Apache Airflow Tutorials – From Basics to Production Data Orchestration
🚀 Apache Airflow Tutorials
Welcome to the Apache Airflow Tutorials hub.
This section is designed to take you from Airflow fundamentals to advanced production-grade workflow orchestration used in modern data engineering systems.
The tutorials are structured to reflect how Airflow is used in batch pipelines, event-driven workflows, and enterprise data platforms.
🧱 Airflow Fundamentals
Get started with the core concepts of workflow orchestration.
- What is Apache Airflow?
- Airflow Architecture
- Understanding DAGs
- Airflow Components Overview
- How Airflow Executes Workflows
- Airflow UI Guide
👉 Start here if you are new to Airflow.
⚙️ DAG Development Basics
Learn how to build and schedule workflows.
- Creating Your First DAG
- Operators Basics
- Task Dependencies
- Scheduling & Cron Expressions
- Variables & Connections
- Templating & Jinja Expressions
👉 Core skills for building real DAGs.
🔗 Operators & Sensors
Work with tasks that interact with systems and services.
- PythonOperator Deep Dive
- BashOperator Workflows
- SQL Operators
- File & Cloud Operators (S3, GCS)
- HttpOperator & APIs
- Sensors Explained
- Hooks Overview
👉 Used in real-world integrations.
🧠 XComs & Dynamic Workflows
Advanced data flow and dynamic DAG behavior.
- XComs Explained
- Branching Workflows
- ShortCircuitOperator
- Trigger Rules
- Dynamic Tasks (TaskFlow API)
- Dynamic DAG Generation
👉 Essential for advanced pipeline logic.
⚡ Performance & Executors
Understand how Airflow scales.
- Executors (Local, Celery, Kubernetes)
- Scaling Workers
- Performance Tuning
- Scheduling Optimization
- Python Performance Best Practices
👉 Critical for production workloads.