DDrona4U
Sign inCreate account
My learningAPACHE AIRFLOW INTERVIEW QUESTIONSLesson 04
Airflow Core Components Explained – Webserver, Scheduler, Executor, and Metadata Database

Lesson 04

Airflow Core Components Explained – Webserver, Scheduler, Executor, and Metadata Database

Learn the four core components of Apache Airflow—Webserver, Scheduler, Executor, and Metadata Database—and understand how they work together to manage, schedule, execute, and monitor workflow pipelines efficiently.

Get the full lesson

Sign in to unlock everything beyond the preview — it's free.

  • Take timestamped notes as you watch
  • Read the full transcript and download resources
  • Join the discussion and track your progress
Sign inCreate free account

Curriculum

20 lessons · 40m

0/20 lessons done40m left
  1. 0102:05

    Apache Airflow – What It Is and the Problem It Solves

    02:05

  2. 0202:13

    Airflow vs Cron vs Jenkins – Why Choose Airflow?

    02:13

  3. 0302:07

    What Is a DAG in Airflow and Why Must It Be Acyclic?

    02:07

  4. 01:51

    Airflow Core Components Explained – Webserver, Scheduler, Executor, and Metadata Database

    01:51

  5. 0501:59

    Task vs Operator vs Task Instance in Airflow – Key Differences

    01:59

  6. 0601:55

    Airflow – Data Processing Tool or Orchestration Tool

    01:55

  7. 0701:54

    Airflow DAG Files – Format and Where Airflow Finds Them

    01:54

  8. 0802:01

    Idempotent Tasks in Airflow – Meaning and Importance

    02:01

  9. 0902:10

    Airflow vs Prefect vs Dagster – When to Choose Each

    02:10

  10. 1002:08

    Common Real-World Use Cases of Apache Airflow

    02:08

  11. 1101:56

    Anatomy of a Simple Airflow DAG File – Section by Section

    01:56

  12. 1201:58

    Defining Task Dependencies in Airflow Using >>, <<, and set_upstream()

    01:58

  13. 1301:47

    start_date vs execution_date vs logical_date in Airflow

    01:47

  14. 1401:56

    Airflow Catchup Explained – When to Set catchup=False

    01:56

  15. 1501:48

    No Dependency Between Tasks in Airflow – What Happens?

    01:48

  16. 1602:07

    Organizing Large Airflow DAGs – Keeping 50+ Tasks Readable

    02:07

  17. 1701:54

    Dynamic Task Mapping in Airflow with .expand() – Real-World Use Case

    01:54

  18. 1802:09

    Creating Multiple Airflow DAGs Programmatically from a Config File

    02:09

  19. 1902:05

    Maximum Tasks in an Airflow DAG and Its Impact on Scheduler Performance

    02:05

  20. 2001:56

    Why Choose Apache Airflow Over Cron Jobs or Jenkins?

    01:56