如何使用AWS Elastic Beanstalk可扩展的Django app运行芹菜工作者？

Question

如何使用django与Elastic Benastalk,它也只能在主节点上通过芹菜运行任务？

Answer 1

这就是我在弹性豆茎上用django设置芹菜的方法,可扩展性很好.

请记住,"leader_only"的选项container_commands仅适用于环境重建或部署的应用程式.如果服务工作时间足够长,则可以通过Elastic Beanstalk删除领导节点.要解决此问题,您可能必须为领导节点应用实例保护.检查:http://docs.aws.amazon.com/autoscaling/latest/userguide/as-instance-termination.html#instance-protection-instance

为芹菜工人添加bash脚本并节拍配置.

添加文件root_folder/.ebextensions/files/celery_configuration.txt:

#!/usr/bin/env bash

# Get django environment variables
celeryenv=`cat /opt/python/current/env | tr '\n' ',' | sed 's/export //g' | sed 's/$PATH/%(ENV_PATH)s/g' | sed 's/$PYTHONPATH//g' | sed 's/$LD_LIBRARY_PATH//g' | sed 's/%/%%/g'`
celeryenv=${celeryenv%?}

# Create celery configuraiton script
celeryconf="[program:celeryd-worker]
; Set full path to celery program if using virtualenv
command=/opt/python/run/venv/bin/celery worker -A django_app --loglevel=INFO

directory=/opt/python/current/app
user=nobody
numprocs=1
stdout_logfile=/var/log/celery-worker.log
stderr_logfile=/var/log/celery-worker.log
autostart=true
autorestart=true
startsecs=10

; Need to wait for currently executing tasks to finish at shutdown.
; Increase this if you have very long running tasks.
stopwaitsecs = 600

; When resorting to send SIGKILL to the program to terminate it
; send SIGKILL to its whole process group instead,
; taking care of its children as well.
killasgroup=true

; if rabbitmq is supervised, set its priority higher
; so it starts first
priority=998

environment=$celeryenv

[program:celeryd-beat]
; Set full path to celery program if using virtualenv
command=/opt/python/run/venv/bin/celery beat -A django_app --loglevel=INFO --workdir=/tmp -S django --pidfile /tmp/celerybeat.pid

directory=/opt/python/current/app
user=nobody
numprocs=1
stdout_logfile=/var/log/celery-beat.log
stderr_logfile=/var/log/celery-beat.log
autostart=true
autorestart=true
startsecs=10

; Need to wait for currently executing tasks to finish at shutdown.
; Increase this if you have very long running tasks.
stopwaitsecs = 600

; When resorting to send SIGKILL to the program to terminate it
; send SIGKILL to its whole process group instead,
; taking care of its children as well.
killasgroup=true

; if rabbitmq is supervised, set its priority higher
; so it starts first
priority=998

environment=$celeryenv"

# Create the celery supervisord conf script
echo "$celeryconf" | tee /opt/python/etc/celery.conf

# Add configuration script to supervisord conf (if not there already)
if ! grep -Fxq "[include]" /opt/python/etc/supervisord.conf
  then
  echo "[include]" | tee -a /opt/python/etc/supervisord.conf
  echo "files: celery.conf" | tee -a /opt/python/etc/supervisord.conf
fi

# Reread the supervisord config
supervisorctl -c /opt/python/etc/supervisord.conf reread

# Update supervisord in cache without restarting all services
supervisorctl -c /opt/python/etc/supervisord.conf update

# Start/Restart celeryd through supervisord
supervisorctl -c /opt/python/etc/supervisord.conf restart celeryd-beat
supervisorctl -c /opt/python/etc/supervisord.conf restart celeryd-worker

在部署期间注意脚本执行,但仅限于主节点(leader_only:true).添加文件root_folder/.ebextensions/02-python.config:

container_commands:
  04_celery_tasks:
    command: "cat .ebextensions/files/celery_configuration.txt > /opt/elasticbeanstalk/hooks/appdeploy/post/run_supervised_celeryd.sh && chmod 744 /opt/elasticbeanstalk/hooks/appdeploy/post/run_supervised_celeryd.sh"
    leader_only: true
  05_celery_tasks_run:
    command: "/opt/elasticbeanstalk/hooks/appdeploy/post/run_supervised_celeryd.sh"
    leader_only: true

• Beat是可配置的,无需重新部署,具有单独的django应用程序:https://pypi.python.org/pypi/django_celery_beat.
• 存储任务结果是个好主意:https://pypi.python.org/pypi/django_celery_beat

文件requirements.txt

celery==4.0.0
django_celery_beat==1.0.1
django_celery_results==1.0.1
pycurl==7.43.0 --global-option="--with-nss"

为Amazon SQS代理配置celery(从列表中获取所需的端点:http://docs.aws.amazon.com/general/latest/gr/rande.html) root_folder/django_app/settings.py:

...
CELERY_RESULT_BACKEND = 'django-db'
CELERY_BROKER_URL = 'sqs://%s:%s@' % (aws_access_key_id, aws_secret_access_key)
# Due to error on lib region N Virginia is used temporarily. please set it on Ireland "eu-west-1" after fix.
CELERY_BROKER_TRANSPORT_OPTIONS = {
    "region": "eu-west-1",
    'queue_name_prefix': 'django_app-%s-' % os.environ.get('APP_ENV', 'dev'),
    'visibility_timeout': 360,
    'polling_interval': 1
}
...

django django_app应用程序的芹菜配置

添加文件root_folder/django_app/celery.py:

from __future__ import absolute_import, unicode_literals
import os
from celery import Celery

# set the default Django settings module for the 'celery' program.
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'django_app.settings')

app = Celery('django_app')

# Using a string here means the worker don't have to serialize
# the configuration object to child processes.
# - namespace='CELERY' means all celery-related configuration keys
#   should have a `CELERY_` prefix.
app.config_from_object('django.conf:settings', namespace='CELERY')

# Load task modules from all registered Django app configs.
app.autodiscover_tasks()

修改文件root_folder/django_app/__ init__.py:

from __future__ import absolute_import, unicode_literals

# This will make sure the app is always imported when
# Django starts so that shared_task will use this app.
from django_app.celery import app as celery_app

__all__ = ['celery_app']

检查还:

• 如何使用AWS Elastic Beanstalk运行工作人员？(无可扩展性的解决方案)
• Pip Requirements.txt --global-option导致其他包的安装错误."选项未被识别" (来自弹性beanstalk的绝对点的问题的解决方案,无法处理正确解决pycurl依赖性的全局选项)

Answer 2

这就是我通过@smentek扩展答案的方式，以允许多个工作人员实例和单个节拍实例-在必须保护领导者的地方也有同样的事情。（我还没有一个自动化的解决方案）。

请注意，直到重新启动应用程序服务器之前，通过EB cli或Web界面对EB进行的envvar更新不会被芹菜节拍或工作程序影响。这一次让我措手不及。

单个celery_configuration.sh文件输出两个脚本供supervisor使用，请注意celery-beat具有autostart=false，否则在实例重启后您将获得许多节拍：

# get django environment variables
celeryenv=`cat /opt/python/current/env | tr '\n' ',' | sed 's/export //g' | sed 's/$PATH/%(ENV_PATH)s/g' | sed 's/$PYTHONPATH//g' | sed 's/$LD_LIBRARY_PATH//g' | sed 's/%/%%/g'`
celeryenv=${celeryenv%?}

# create celery beat config script
celerybeatconf="[program:celeryd-beat]
; Set full path to celery program if using virtualenv
command=/opt/python/run/venv/bin/celery beat -A lexvoco --loglevel=INFO --workdir=/tmp -S django --pidfile /tmp/celerybeat.pid

directory=/opt/python/current/app
user=nobody
numprocs=1
stdout_logfile=/var/log/celery-beat.log
stderr_logfile=/var/log/celery-beat.log
autostart=false
autorestart=true
startsecs=10

; Need to wait for currently executing tasks to finish at shutdown.
; Increase this if you have very long running tasks.
stopwaitsecs = 10

; When resorting to send SIGKILL to the program to terminate it
; send SIGKILL to its whole process group instead,
; taking care of its children as well.
killasgroup=true

; if rabbitmq is supervised, set its priority higher
; so it starts first
priority=998

environment=$celeryenv"

# create celery worker config script
celeryworkerconf="[program:celeryd-worker]
; Set full path to celery program if using virtualenv
command=/opt/python/run/venv/bin/celery worker -A lexvoco --loglevel=INFO

directory=/opt/python/current/app
user=nobody
numprocs=1
stdout_logfile=/var/log/celery-worker.log
stderr_logfile=/var/log/celery-worker.log
autostart=true
autorestart=true
startsecs=10

; Need to wait for currently executing tasks to finish at shutdown.
; Increase this if you have very long running tasks.
stopwaitsecs = 600

; When resorting to send SIGKILL to the program to terminate it
; send SIGKILL to its whole process group instead,
; taking care of its children as well.
killasgroup=true

; if rabbitmq is supervised, set its priority higher
; so it starts first
priority=999

environment=$celeryenv"

# create files for the scripts
echo "$celerybeatconf" | tee /opt/python/etc/celerybeat.conf
echo "$celeryworkerconf" | tee /opt/python/etc/celeryworker.conf

# add configuration script to supervisord conf (if not there already)
if ! grep -Fxq "[include]" /opt/python/etc/supervisord.conf
  then
  echo "[include]" | tee -a /opt/python/etc/supervisord.conf
  echo "files: celerybeat.conf celeryworker.conf" | tee -a /opt/python/etc/supervisord.conf
fi

# reread the supervisord config
/usr/local/bin/supervisorctl -c /opt/python/etc/supervisord.conf reread
# update supervisord in cache without restarting all services
/usr/local/bin/supervisorctl -c /opt/python/etc/supervisord.conf update

然后在container_commands中，我们仅在leader上重新启动beat：

container_commands:
  # create the celery configuration file
  01_create_celery_beat_configuration_file:
    command: "cat .ebextensions/files/celery_configuration.sh > /opt/elasticbeanstalk/hooks/appdeploy/post/run_supervised_celeryd.sh && chmod 744 /opt/elasticbeanstalk/hooks/appdeploy/post/run_supervised_celeryd.sh && sed -i 's/\r$//' /opt/elasticbeanstalk/hooks/appdeploy/post/run_supervised_celeryd.sh"
  # restart celery beat if leader
  02_start_celery_beat:
    command: "/usr/local/bin/supervisorctl -c /opt/python/etc/supervisord.conf restart celeryd-beat"
    leader_only: true
  # restart celery worker
  03_start_celery_worker:
    command: "/usr/local/bin/supervisorctl -c /opt/python/etc/supervisord.conf restart celeryd-worker"