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  • Book Overview & Buying Spring Microservices
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Spring Microservices

Spring Microservices

By : Rajesh R V
4.7 (13)
Buy this Book
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Spring Microservices

Spring Microservices

4.7 (13)
By: Rajesh R V
Buy this Book

Overview of this book

The Spring Framework is an application framework and inversion of the control container for the Java platform. The framework's core features can be used by any Java application, but there are extensions to build web applications on top of the Java EE platform. This book will help you implement the microservice architecture in Spring Framework, Spring Boot, and Spring Cloud. Written to the latest specifications of Spring, you'll be able to build modern, Internet-scale Java applications in no time. We would start off with the guidelines to implement responsive microservices at scale. We will then deep dive into Spring Boot, Spring Cloud, Docker, Mesos, and Marathon. Next you will understand how Spring Boot is used to deploy autonomous services, server-less by removing the need to have a heavy-weight application server. Later you will learn how to go further by deploying your microservices to Docker and manage it with Mesos. By the end of the book, you'll will gain more clarity on how to implement microservices using Spring Framework and use them in Internet-scale deployments through real-world examples.
Table of Contents (12 chapters)
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Preface
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Preface
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What this book covers
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What you need for this book
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Who this book is for
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Conventions
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Reader feedback
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Customer support
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1
1. Demystifying Microservices
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1. Demystifying Microservices
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The evolution of microservices
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What are microservices?
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Microservices – the honeycomb analogy
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Principles of microservices
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Characteristics of microservices
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Microservices examples
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Microservices benefits
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Relationship with other architecture styles
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Microservice use cases
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Summary
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2. Building Microservices with Spring Boot
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2. Building Microservices with Spring Boot
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Setting up a development environment
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Developing a RESTful service – the legacy approach
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Moving from traditional web applications to microservices
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Using Spring Boot to build RESTful microservices
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Getting started with Spring Boot
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Developing the Spring Boot microservice using the CLI
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Developing the Spring Boot Java microservice using STS
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Developing the Spring Boot microservice using Spring Initializr – the HATEOAS example
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What's next?
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The Spring Boot configuration
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Changing the default embedded web server
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Implementing Spring Boot security
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Enabling cross-origin access for microservices
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Implementing Spring Boot messaging
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Developing a comprehensive microservice example
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Spring Boot actuators
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Configuring application information
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Adding a custom health module
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Documenting microservices
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Summary
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3. Applying Microservices Concepts
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3. Applying Microservices Concepts
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Patterns and common design decisions
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Microservices challenges
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The microservices capability model
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Summary
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4. Microservices Evolution – A Case Study
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4. Microservices Evolution – A Case Study
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Reviewing the microservices capability model
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Understanding the PSS application
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Death of the monolith
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Microservices to the rescue
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The business case
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Plan the evolution
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Migrate modules only if required
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Target architecture
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Target implementation view
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Summary
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5. Scaling Microservices with Spring Cloud
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5. Scaling Microservices with Spring Cloud
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Reviewing microservices capabilities
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Reviewing BrownField's PSS implementation
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What is Spring Cloud?
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Setting up the environment for BrownField PSS
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Spring Cloud Config
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Feign as a declarative REST client
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Ribbon for load balancing
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Eureka for registration and discovery
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Zuul proxy as the API gateway
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Streams for reactive microservices
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Summarizing the BrownField PSS architecture
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Summary
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6. Autoscaling Microservices
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6. Autoscaling Microservices
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Reviewing the microservice capability model
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Scaling microservices with Spring Cloud
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Understanding the concept of autoscaling
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Autoscaling approaches
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Autoscaling BrownField PSS microservices
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Summary
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7. Logging and Monitoring Microservices
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7. Logging and Monitoring Microservices
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Reviewing the microservice capability model
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Understanding log management challenges
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A centralized logging solution
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The selection of logging solutions
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Monitoring microservices
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Data analysis using data lakes
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Summary
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8. Containerizing Microservices with Docker
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8. Containerizing Microservices with Docker
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Reviewing the microservice capability model
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Understanding the gaps in BrownField PSS microservices
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What are containers?
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The difference between VMs and containers
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The benefits of containers
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Microservices and containers
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Introduction to Docker
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Deploying microservices in Docker
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Running RabbitMQ on Docker
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Using the Docker registry
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Microservices on the cloud
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Running BrownField services on EC2
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Updating the life cycle manager
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The future of containerization – unikernels and hardened security
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Summary
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9. Managing Dockerized Microservices with Mesos and Marathon
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9. Managing Dockerized Microservices with Mesos and Marathon
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Reviewing the microservice capability model
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The missing pieces
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Why cluster management is important
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What does cluster management do?
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Relationship with microservices
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Relationship with virtualization
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Cluster management solutions
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Cluster management with Mesos and Marathon
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Implementing Mesos and Marathon for BrownField microservices
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A place for the life cycle manager
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The technology metamodel
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Summary
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10. The Microservices Development Life Cycle
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10. The Microservices Development Life Cycle
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Reviewing the microservice capability model
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The new mantra of lean IT – DevOps
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Meeting the trio – microservices, DevOps, and cloud
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Practice points for microservices development
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Microservices development governance, reference architectures, and libraries
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Summary
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Index
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Index

Data analysis using data lakes

Similarly to the scenario of fragmented logs and monitoring, fragmented data is another challenge in the microservice architecture. Fragmented data poses challenges in data analytics. This data may be used for simple business event monitoring, data auditing, or even deriving business intelligence out of the data.

A data lake or data hub is an ideal solution to handling such scenarios. An event-sourced architecture pattern is generally used to share the state and state changes as events with an external data store. When there is a state change, microservices publish the state change as events. Interested parties may subscribe to these events and process them based on their requirements. A central event store may also subscribe to these events and store them in a big data store for further analysis.

One of the commonly followed architectures for such data handling is shown in the following diagram:

State change events generated from the microservice—in our case...

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