Apache Airflow 3: Dynamic Task Mapping & Resilience

This course contains the use of artificial intelligence.Stop building brittle, static data pipelines that break under changing workloads and waste expensive cluster resources.In this hands-on, practical course, you will master the next-generation features of Apache Airflow 3.0 to construct fully dynamic, event-driven, and resilient data pipelines built for enterprise scale. You will learn how to scale tasks dynamically at runtime, leverage deferrable operators to reduce infrastructure costs, and build automated self-healing mechanisms into every DAG you deploy.Who this course is for:Data Engineers looking to upgrade their skills to Apache Airflow 3.0Backend Developers and DevOps Engineers managing data orchestrationsData Architects designing enterprise-grade, resilient pipeline infrastructureAnalytics Engineers wanting to automate scaling data workloadsWhat you will learn:Build dynamic workflows with Airflow 3 dynamic task mappingEliminate worker bottlenecks using async deferrable operators and triggersDesign self-healing pipelines with exponential backoffs and callbacksArchitect high-concurrency event-driven DAGs in Apache Airflow 3.0Optimize cloud infrastructure costs by freeing up idle worker slotsImplement circuit breakers, dead letter queues, and SLA monitoringHandle unpredictably sized data payloads smoothly at runtimeAggregate mapped task outputs efficiently across complex workflowsRequirements:Fundamental knowledge of Python programmingBasic understanding of data engineering concepts and SQLFamiliarity with basic Apache Airflow concepts (DAGs, tasks, operators)Final Project Description: For your capstone project, you will build an end-to-end, market-ready e-commerce data pipeline in Apache Airflow 3. Your pipeline will dynamically discover multi-region data stores, wait asynchronously for third-party file uploads using deferrable triggers, process store data in parallel, and automatically handle simulated network failures using advanced retry strategies and failure callbacks.