将Django频道部署到Elastic Beanstalk Python3.4环境

Question

过去几天我花了很多时间将频道实现到我的Django应用程序中,以便使用Channel的websocket支持.我的Django项目是用Python 3.4编写的,我使用的是DaphneChannel的redis后端.

通过将Supervisord包装在Python2 virtualenv中并使用它来运行在Python3 virtualenv中启动Daphne/Redis/workers的脚本,但是没有成功部署到我们的Elastic Beanstalk(Python 3.4)环境,我已经能够在本地运行一切.

有没有办法设置我的EB部署配置在Python2 virtualenv中运行Supervisor,就像我可以在本地？如果没有,我怎样才能让Daphne,redis和我的员工在EB部署上运行？如果有必要,我愿意转换流程管理员,但发现Supervisor的语法比Circus更容易理解/实现,并且我不知道任何其他可行的替代方案.

有了这个配置,我能够成功地部署到我的EB环境和ssh进去,但主管无法启动每一个过程,如果我尝试手动启动监督员检查的过程中supervisorctl status给了我FATAL "Exited too quickly (process log may have details)的一切,我尝试初始化.日志是空的.

频道后端配置:

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()

主管conf(其余的conf文件保留默认值):

[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

我松散地遵循这个指南但是因为它是为python2 EB环境编写的,所以它实际上只对ALB设置和基本管理程序配置有用.

感谢大家阅读本文,如果我能通过代码/输出等方式提供其他任何内容,请告诉我.

Answer 1

因此，感谢 Berlin 的回答提供的日志记录建议，以及 AWS 支持团队建议的虚拟环境调整（我将这个问题转发给他们），我终于能够让它发挥作用。

首先，我最终完全Redis从 Supervisor 中删除，而是选择运行 ElastiCache Redis 实例，然后将其连接到我的 EB 实例。我不认为这是处理这个问题的唯一方法，但这是我实施的最佳途径。

然后，我不再使用预先存在的start_supervisor.sh脚本，而是向channels.configebextension 添加了一个命令来创建脚本并将其添加到 EB 的部署后操作中。这是必要的，因为.ebextension配置文件是在部署期间运行的，但不会在环境创建之后存在（这可能不完全正确，但为了这个解决方案，这就是我对它们的看法），所以即使我的脚本大部分是正确的一旦部署完成，它启动的 Supervisor 进程就会立即终止。

所以我.ebextensions/channels.config现在是：

container_commands:
  01_create_post_dir:
    command: "mkdir /opt/elasticbeanstalk/hooks/appdeploy/post"
    ignoreErrors: true
files:
  "/opt/elasticbeanstalk/hooks/appdeploy/post/start_supervisor.sh":
    mode: "000755"
    owner: root
    group: root
    content: |
      #!/usr/bin/env bash
      virtualenv -p /usr/bin/python2.7 /tmp/senv
      source /tmp/senv/bin/activate && source /opt/python/current/env
      python --version > /tmp/version_check.txt
      sudo pip install supervisor
      /usr/local/bin/supervisord -c /opt/python/current/app/<app>/supervisord.conf
      supervisorctl -c /opt/python/current/app/<app>/supervisord.conf status

仅此一项就足以让 Supervisor 在 EB 部署上运行，但我必须进行更多更改才能让 Daphne 和我的 Django 工作人员保持活力：

启动_daphne.sh：

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

start_worker.sh：

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

AWS 支持人员建议我添加&& source /opt/python/current/envvirtualenv 激活命令，因为 env 变量不会自动拉入 virtualenv，这会导致 Daphne 和工作人员因导入错误而在创建时死亡。

我还对我的supervisord.conf文件做了一些更改：

[unix_http_server]
file=/tmp/supervisor.sock   ; (the path to the socket file)

[supervisord]
logfile=/tmp/supervisord.log ; supervisord log file
loglevel=error ; info, debug, warn, trace
logfile_maxbytes=50MB        ; (max main logfile bytes b4 rotation;default 50MB)
logfile_backups=10           ; (num of main logfile rotation backups;default 10)
pidfile=/tmp/supervisord.pid ; (supervisord pidfile;default supervisord.pid)
nodaemon=false               ; (start in foreground if true;default false)
minfds=1024                  ; (min. avail startup file descriptors;default 1024)
minprocs=200                 ; (min. avail process descriptors;default 200)

; the below section must remain in the config file for RPC
; (supervisorctl/web interface) to work, additional interfaces may be
; added by defining them in separate rpcinterface: sections
[rpcinterface:supervisor]
supervisor.rpcinterface_factory = supervisor.rpcinterface:make_main_rpcinterface

[supervisorctl]
serverurl=unix:///tmp/supervisor.sock ; use a unix:// URL  for a unix socket

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

[program:Worker]
environment=PATH="/opt/python/run/venv/bin"
command=sh /opt/python/current/app/<app>/start_worker.sh --log-file /tmp/start_worker.log
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
stderr_logfile=/tmp/workers.err.log