: Controls how the scheduler identifies and kicks off tasks. Important settings include dag_dir_list_interval , which determines how often the scheduler scans for new DAG files.
: Contains foundational settings like dags_folder (where Airflow scans for workflows) and executor (the mechanism that actually runs your tasks, such as SequentialExecutor or CeleryExecutor ). airflow cfg.zip
The airflow.cfg file is the central command center for , a Python-based platform used to author, schedule, and monitor complex workflows. This configuration file dictates everything from how many tasks can run simultaneously to where your DAGs (Directed Acyclic Graphs) are stored. Core Purpose and Location : Controls how the scheduler identifies and kicks off tasks
: The hardcoded defaults within the Airflow source code if no other value is provided. Performance Tuning data-engineering/airflow/airflow.cfg at main - GitHub The airflow
: You can override any config setting using the format AIRFLOW__{SECTION}__{KEY} (e.g., AIRFLOW__CORE__PARALLELISM ). airflow.cfg : The settings defined in the physical file.
: Configures the connection to the metadata database where Airflow stores state information about tasks and DAG runs. Precedence and Overrides