Deploying Django Channels to Elastic Beanstalk Python3.4 environment

I have spent the past few days implementing Channels into my Django app in order to use Channel's websocket support. My Django project is written in Python 3.4 and I am using Daphne and Channel's redis backend.

I have been able to get everything functioning locally by wrapping Supervisord in a Python2 virtualenv and using it to run scripts that start Daphne/Redis/workers inside a Python3 virtualenv, but have had no success deploying to our Elastic Beanstalk (Python 3.4) environment.

Is there any way to set up my EB deployment configs to run Supervisor in a Python2 virtualenv, like I can locally? If not, how can I go about getting Daphne, redis, and my workers up and running on EB deploy? I am willing to switch process managers if necessary, but have found Supervisor's syntax to be easier to understand/implement than Circus, and am not aware of any other viable alternatives.

With this configuration, I am able to successfully deploy to my EB environment and ssh into it, but Supervisor fails to start every process, and if I try to start Supervisor manually to check on the processes supervisorctl status gives me FATAL "Exited too quickly (process log may have details) for everything I try to initialize. The logs are empty.

Channels backend config:

CHANNEL_LAYERS = {
    "default": {
        "BACKEND": "asgi_redis.RedisChannelLayer",
        "ROUTING": "<app>.routing.channel_routing",
        "CONFIG": {
            "hosts": [
                os.environ.get('REDIS_URL', 'redis://localhost:6379')
            ],
        },
    },
}

asgi.py:

import os
from channels.asgi import get_channel_layer

os.environ.setdefault("DJANGO_SETTINGS_MODULE", "<app>.settings")

channel_layer = get_channel_layer()

supervisor conf (rest of the conf file was left default):

[program:Redis]
environment=PATH="/opt/python/run/venv/bin"
command=sh /opt/python/current/app/<app>/start_redis.sh
directory=/opt/python/current/app
autostart=true
autorestart=true
redirect_stderr=true
stdout_logfile=/tmp/redis.out.log

[program:Daphne]
environment=PATH="/opt/python/run/venv/bin"
command=sh /opt/python/current/app/<app>/start_daphne.sh
directory=/opt/python/current/app
autostart=true
autorestart=true
redirect_stderr=true
stdout_logfile=/tmp/daphne.out.log

[program:Worker]
environment=PATH="/opt/python/run/venv/bin"
command=sh /opt/python/current/app/<app>/start_worker.sh
directory=/opt/python/current/app
process_name=%(program_name)s_%(process_num)02d
numprocs=4
autostart=true
autorestart=true
redirect_stderr=true
stdout_logfile=/tmp/workers.out.log

.ebextensions/channels.config:

container_commands:
  01_start_supervisord:
    command: "sh /supervisord/start_supervisor.sh"

start_supervisor.sh:

#!/usr/bin/env bash
virtualenv -p /usr/bin/python2.7 /tmp/senv
source /tmp/senv/bin/activate
sudo pip install supervisor
sudo /usr/local/bin/supervisord -c 
/opt/python/current/app/<app>/supervisord.conf
supervisorctl -c /opt/python/current/app/<app>/supervisord.conf status

start_redis:

#!/usr/bin/env bash
sudo wget http://download.redis.io/releases/redis-3.2.8.tar.gz
sudo tar xzf redis-3.2.8.tar.gz
cd redis-3.2.8
sudo make
source /opt/python/run/venv/bin/activate
sudo src/redis-server

start_daphne:

#!/usr/bin/env bash
source /opt/python/run/venv/bin/activate
/opt/python/run/venv/bin/daphne -b 0.0.0.0 -p 5000 <app>.asgi:channel_layer

start_worker:

#!/usr/bin/env bash
source /opt/python/run/venv/bin/activate
python manage.py runworker

I was loosely following this guide but since it was written for a python2 EB environment it is really only good for the ALB setup and base supervisor configuration.

Thank you guys for reading this, and please let me know if I can provide anything else by way of code/output etc.