Apache Airflow Architecture: Core Components and Workflows

To build resilient data pipelines, you must first understand what happens behind the scenes when a workflow runs. Apache Airflow is a powerful orchestrator, but its true strength lies in how its core components interact. This text-based course guides you through the foundational architecture of Apache Airflow, explaining how each part of the system communicates to execute tasks reliably. By reading through these comprehensive lessons, you will transition from writing basic DAGs to understanding the underlying infrastructure that keeps your data platform running smoothly. What you'll learn: - Understand the roles of the Webserver, Scheduler, Metadata Database, and Executor. - Explore how task scheduling, queuing, and execution flow through the system. - Compare different executor types, including Sequential, Celery, and Kubernetes executors. - Learn how the modern Triggerer component enables efficient, asynchronous event-driven tasks. - Analyze database interactions and state management within your orchestration environment. You will start with basic architectural definitions before diving into detailed explanations of the scheduler loop, worker nodes, and database schema. The course wraps up with practical architectural patterns for modern cloud environments. This course is designed for beginner data engineers, developers, and system administrators who want to build a solid conceptual foundation in Airflow without needing prior infrastructure experience. Read through our structured guides to master the mechanics of modern data orchestration.