Description
Apress Spring Cloud Data Flow Native Cloud Orchestration Services for Microservice Applications on Modern Runtimes 2021 Edition by Felipe Gutierrez
Work with big data applications by using Spring Cloud Data Flow as a unified, distributed, and extensible system for data ingestion and integration, real-time analytics and data processing pipelines, batch processing, and data export. With this book you will develop a foundation for creating applications that use real-time data streaming by combining different technologies and use the full power of Spring Cloud Data Flow. The first part of Spring Cloud Data Flow introduces the concepts you will need in the rest of the book. It begins with an overview of the cloud, microservices, and big data, before moving on to the Spring projects essential to modern big data applications in Java: Spring Integration, Spring Batch, Spring Cloud Stream, and Spring Cloud Task. The second part of the book covers the internals of Spring Cloud Data Flow, giving you the insights and knowledge required to build the applications you need. You'll learn how to use Spring Data Flow's DSL and how to integrate with third-party cloud platform solutions, such as Kubernetes. Finally, the book covers Spring Cloud Data Flow applications to impart practical, useful skills for real-world applications of the technologies covered throughout the rest of the book. What You Will LearnSee the Spring Cloud Data Flow internals Create your own Binder using NATs as BrokerMater Spring Cloud Data Flow architecture, data processing, and DSLIntegrate Spring Cloud Data Flow with KubernetesUse Spring Cloud Data Flow local server, Docker Compose, and KubernetesDiscover the Spring Cloud Data Flow applications and how to use themWork with source, processor, sink, tasks, Spring Flo and its GUI, and analytics via the new Micrometer stack for realtime visibility with Prometheus and GrafanaWho This Book Is ForThose with some experience with the Spring Framework, Microservices and Cloud Native Applications. Java experience is recommended.