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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 the book 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 Cloud Foundry and 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 learn:

See the Spring Cloud Data Flow internals
Master Spring Cloud Data Flow architecture, data processing, and DSL
Integrate Spring Cloud Data Flow with Cloud Foundry, and Kubernetes
Use Spring Cloud Data Flow local server, Cloud Foundry, and more
Discover the Spring Cloud Data Flow applications and how to use them
Work with source, processor, sink, tasks, Spring Flo and its GUI, and analytics via the new Micrometer stack for realtime visibility with Prometheus and Grafana Who is this book for:

Those with some experience with the Spring Framework, Microservices and Cloud Nativa Applications; Java experience preferred.

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Part I. Introductions 1 - Cloud, Microservices and Big Data an Overview 2 - Quick Introduction to Spring Framework and Spring Boot 3 - Spring Integration 4 - Spring Batch 5 - Spring Cloud Stream 6 - Spring Cloud Task 7 - Spring Cloud Services
Part II. Spring Cloud Data Flow: Internals 8 - Spring Cloud Data Flow Architecture, Data Processing and DSL 9 - Spring Cloud Data Flow Local Server 10 - Spring Cloud Data Flow for Cloud Foundry 11 - Spring Cloud Data Flow for Kubernetes
Part III. Spring Cloud Data Flow: Applications 12 - Source, Processor, Sink, Tasks 13 - Spring Flo - GUI 14 - Analytics: Counters and Gauges 15 - Skipper
Part IV. Spring Cloud Data Flow Development and Deployment 16 - Custom Application Development and Deployment 17 - Use Cases

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Felipe Gutierrez is a solutions software architect, with a bachelors and master degree in computer science from Instituto Tecnologico y de Estudios Superiores de Monterrey Campus Ciudad de Mexico. With over 20 years of IT experience, during which time he developed programs for companies in multiple vertical industries, such as government, retail, healthcare, education, and banking. Right now, he is currently working as a principal technical instructor for Pivotal, specializing in Cloud Foundry, Spring Framework, Spring Cloud Native Applications, Groovy, and RabbitMQ, among other technologies. He has worked as a solutions architect for big companies like Nokia, Apple, Redbox, and Qualcomm, among others. He is also the author of Introducing Spring Framework, Pro Spring Boot and Spring Boot Messaging, all published by Apress.

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