Auguste Kevin (14 results)
- Softcover
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
- Softcover
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
- Softcover
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
- Softcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
- Softcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
Contact seller5-star sellerCondition: New
US$ 29.69
US$ 5.61 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
- Softcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
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US$ 30.39
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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US$ 39.21
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Taschenbuch. Condition: 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, API…s, 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.
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
Contact seller5-star sellerCondition: New
US$ 39.21
US$ 71.54 shippingShips from Germany to U.S.A.Quantity: 2 available
Taschenbuch. Condition: Neu. Neuware - Modern applications are no longer limited by code alone, they are limited by how fast they can process, distribute, and react to data in real time.Can your architecture handle millions of events without collapsing under latency, bottlenecks, consumer lag, or inconsistent data flows Designin…g Scalable Streaming Architectures with Apache Kafka is a practical, production-focused guide for data engineers, backend developers, software engineers, and solutions architects who want to build resilient, high-performance streaming systems that scale under real-world pressure.Instead of treating Apache Kafka as 'just another messaging tool,' this book explains how Kafka functions as the backbone of modern event-driven architecture, distributed systems, real-time analytics, microservices communication, and large-scale data pipelines.You'll learn how to: - Design scalable Kafka architectures for high-throughput systems- Structure events and schemas for long-term evolution- Build reliable producers and fault-tolerant consumers- Manage partitions, replication, and delivery guarantees- Diagnose consumer lag, rebalance issues, and production bottlenecks- Apply stream processing, CQRS, and event sourcing patterns effectively- Handle scaling, observability, and failure recovery in production environments- Understand the real trade-offs behind exactly-once processing and asynchronous communicationInside, you'll explore practical chapters such as Partitioning Strategies and Their Trade-Offs, Handling Failures and Backpressure in Applications, Multi-Cluster and Geo-Distributed Architectures, and When Not to Use Kafka: Limits and Trade-Offs.Every concept is explained with real architectural reasoning and hands-on code examples designed for modern distributed systems, not toy projects.Whether you are building real-time data pipelines, event-driven microservices, streaming analytics platforms, or scalable backend systems, this book will help you make better architectural decisions, avoid costly design mistakes, and operate Kafka with confidence in production.If you want to build faster, more resilient, and scalable streaming systems with Apache Kafka, this book belongs on your desk.
- Softcover
- Print on Demand
Seller: California Books, Miami, FL, U.S.A.California Books
Contact seller4-star sellerCondition: New
US$ 28.00
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Condition: New. Print on Demand.
- Softcover
- Print on Demand
Seller: California Books, Miami, FL, U.S.A.California Books
Contact seller4-star sellerCondition: New
US$ 28.00
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Condition: New. Print on Demand.
- Softcover
- Print on Demand
Seller: California Books, Miami, FL, U.S.A.California Books
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US$ 29.00
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Condition: New. Print on Demand.
- Softcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
Contact seller5-star sellerCondition: New
US$ 33.99
US$ 49.87 shippingShips from United Kingdom to U.S.A.Quantity: 1 available
Paperback. Condition: 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, API…s, 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.
- Softcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
Contact seller5-star sellerCondition: New
US$ 33.99
US$ 49.87 shippingShips from United Kingdom to U.S.A.Quantity: 1 available
Paperback. Condition: new. Paperback. Modern applications are no longer limited by code alone, they are limited by how fast they can process, distribute, and react to data in real time.Can your architecture handle millions of events without collapsing under latency, bottlenecks, consumer lag, or inconsistent data flows?Designing… Scalable Streaming Architectures with Apache Kafka is a practical, production-focused guide for data engineers, backend developers, software engineers, and solutions architects who want to build resilient, high-performance streaming systems that scale under real-world pressure.Instead of treating Apache Kafka as "just another messaging tool," this book explains how Kafka functions as the backbone of modern event-driven architecture, distributed systems, real-time analytics, microservices communication, and large-scale data pipelines.You'll learn how to: Design scalable Kafka architectures for high-throughput systemsStructure events and schemas for long-term evolutionBuild reliable producers and fault-tolerant consumersManage partitions, replication, and delivery guaranteesDiagnose consumer lag, rebalance issues, and production bottlenecksApply stream processing, CQRS, and event sourcing patterns effectivelyHandle scaling, observability, and failure recovery in production environmentsUnderstand the real trade-offs behind exactly-once processing and asynchronous communicationInside, you'll explore practical chapters such as Partitioning Strategies and Their Trade-Offs, Handling Failures and Backpressure in Applications, Multi-Cluster and Geo-Distributed Architectures, and When Not to Use Kafka: Limits and Trade-Offs.Every concept is explained with real architectural reasoning and hands-on code examples designed for modern distributed systems, not toy projects.Whether you are building real-time data pipelines, event-driven microservices, streaming analytics platforms, or scalable backend systems, this book will help you make better architectural decisions, avoid costly design mistakes, and operate Kafka with confidence in production.If you want to build faster, more resilient, and scalable streaming systems with Apache Kafka, this book belongs on your desk. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
- Softcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
Contact seller5-star sellerCondition: New
US$ 34.69
US$ 49.87 shippingShips from United Kingdom to U.S.A.Quantity: 1 available
Paperback. Condition: new. Paperback. Are your data pipelines slowing down, breaking under scale, or becoming too complex to maintain?Modern data systems demand more than scripts that "just work." They require reliability, performance, and the ability to evolve without constant rewrites. Yet many engineers and analysts struggle…with inefficient Spark jobs, unpredictable execution, and rising infrastructure costs.This book addresses that gap.Building Scalable Data Systems with Apache Spark 4.x is a practical guide to designing, optimizing, and operating distributed data pipelines using Apache Spark, PySpark, SQL, and lakehouse technologies. It focuses on how Spark actually behaves at scale, so you can build systems that are not only functional, but fast, stable, and production-ready.You won't just learn how to write Spark code, you'll learn how to think like a data systems engineer.Inside, you will learn how to: Design end-to-end pipelines from ingestion to output using PySpark and SQLUnderstand execution internals like DAGs, jobs, stages, and Catalyst optimizationOptimize performance through partitioning, Adaptive Query Execution (AQE), and efficient joinsBuild reliable streaming systems with Structured Streaming and exactly-once semanticsWork with modern storage systems like Delta Lake and Apache IcebergDeploy and operate Spark workloads using Kubernetes, monitoring, and resource tuningEach chapter builds practical intuition, connecting code to execution so you can diagnose bottlenecks, reduce cost, and scale confidently.If you work as a data engineer, data analyst, backend developer, or data scientist, this book equips you with the skills to move beyond trial-and-error and build systems that perform consistently in real-world environments.Your data is growing. Your systems should keep up.Get your copy today and start building data pipelines that scale, perform, and last. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
