Book Image

Building Microservices with Spring

By : Dinesh Rajput, Rajesh R V
Book Image

Building Microservices with Spring

By: Dinesh Rajput, Rajesh R V

Overview of this book

Getting Started with Spring Microservices begins with an overview of the Spring Framework 5.0, its design patterns, and its guidelines that enable you to implement responsive microservices at scale. You will learn how to use GoF patterns in application design. You will understand the dependency injection pattern, which is the main principle behind the decoupling process of the Spring Framework and makes it easier to manage your code. Then, you will learn how to use proxy patterns in aspect-oriented programming and remoting. Moving on, you will understand the JDBC template patterns and their use in abstracting database access. After understanding the basics, you will move on to more advanced topics, such as reactive streams and concurrency. Written to the latest specifications of Spring that focuses on Reactive Programming, the Learning Path teaches you how to build modern, internet-scale Java applications in no time. Next, you will understand how Spring Boot is used to deploying serverless autonomous services by removing the need to have a heavyweight application server. You’ll also explore ways to deploy your microservices to Docker and managing them with Mesos. By the end of this Learning Path, you will have the clarity and confidence for implementing microservices using Spring Framework. This Learning Path includes content from the following Packt products: • Spring 5 Microservices by Rajesh R V • Spring 5 Design Patterns by Dinesh Rajput
Table of Contents (22 chapters)
Title Page
Copyright
About Packt
Contributors
Preface
Index

Centralized logging solution


In order to address the earlier stated challenges, traditional logging solutions require serious rethinking. The new logging solution, in addition to addressing the preceding challenges, is also expected to support the capabilities summarized here:

  • Ability to collect all log messages and run analytics on top of the log messages
  • Ability to correlate and track transactions end-to-end
  • Ability to keep log information for longer time periods for trending and forecasting
  • Ability to eliminate dependency on the local disk system
  • Ability to aggregate log information coming from multiple sources, such as network devices, operating system, microservices, and so on

The solution to these problems is to centrally store and analyze all log messages, irrespective of the source of the log. The fundamental principle employed in the new logging solution is to detach log storage and processes from the service execution environments. Big data solutions are better suited for storing and...