Hello,

What does the math say at peak times?  100,000,000 is a lot in a day, and
it would not take much disturbance to spike requests.

I assume the clients are not slow?  Hanging clients consume a valuable
thread.  We use nginx buffering request/response to mitigate that and free
up thread as soon as possible.

Keep in mind python gil will bottleneck threads if your processes are at
all cpu bound...  I might consider more processes and less threads per
process.

Any pattern around when you get 5xx errors?   Can you spin up 20 extra
instances for an hour to see if that cures them?

Just some thoughts...
Jason






On Mon, Feb 17, 2020, 9:13 PM Andrew Charles <[email protected]>
wrote:

> Ubuntu 18.04.04
> Apache 2.4.29 (event)
> mod_wsgi 4.5.17
> Python 3.6.8
> Django 2.2.10
>
> WSGIScriptAlias / ...wsgi.py
> WSGIDaemonProcess name processes=8 threads=30 queue-timeout=45 socket-
> timeout=60 request-timeout=60 inactivity-timeout=0 startup-timeout=45
> deadlock-timeout=60 graceful-timeout=15 eviction-timeout=0 python-path=...
> base/ python-home=...virtualenv/
> WSGIProcessGroup name
>
>
> AWS ec2 c5.xlarge 4 CPUs 8GB Mem (ASG autoscaling between 4 and 10
> instances) behind an ELB
> Averaging 100,000,000 requests per day (107 mil today)
>
> We have a few django api endpoints that are very simple, which only hit a
> local or separate redis cache, no db hits. We relay data to firehose but
> use django-q to offload those tasks. Requests take around 200ms but a fair
> number are 400-500ms. The ELB reports the average as 60ms. Each instances
> uses between 4-5GB mem. I've been trying to get more performance out of our
> instances and reduce our 5XXs. I previously tried 3 processes and the
> default (15) threads. I've been researching the best ways to change
> settings but it seems like it's unique to every setup and there's no easy
> rules to follow. I'm looking for suggestions or at least someone to tell me
> I'm on the right track.
>
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