.
>>
>> Is the client and server running on the same computer?
>>
>> Don't stress test your server manually, you should write a script to do
>> it.
>>
>> On Sun, Mar 5, 2017 at 1:28 PM, Lada B <lada...@gmail.com <javascript:>>
>> wrote:
>>
>>> HW performance with 1 user sending message every 100ms:
>>> https://i.imgur.com/5F4mKAI.png
>>>
>>>
>>> Yesterday i tried to use it in production and when there were 15 clients
>>> connected (each one pinging server every 2 seconds) nobody else could
>>> connect.
>>>
>>> I have default settings and I followed Getting started tutorial.
>>>
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