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Paperback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

paperback. Condición: Very Good.

Condición: As New. Unread book in perfect condition.

HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

Condición: New.

Paperback or Softback. Condición: New. Data Pipelines with Apache Airflow, Second Edition: Orchestration for Data and AI. Book.

Hardcover. Condición: new. Hardcover. Scripts keep crashing and stakeholders demand data they can trust. Late-night alerts drain your energy and delay business decisions. Manual fixes multiply as pipelines sprawl across clouds and clusters. You need orchestration that scales without sacrificing reliability or sleep. Apache Airflow promises order, yet its power can feel overwhelming. This book makes Airflow mastery achievable, practical, and immediately rewarding. Dynamic scheduling with Dataset API: Align complex, irregular jobs to real-world data availability. Taskflow API patterns: Write cleaner Python code, reduce boilerplate, and speed team onboarding. Container-native deployments: Run pipelines on Kubernetes for elastic scaling and cost control. Comprehensive testing strategies: Catch issues before production, slash incident time, protect reputation. Production-ready best practices: Logging, security, and monitoring that keep auditors and leaders happy. Custom operator design: Extend Airflow to any system, unlocking limitless integration possibilities. Data Pipelines with Apache Airflow, Second Edition gathers five seasoned consultants into one definitive field guide. Their combined experience turns cutting-edge features into steps you can reproduce today. It is the trusted companion for every data engineer. The book starts with Airflow architecture, then walks through DAG design, testing, deployment, and operations. Updated chapters reveal Taskflow, Dataset scheduling, and Kubernetes setups, explained through real projects, not toy examples. Clear language, diagrams, and downloadable code remove guesswork. Finish the last page knowing your pipelines deploy reliably, recover gracefully, and scale effortlessly. Sleep through the night while Airflow delivers fresh, accurate data to every downstream consumer. Ideal for data engineers, DevOps, machine-learning engineers, and Python-savvy analysts ready to level-up orchestration skills. Apache Airflow provides a batteries-included platform for designing, implementing, and monitoring data pipelines. Building pipelines on Airflow eliminates the need for patchwork stacks and homegrown processes, adding security and consistency to the process. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condición: new.

Condición: New.

Condición: New.

Hardback. Condición: New. Scripts keep crashing and stakeholders demand data they can trust. Late-night alerts drain your energy and delay business decisions. Manual fixes multiply as pipelines sprawl across clouds and clusters. You need orchestration that scales without sacrificing reliability or sleep. Apache Airflow promises order, yet its power can feel overwhelming. This book makes Airflow mastery achievable, practical, and immediately rewarding.  Dynamic scheduling with Dataset API: Align complex, irregular jobs to real-world data availability.  Taskflow API patterns: Write cleaner Python code, reduce boilerplate, and speed team onboarding.  Container-native deployments: Run pipelines on Kubernetes for elastic scaling and cost control.  Comprehensive testing strategies: Catch issues before production, slash incident time, protect reputation.  Production-ready best practices: Logging, security, and monitoring that keep auditors and leaders happy.  Custom operator design: Extend Airflow to any system, unlocking limitless integration possibilities.  Data Pipelines with Apache Airflow, Second Edition gathers five seasoned consultants into one definitive field guide. Their combined experience turns cutting-edge features into steps you can reproduce today. It is the trusted companion for every data engineer.  The book starts with Airflow architecture, then walks through DAG design, testing, deployment, and operations. Updated chapters reveal Taskflow, Dataset scheduling, and Kubernetes setups, explained through real projects, not toy examples. Clear language, diagrams, and downloadable code remove guesswork.  Finish the last page knowing your pipelines deploy reliably, recover gracefully, and scale effortlessly. Sleep through the night while Airflow delivers fresh, accurate data to every downstream consumer.  Ideal for data engineers, DevOps, machine-learning engineers, and Python-savvy analysts ready to level-up orchestration skills.…

Condición: As New. Unread book in perfect condition.

paperback. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condición: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Hardback. Condición: New. Scripts keep crashing and stakeholders demand data they can trust. Late-night alerts drain your energy and delay business decisions. Manual fixes multiply as pipelines sprawl across clouds and clusters. You need orchestration that scales without sacrificing reliability or sleep. Apache Airflow promises order, yet its power can feel overwhelming. This book makes Airflow mastery achievable, practical, and immediately rewarding.  Dynamic scheduling with Dataset API: Align complex, irregular jobs to real-world data availability.  Taskflow API patterns: Write cleaner Python code, reduce boilerplate, and speed team onboarding.  Container-native deployments: Run pipelines on Kubernetes for elastic scaling and cost control.  Comprehensive testing strategies: Catch issues before production, slash incident time, protect reputation.  Production-ready best practices: Logging, security, and monitoring that keep auditors and leaders happy.  Custom operator design: Extend Airflow to any system, unlocking limitless integration possibilities.  Data Pipelines with Apache Airflow, Second Edition gathers five seasoned consultants into one definitive field guide. Their combined experience turns cutting-edge features into steps you can reproduce today. It is the trusted companion for every data engineer.  The book starts with Airflow architecture, then walks through DAG design, testing, deployment, and operations. Updated chapters reveal Taskflow, Dataset scheduling, and Kubernetes setups, explained through real projects, not toy examples. Clear language, diagrams, and downloadable code remove guesswork.  Finish the last page knowing your pipelines deploy reliably, recover gracefully, and scale effortlessly. Sleep through the night while Airflow delivers fresh, accurate data to every downstream consumer.  Ideal for data engineers, DevOps, machine-learning engineers, and Python-savvy analysts ready to level-up orchestration skills.…

Hardback. Condición: New. New copy - Usually dispatched within 4 working days.

paperback. Condición: New. Special order direct from the distributor.

Paperback. Condición: Brand New. 454 pages. 9.25x7.50x1.00 inches. In Stock.

Paperback. Condición: Brand New. 2nd edition. 450 pages. 9.26x7.38x9.25 inches. In Stock.

Hardcover. Condición: new. Hardcover. Scripts keep crashing and stakeholders demand data they can trust. Late-night alerts drain your energy and delay business decisions. Manual fixes multiply as pipelines sprawl across clouds and clusters. You need orchestration that scales without sacrificing reliability or sleep. Apache Airflow promises order, yet its power can feel overwhelming. This book makes Airflow mastery achievable, practical, and immediately rewarding. Dynamic scheduling with Dataset API: Align complex, irregular jobs to real-world data availability. Taskflow API patterns: Write cleaner Python code, reduce boilerplate, and speed team onboarding. Container-native deployments: Run pipelines on Kubernetes for elastic scaling and cost control. Comprehensive testing strategies: Catch issues before production, slash incident time, protect reputation. Production-ready best practices: Logging, security, and monitoring that keep auditors and leaders happy. Custom operator design: Extend Airflow to any system, unlocking limitless integration possibilities. Data Pipelines with Apache Airflow, Second Edition gathers five seasoned consultants into one definitive field guide. Their combined experience turns cutting-edge features into steps you can reproduce today. It is the trusted companion for every data engineer. The book starts with Airflow architecture, then walks through DAG design, testing, deployment, and operations. Updated chapters reveal Taskflow, Dataset scheduling, and Kubernetes setups, explained through real projects, not toy examples. Clear language, diagrams, and downloadable code remove guesswork. Finish the last page knowing your pipelines deploy reliably, recover gracefully, and scale effortlessly. Sleep through the night while Airflow delivers fresh, accurate data to every downstream consumer. Ideal for data engineers, DevOps, machine-learning engineers, and Python-savvy analysts ready to level-up orchestration skills. Apache Airflow provides a batteries-included platform for designing, implementing, and monitoring data pipelines. Building pipelines on Airflow eliminates the need for patchwork stacks and homegrown processes, adding security and consistency to the process. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Paperback. Condición: Brand New. 454 pages. 9.25x7.50x1.00 inches. In Stock.

Hardback. Condición: New. Scripts keep crashing and stakeholders demand data they can trust. Late-night alerts drain your energy and delay business decisions. Manual fixes multiply as pipelines sprawl across clouds and clusters. You need orchestration that scales without sacrificing reliability or sleep. Apache Airflow promises order, yet its power can feel overwhelming. This book makes Airflow mastery achievable, practical, and immediately rewarding.  Dynamic scheduling with Dataset API: Align complex, irregular jobs to real-world data availability.  Taskflow API patterns: Write cleaner Python code, reduce boilerplate, and speed team onboarding.  Container-native deployments: Run pipelines on Kubernetes for elastic scaling and cost control.  Comprehensive testing strategies: Catch issues before production, slash incident time, protect reputation.  Production-ready best practices: Logging, security, and monitoring that keep auditors and leaders happy.  Custom operator design: Extend Airflow to any system, unlocking limitless integration possibilities.  Data Pipelines with Apache Airflow, Second Edition gathers five seasoned consultants into one definitive field guide. Their combined experience turns cutting-edge features into steps you can reproduce today. It is the trusted companion for every data engineer.  The book starts with Airflow architecture, then walks through DAG design, testing, deployment, and operations. Updated chapters reveal Taskflow, Dataset scheduling, and Kubernetes setups, explained through real projects, not toy examples. Clear language, diagrams, and downloadable code remove guesswork.  Finish the last page knowing your pipelines deploy reliably, recover gracefully, and scale effortlessly. Sleep through the night while Airflow delivers fresh, accurate data to every downstream consumer.  Ideal for data engineers, DevOps, machine-learning engineers, and Python-savvy analysts ready to level-up orchestration skills.…

Condición: New. 2026. 2nd Edition. paperback. . . . . . Books ship from the US and Ireland.

Hardcover. Condición: new. Hardcover. Scripts keep crashing and stakeholders demand data they can trust. Late-night alerts drain your energy and delay business decisions. Manual fixes multiply as pipelines sprawl across clouds and clusters. You need orchestration that scales without sacrificing reliability or sleep. Apache Airflow promises order, yet its power can feel overwhelming. This book makes Airflow mastery achievable, practical, and immediately rewarding. Dynamic scheduling with Dataset API: Align complex, irregular jobs to real-world data availability. Taskflow API patterns: Write cleaner Python code, reduce boilerplate, and speed team onboarding. Container-native deployments: Run pipelines on Kubernetes for elastic scaling and cost control. Comprehensive testing strategies: Catch issues before production, slash incident time, protect reputation. Production-ready best practices: Logging, security, and monitoring that keep auditors and leaders happy. Custom operator design: Extend Airflow to any system, unlocking limitless integration possibilities. Data Pipelines with Apache Airflow, Second Edition gathers five seasoned consultants into one definitive field guide. Their combined experience turns cutting-edge features into steps you can reproduce today. It is the trusted companion for every data engineer. The book starts with Airflow architecture, then walks through DAG design, testing, deployment, and operations. Updated chapters reveal Taskflow, Dataset scheduling, and Kubernetes setups, explained through real projects, not toy examples. Clear language, diagrams, and downloadable code remove guesswork. Finish the last page knowing your pipelines deploy reliably, recover gracefully, and scale effortlessly. Sleep through the night while Airflow delivers fresh, accurate data to every downstream consumer. Ideal for data engineers, DevOps, machine-learning engineers, and Python-savvy analysts ready to level-up orchestration skills. Apache Airflow provides a batteries-included platform for designing, implementing, and monitoring data pipelines. Building pipelines on Airflow eliminates the need for patchwork stacks and homegrown processes, adding security and consistency to the process. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Condición: New. 2026. 2nd Edition. paperback. . . . . .

Hardback. Condición: New. Scripts keep crashing and stakeholders demand data they can trust. Late-night alerts drain your energy and delay business decisions. Manual fixes multiply as pipelines sprawl across clouds and clusters. You need orchestration that scales without sacrificing reliability or sleep. Apache Airflow promises order, yet its power can feel overwhelming. This book makes Airflow mastery achievable, practical, and immediately rewarding.  Dynamic scheduling with Dataset API: Align complex, irregular jobs to real-world data availability.  Taskflow API patterns: Write cleaner Python code, reduce boilerplate, and speed team onboarding.  Container-native deployments: Run pipelines on Kubernetes for elastic scaling and cost control.  Comprehensive testing strategies: Catch issues before production, slash incident time, protect reputation.  Production-ready best practices: Logging, security, and monitoring that keep auditors and leaders happy.  Custom operator design: Extend Airflow to any system, unlocking limitless integration possibilities.  Data Pipelines with Apache Airflow, Second Edition gathers five seasoned consultants into one definitive field guide. Their combined experience turns cutting-edge features into steps you can reproduce today. It is the trusted companion for every data engineer.  The book starts with Airflow architecture, then walks through DAG design, testing, deployment, and operations. Updated chapters reveal Taskflow, Dataset scheduling, and Kubernetes setups, explained through real projects, not toy examples. Clear language, diagrams, and downloadable code remove guesswork.  Finish the last page knowing your pipelines deploy reliably, recover gracefully, and scale effortlessly. Sleep through the night while Airflow delivers fresh, accurate data to every downstream consumer.  Ideal for data engineers, DevOps, machine-learning engineers, and Python-savvy analysts ready to level-up orchestration skills.…