Apache Airflow Architecture | Key Components

Apache Airflow is built on a modular architecture that supports scalable and flexible workflow orchestration.
The Scheduler monitors DAGs and triggers tasks based on time or event.
The Executor and Workers handle task execution across different environments.
The Web Server (UI) provides a visual interface to manage and monitor workflows.
All metadata, including DAGs and task states, is stored in the Metadata Database.

1. Apache Airflow Architecture & Key Components

2. 1️⃣ Scheduler Triggers tasks based on defined schedules and dependencies. Monitors DAGs and queues tasks for execution.

3. 2️⃣ Executor Handles how and where tasks are executed (e.g., Local, Celery, Kubernetes). Works closely with the scheduler.

4. 3️⃣ Workers Execute individual tasks as directed by the executor. Scalable depending on the execution environment.

5. 4️⃣ Web Server Provides a user-friendly UI to monitor DAGs, tasks, logs, and execution status. Supports real-time interaction and control.

6. 5️⃣ Metadata Database Stores DAGs, task states, schedules, and logs. Central to Airflow's state management using SQLAlchemy ORM.

7. 6️⃣ DAGs (Directed Acyclic Graphs) Define workflows using Python code. Represent task relationships and dependencies.

8. Contact Details 👉 Enroll Now: www.accentfuture.com 📩 Email: [email protected] 📞 Call: [phone] Apache Airflow Training