Apache Airflow and FastAPI for Enterprise Pipelines

Reactive Publishing

Stop building brittle data pipelines that fail quietly in production.

As modern data infrastructure scales, bridging the gap between batch workflow orchestration and real-time API services becomes critical. Apache Airflow and FastAPI for Enterprise Pipelines provides a production-grade blueprint for integrating Apache Airflow and FastAPI into high-availability, resilient data engineering architectures.

Designed for data engineers, backend developers, and system architects, this comprehensive guide demonstrates how to design, automate, and deploy production pipelines capable of handling heavy ETL workloads, machine learning automation, and high-performance microservices.

• Production Apache Airflow: Architect scalable Directed Acyclic Graphs (DAGs), implement custom operators, optimize task concurrency, and handle dynamic workflow execution.

• Modern API Microservices with FastAPI: Build high-throughput asynchronous REST APIs to serve ML models, trigger remote pipeline runs, and expose operational metadata.

• Integrated Architecture Pattern: Connect batch orchestration (Airflow) with event-driven execution (FastAPI) to eliminate data latency and improve system reliability.

• Resilience & Fault Tolerance: Implement robust error handling, circuit breakers, backoff retry strategies, and automated alert mechanisms.

• Testing, CI/CD, & Containerization: Write unit and integration tests for DAGs and APIs, dockerize multi-service architectures, and automate deployment with modern CI/CD pipelines.

• Monitoring & Observability: Track pipeline health using Prometheus, Grafana, and structured logging to catch failures before they impact business logic.

Packed with end-to-end Python examples, architectural diagrams, and battle-tested industry practices, this book delivers the concrete tools needed to move from fragmented scripts to robust, enterprise-grade data automation platforms.