What you'll learn
Gain complete understanding of the apache airflow
Learn different types of Executors and it's working principles
Own a scalable distributed airflow setup which could be shared by multi teams in your organisation

Requirements
Python >= 2.7

Description
Airflow is a platform created by the community to programmatically author, schedule and monitor workflows. Airflow is one of the best open source orchestrators and it is used widely because it is simplicity, scalability and extensibility.

Main goal of this course is to achieve an Airflow distributed setup using Celery Executor and be able to run more than 100 jobs or DAGs in parallel at any instance in time. I cover Sequential, Local and Celery Executor in this course. We acquire few EC2 instances from AWS and configure these executors.

In addition to this, we explore salient features like Login, Email alerting and Logs management.

By the end of this course, you own a great distributed airflow setup which could be shared by multi teams in your organisation.

Who this course is for:
Curious on Big Data Technologies

Citación :

https://rapidgator.net/file/7fc74f82b24a721d2a4f75a3f91670f6/pme1g.Apache.Airflow..Complete.Distributed.Configuration.rar.html


https://nitroflare.com/view/91E097BBC8EADCD/pme1g.Apache.Airflow..Complete.Distributed.Configuration.rar


https://uploadgig.com/file/download/e0ae6E5B0206ce8f/pme1g.Apache.Airflow..Complete.Distributed.Configuration.rar