Airflow remains a popular choice when it comes to open-source orchestration tools.
When I surveyed people about a year ago now, it was the most popular open-source solution, and still to this day, my video on “Should You Use Airflow” drives a lot of prospect conversations.
Now, I do want to say that there are plenty of organizations using Azure Data Factory and Informatica, and there are plenty of competitors knocking on Airflow's door.
But for now, Airflow is like the PHP of the data world; people can talk poorly about it, but it continues to be heavily relied upon.
Now, as I said, Airflow is often why I get brought into many projects, meaning I have seen many different ways that teams decide to deploy Airflow.
Some scaled, others didn’t.
Thus, I wanted to take a moment and discuss some ways I have seen Airflow deployed in the past and the challenges people faced as they deployed their code.
If your team is looking to deploy Airflow, or needs help setting up Airflow, then set up a consultation here - calendly.com/ben-rogojan/cons...
Also, if you'd like to learn about an alternative to Airflow, you can check out Mage.ai(bit.ly/41h6Pjy)
This video isn't sponsored by them, but I am an advisor for mage.ai
0:00 - Intro
1:44 - Mistake #1 Putting The DAG Folder In The Same Repo As The Webserver
4:58 - Mistake #2 Not Using All The Features Airflow Offers
8:43 - Mistake #3 Not Thinking About Scale
Looking for an alternative to Airflow, check out this article!
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About me:
I have spent my career focused on all forms of data. I have focused on developing algorithms to detect fraud, reduce patient readmission and redesign insurance provider policy to help reduce the overall cost of healthcare. I have also helped develop analytics for marketing and IT operations in order to optimize limited resources such as employees and budget. I privately consult on data science and engineering problems both solo as well as with a company called Acheron Analytics. I have experience both working hands-on with technical problems as well as helping leadership teams develop strategies to maximize their data.
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29 июл 2024
