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flask-docker-celery-rabbitmq-nginx-gunicorn's Introduction

flask-docker-celery-rabbitmq-nginx-gunicorn

This repository is for running a simple dummy flask application in a docker environment.

It uses:

  • Flask
  • Celery
  • Flower
  • Rabbitmq
  • PostgreSQL (not doing anything, though)
  • Nginx
  • Gunicorn

Prerequisites

Make sure you have docker and docker-compose installed.

Running

Clone this repository and navigate into it in your terminal. Run in development mode, so set APP_ENV environment to Dev

APP_ENV=Dev docker-compose up --build

It will expose 2 ports, one for the flask application (8888) and one for the RabbitMQ management interface (15672). It will also start 2 worker containers.

When it runs, you can test it with several curl posts request and check it running in the Flower interface.

for value in {1..50}
do
    curl --data '{json}' -H 'Content-Type: application/json' 0.0.0.0:8888/api/process_data
done

This will run 50 tasks, you can see in the flower http://localhost:5555 how the tasks are distributed between the worker instances. Plus, you can run tasks by executing stress.sh

You can also check the status of a specific task in flask: http://localhost:8888/api/tasks/<task-id>

The RabbitMQ interface http://localhost:15673 with login:

  • username: rabbit_user
  • password: rabbit_password

핵심 내용

image

  • 주어진 그림과 같이 프로토콜을 통해 요청이 어떤 방식으로 프로세스에게 전달되는 지 이해하기
  • 하나의 컨테이너 내부에서 마스터 프로세스와 워커 프로세스가 어떤 방식으로 작동하는 지 이해하기
  • docker compose를 통해서 컨테이너를 실행한 뒤에 stress.sh 스크립트를 통해 전달된 요청이 어떻게 비동치 처리 되는지 이해하기
    • stress.sh를 통해 nginx로 api(HTTP) 요청 전달
    • nginx 내부의 워커 프로세스의 태스크 큐로 os가 해당 요청을 전달
    • 워커 프로세스가 해당 요청이 정적 요청인지 동적 요청인지 판단한 뒤에 필요할 시에 WAS 서버로 요청 전달(HTTP)
    • Gunicorn의 마스터 프로세스가 HTTP 요청을 WSGI 요청으로 변환한 뒤에 해당 요청을 워커 프로세스에게 전달
    • 워커 프로세스는 비동기 처리가 필요할 시에 AMQP 프로토콜을 통해 RabbitMQ에게 메세지를 전달
    • RabbitMQ는 Celery에게 메세지를 전달
    • Celery의 태스크큐에 메세지가 전달되면, Celery 내부에 있는 워커 프로세스에게 해당 메세지가 전달
    • 최종적으로 Celery의 워커 프로세스가 해당 메세지를 처리
    • 이때 클라이언트는 곧바로 해당 태스크가 시작됐음을 알리는 태스크 아이디만을 반환 받음
    • 이후에 태스크 아이디를 통해서 결과값을 조회하도록 만들 수 있음
    • 최종적으로 셀러리와 래빗앰큐가 작동하는 모습을 모니터링 툴을 통해서 직접 관찰해볼 것

flask-docker-celery-rabbitmq-nginx-gunicorn's People

Contributors

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Forkers

aristo0922

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