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 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 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.

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Bibliographic Details

Title: Designing Scalable Streaming Architectures with Apache Kafka : Apply Proven Patterns, Balance Trade-Offs, and Build High-Performance Systems for Data-Intensive Applications
Publisher: Amazon Digital Services LLC - Kdp Mai 2026
Publication Date: 2026
Language: English
ISBN 13: 9798196222634
Binding: Taschenbuch
Condition: Neu
Dimensions: 254 millimeters width by 178 millimeters height by 12 millimeters depth
Weight: 404 grams

About this title

Synopsis

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 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 communication

Inside, 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.

"About this title" may belong to another edition of this title.

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