Mastering Airflow Variables

The way you retrieve variables from Airflow can impact the performance of your DAGs

Photo by Daniele Franchi on Unsplash

What happens if multiple data pipelines need to interact with the same API endpoint? Would you really have to declare this endpoint in every pipeline? In case this endpoint changes in the near future, you will have to update its value in every single file.

Airflow variables are simple yet valuable construct, used to prevent redundant declarations across multiple DAGs. They are simply objects consisting of a key and a JSON serialiasable value, stored in Airflow’s metadata database.

And what if your code uses tokens or other type of secrets? Hardcoding them in plain-text doesn’t seem to be a secure approach. Beyond reducing repetition, Airflow variables also aid in managing sensitive information. With six different ways to define variables in Airflow, selecting the appropriate method is crucial for ensuring security and portability.

An often overlooked aspect is the impact that variable retrieval has on Airflow performance. It can potentially strain the metadata database with requests, every time the Scheduler parses the DAG files (defaults to thirty seconds).

It’s fairly easy to fall into this trap, unless you understand how the Scheduler parses DAGs and how Variables are retrieved from the database.