In this part of the series I will cover how to get a nice Apache Airflow instance up and running with docker. You won't need to have anything installed locally besides docker, which is fantastic, because configuring all these pieces individually would be kind of awful!
This is the exact same setup and configuration I use for my own Apache Airflow instances. When I run Apache Airflow in production I don't use Postgres in a docker container, as that is not recommended, but this setup is absolutely perfect for dev and will very closely match your production requirements!
Following along with a blog post is great, but the best way to learn is to just jump in and start building. Get the Apache Airflow Docker Dev Stack here.
Getting an instance Apache Airflow up and running looks very similar to a Celery instance. This is because Airflow uses Celery behind the scenes to execute tasks. Read more...
In Part 1 of this series we went over the Celery Architecture, how to separate out the components in a docker-compose file, and laid the ground for deployment.
This portion of the blog post assumes you have a ssh key setup. If you don't go to the AWS docs here.
AWS CloudFormation is an infrastructure design tool that allows users to design their infrastructure by defining file systems, compute requirements, networking, etc. If you have no interest in designing infrastructure, y0u probably don't need to worry. Cloudformation configurations are shareable through templates.
Docker has come to our rescue here, with a Docker for AWS CloudFormation template. This will, with the click of a few buttons, deploy a docker swarm on AWS for us!!
Click on the page, and scroll down to quick start. Under 'Stable Channel' select '...
In this post I will hopefully show you how to organize a large docker-compose project, specifically a project related to a job queue. In this instance we will use Celery, but hopefully you can see how the concepts relate to any project with a job queue, or just a large number of moving pieces.
This post will be in two parts. The first will give a very brief overview of celery, the architecture of a celery job queue, and how to setup a celery task, worker, and celery flower interface with docker and docker-compose. Part 2 will go over deployment using docker-swarm.
Celery is a distributed job queuing system that allows us queue up oodles of tasks, and execute them as we have resources.
From celeryproject.org -
Celery is an asynchronous task queue/job queue based on distributed message passing.It is focused on real-time operation, but supports scheduling as well.The execution units, called tasks, are executed...