The "SSL handshake failed" doesn't seem related to the alleged memory leak.

Now, you say you have this problem only in production. If you restart uwsgi,
does memory usage go immediately up? Does it go after a few requests? How many
requests? Do you have the same data in development and production? If, for
example, your app loads a whole db table in memory, and this db table has a
million records in production and only a few in development, there would be a
difference.

Regards,

Antonis

Antonis Christofides
http://djangodeployment.com

On 2017-12-06 19:38, Etienne Robillard wrote:
> Hi Antonis,
>
> My development server appears unaffected by this problem. Plus I can get heap
> stats using guppy, which is pretty cool. :)
>
> Both my production and development servers have __debug__ enabled in Python
> 2.7.13.
>
> However when using ab -c 100 to benchmark my nginx server I get:
>
> SSL handshake failed (1).
>
> Do you have any ideas how to configure nginx to allow a minimum of 100
> concurrent connections when using SSL encryption?
>
> I have worker_connections set to 512 in my nginx.conf
>
> Regards,
>
> Etienne
>
>
> Le 2017-12-06 à 12:17, Antonis Christofides a écrit :
>> Does this happen only in production? What about when you run a development
>> server? What is the memory usage of your development server?
>>
>> Antonis Christofides
>> http://djangodeployment.com
>>
>>
>> On 2017-12-06 15:05, Etienne Robillard wrote:
>>> Hi Antonis,
>>>
>>> Thank you for your reply. I installed the htop utility and found that 2 of 
>>> my
>>> 4 uWSGI processes are using 882M (42.7%) of resident memory each. Theses two
>>> processes takes about  (85%) of the available RAM memory! That can explain 
>>> why
>>> I get "out of memory" errors when no more memory is available for sshd.
>>>
>>> I tried to debug memory allocation with guppy following instructions here:
>>> https://www.toofishes.net/blog/using-guppy-debug-django-memory-leaks/
>>>
>>> But I get "hp.Nothing" when I attempt to get the heap stats from the master
>>> uWSGI process.
>>>
>>> Example:
>>>>>> hp.setref()
>>>>>> hp.heap()
>>> hp.Nothing
>>>
>>> Any help would be appreciated!
>>>
>>> Etienne
>>>
>>>
>>> Le 2017-12-06 à 07:53, Antonis Christofides a écrit :
>>>> Hello,
>>>>
>>>> the amount of memory you need depends on what Django does and how many 
>>>> workers
>>>> (instances of Django) you run (which usually depends on how many requests 
>>>> you
>>>> are getting and how I/O intensive your Django application is). For many
>>>> applications, 512 MB is enough.
>>>>
>>>> Why are you worried? The only symptom you describe is that your free 
>>>> memory is
>>>> decreasing. This is absolutely normal. The operating system doesn't like 
>>>> RAM
>>>> that is sitting down doing nothing, so it will do its best to make free RAM
>>>> nearly zero. Whenever there's much RAM available, it uses more for its 
>>>> caches.
>>>>
>>>> How much memory is your Django app consuming? You can find out by executing
>>>> "top" and pressing "M" to sort by memory usage.
>>>>
>>>> Regards,
>>>>
>>>> Antonis
>>>>
>>>> Antonis Christofides
>>>> http://djangodeployment.com
>>>>
>>>> On 2017-12-06 14:04, Etienne Robillard wrote:
>>>>> Hi all,
>>>>>
>>>>> I'm struggling to understand how django/python may allocate and unallocate
>>>>> memory when used with uWSGI.
>>>>>
>>>>> I have a Debian system running Python 2.7 and uwsgi with 2GB of RAM and 2
>>>>> CPUs.
>>>>>
>>>>> Is that enough RAM memory for a uWSGI/Gevent based WSGI app running 
>>>>> Django?
>>>>>
>>>>> I'm running uWSGI with the --gevent switch in order to allow cooperative
>>>>> multithreading, but my free RAM memory is always decreasing when nginx is
>>>>> running.
>>>>>
>>>>> How can I debug memory allocation in a Django/uWSGI app?
>>>>>
>>>>> I defined also in my sitecustomize.py "gc.enable()" to allow garbage
>>>>> collection, but it does not appears to make any differences.
>>>>>
>>>>> Can you recommend any libraries to debug/profile memory allocation in 
>>>>> Python
>>>>> 2.7 ?
>>>>>
>>>>> Is Django more memory efficient with --pymalloc or by using the default 
>>>>> linux
>>>>> malloc() ?
>>>>>
>>>>> Thank you in advance,
>>>>>
>>>>> Etienne
>>>>>
>

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