fix OOM kills by reducing worker counts, cuts memory utilization

[irvingpop]

Description of changes

we were using way too much memory and racking up oomkills.

Before:
1 gunicorn master + 3 gunicorn workers + 2 django_q workers = 6 processes per container
At ~65 MB average: ~390 MB per container
Two containers (prod + staging): ~780 MB

After:
1 gunicorn master + 1 gunicorn worker + 1 django_q worker = 3 processes per container
At ~65 MB average: ~195 MB per container
Two containers: ~390 MB (~50% reduction!)

[irvingpop]

confirmed memory use reduction in staging:

Gunicorn:
  40.8 MB - gunicorn master
  49.5 MB - gunicorn worker
  ------
  90.3 MB subtotal

Django-Q:
  27.3 MB - qcluster (monitor/sentinel)
  22.3 MB - qcluster (process)
  25.2 MB - qcluster (worker - active)
  16.8 MB - qcluster (pusher)
  16.8 MB - qcluster (guard)
  ------
 108.4 MB subtotal

Total per container: ~199 MB PSS