ISBN: 9798199952217 - designing workflow orchestration systems with apache airflow 3: coordinate complex dependencies, ensure fault tolerance, and deliver scalable production pipelines with airflow 3.x (5 resultados)

Taschenbuch. Condición: Neu. Neuware - Are your data pipelines becoming harder to manage, troubleshoot, and scale Do workflow failures, hidden dependencies, delayed schedules, and unreliable retries threaten the stability of your data platform Modern data systems are more connected than ever. Data warehouses, cloud services, APIs, machine learning workflows, analytics platforms, and event-driven applications all depend on reliable orchestration. The challenge is no longer running individual tasks, it is coordinating complex workflows across distributed environments while maintaining performance, visibility, and fault tolerance.Designing Workflow Orchestration Systems with Apache Airflow 3 provides a practical roadmap for building production-grade orchestration platforms using the latest capabilities of Airflow 3.x. Rather than focusing solely on DAG creation, this book teaches you how to design reliable, scalable, and maintainable workflow systems that support real business operations.Inside, you'll learn how to: - Build end-to-end data pipelines that remain reliable in production environments- Design maintainable DAGs with robust dependency management and safe re-runs- Implement fault-tolerant workflows using retries, backoff strategies, and self-healing patterns- Leverage dataset-aware scheduling, event-driven workflows, and API-based execution- Scale Airflow with Celery, Kubernetes, and distributed execution models- Monitor workflow health, collect meaningful metrics, and debug complex failures- Orchestrate ETL, ELT, analytics, and machine learning pipelines with confidence- Integrate Airflow with data warehouses, data lakes, APIs, and modern cloud platforms- Establish governance, security, CI/CD automation, and long-term operational excellenceFrom Designing DAGs for Reliability and Fault Tolerance and Failure Handling to Scaling Airflow in Production and Production Readiness and Operational Excellence, each chapter focuses on practical engineering decisions that directly impact system reliability and business outcomes.Whether you're a Data Engineer, Analytics Engineer, Platform Engineer, DevOps Professional, MLOps Practitioner, or Technical Architect, this book will help you move beyond basic scheduling and develop the skills needed to build resilient workflow orchestration systems at scale.If you're ready to coordinate complex dependencies, strengthen pipeline reliability, and deliver scalable production workflows with Apache Airflow 3.x, this book belongs on your desk. Get your copy now.…

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PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condición: new. Paperback. Are your data pipelines becoming harder to manage, troubleshoot, and scale? Do workflow failures, hidden dependencies, delayed schedules, and unreliable retries threaten the stability of your data platform?Modern data systems are more connected than ever. Data warehouses, cloud services, APIs, machine learning workflows, analytics platforms, and event-driven applications all depend on reliable orchestration. The challenge is no longer running individual tasks, it is coordinating complex workflows across distributed environments while maintaining performance, visibility, and fault tolerance.Designing Workflow Orchestration Systems with Apache Airflow 3 provides a practical roadmap for building production-grade orchestration platforms using the latest capabilities of Airflow 3.x. Rather than focusing solely on DAG creation, this book teaches you how to design reliable, scalable, and maintainable workflow systems that support real business operations.Inside, you'll learn how to: - Build end-to-end data pipelines that remain reliable in production environments- Design maintainable DAGs with robust dependency management and safe re-runs- Implement fault-tolerant workflows using retries, backoff strategies, and self-healing patterns- Leverage dataset-aware scheduling, event-driven workflows, and API-based execution- Scale Airflow with Celery, Kubernetes, and distributed execution models- Monitor workflow health, collect meaningful metrics, and debug complex failures- Orchestrate ETL, ELT, analytics, and machine learning pipelines with confidence- Integrate Airflow with data warehouses, data lakes, APIs, and modern cloud platforms- Establish governance, security, CI/CD automation, and long-term operational excellenceFrom Designing DAGs for Reliability and Fault Tolerance and Failure Handling to Scaling Airflow in Production and Production Readiness and Operational Excellence, each chapter focuses on practical engineering decisions that directly impact system reliability and business outcomes.Whether you're a Data Engineer, Analytics Engineer, Platform Engineer, DevOps Professional, MLOps Practitioner, or Technical Architect, this book will help you move beyond basic scheduling and develop the skills needed to build resilient workflow orchestration systems at scale.If you're ready to coordinate complex dependencies, strengthen pipeline reliability, and deliver scalable production workflows with Apache Airflow 3.x, this book belongs on your desk. Get your copy now! This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…