Spring Cloud Data Flow

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. You will:

• See the Spring Cloud Data Flow internals
• Create your own Binder using NATs as Broker
• Mater Spring Cloud Data Flow architecture, data processing, and DSL
• Integrate Spring Cloud Data Flow with Kubernetes
• Use Spring Cloud Data Flow local server, Docker Compose, and Kubernetes
• 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

Auteur
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.

Contenu

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

6 - Spring Cloud App Stream

7 - Binders

8 Spring Cloud Data Flow Introduction & Installation

Part II. Spring Cloud Data Flow: Internals

9 - Spring Cloud Data Flow Internals

10 - Custom Source, Processor, Sink, Tasks with Spring Cloud Task

11 - Analytics: Counters and Gauges