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(Ebook) Designing Event-Driven Systems: Concepts and Patterns for Streaming Services with Apache Kafka by Ben Stopford ISBN 9781492038221, 1492038229

  • SKU: EBN-7246304
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Instant download (eBook) Designing Event-Driven Systems: Concepts and Patterns for Streaming Services with Apache Kafka after payment.
Authors:Ben Stopford
Pages:151 pages.
Year:2018
Editon:1st
Language:english
File Size:5.05 MB
Format:pdf
ISBNS:9781492038221, 1492038229
Categories: Ebooks

Product desciption

(Ebook) Designing Event-Driven Systems: Concepts and Patterns for Streaming Services with Apache Kafka by Ben Stopford ISBN 9781492038221, 1492038229

Many forces affect software today: larger datasets, geographical disparities, complex company structures, and the growing need to be fast and nimble in the face of change. Proven approaches such as service-oriented and event-driven architectures are joined by newer techniques such as microservices, reactive architectures, DevOps, and stream processing. Many of these patterns are successful by themselves, but as this practical ebook demonstrates, they provide a more holistic and compelling approach when applied together. Author Ben Stopford explains how service-based architectures and stream processing tools such as Apache Kafka can help you build business-critical systems. You'll learn how to apply patterns including Event Sourcing and CQRS, and how to build multi-team systems with microservices and SOA using patterns such as "inside out databases" and "event streams as a source of truth." These approaches provide a unique foundation for how these large, autonomous service ecosystems can communicate and share data. Learn why streaming beats request-response based architectures in complex, contemporary use cases Understand why replayable logs such as Kafka provide a backbone for both service communication and shared datasets Explore how event collaboration and event sourcing patterns increase safety and recoverability with functional, event-driven approaches Build service ecosystems that blend event-driven and request-driven interfaces using a replayable log and Kafka's Streams API Scale beyond individual teams into larger, department- and company-sized architectures, using event streams as a source of truth.
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