It is resident memory (RSS), not virtual memory which is more important to know.

> On 20 Feb 2020, at 11:06 am, Andrew Charles <[email protected]> wrote:
> 
> The default one, and a2query -M outputs event. I haven't changed any apache 
> settings like MaxMemFree.
> 
> In htop each mod_wsgi proc takes ~960M VIRT, each apache proc takes 
> ~1980-2060M VIRT
> 
> I've been testing out different procs/threads and 10 procs with 5 threads 
> seems to be the same as 8 procs with 30 threads.
> 
> I'll see what the logs output with info.
> 
> On Wednesday, February 19, 2020 at 3:10:53 PM UTC-7, Graham Dumpleton wrote:
> What Apache MPM are you using? What are the MPM settings in Apache? Eg:
> 
> * https://httpd.apache.org/docs/2.4/mod/event.html 
> <https://www.google.com/url?q=https%3A%2F%2Fhttpd.apache.org%2Fdocs%2F2.4%2Fmod%2Fevent.html&sa=D&sntz=1&usg=AFQjCNFEqVlH2ExZTHClVfVyHthuG78oYg>
> 
> Is MaxMemFree directive set in Apache configuration?
> 
> How much memory does each mod_wsgi daemon process take?
> 
> How much memory does each normal Apache child process take?
> 
> Do you have log level set to info so you know how often mod_wsgi daemon 
> processes are getting restarted due to request timeouts?
> 
> Graham
> 
>> On 20 Feb 2020, at 8:36 am, Andrew Charles <andrew...@ <>antyc.ca 
>> <http://antyc.ca/>> wrote:
>> 
>> Upping the processes increases the memory usage quite a lot. I tried 16 
>> procs and 15 threads and ran out.
>> 
>> On Monday, February 17, 2020 at 7:13:24 PM UTC-7, Andrew Charles 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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