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Hands-On Microservices with Spring Boot and Spring Cloud

You're reading from   Hands-On Microservices with Spring Boot and Spring Cloud Build and deploy Java microservices using Spring Cloud, Istio, and Kubernetes

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Product type Paperback
Published in Sep 2019
Publisher Packt
ISBN-13 9781789613476
Length 668 pages
Edition 1st Edition
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Author (1):
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Magnus Larsson AB Magnus Larsson AB
Author Profile Icon Magnus Larsson AB
Magnus Larsson AB
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Table of Contents (25) Chapters Close

Preface 1. Section 1: Getting Started with Microservice Development Using Spring Boot
2. Introduction to Microservices FREE CHAPTER 3. Introduction to Spring Boot 4. Creating a Set of Cooperating Microservices 5. Deploying Our Microservices Using Docker 6. Adding an API Description Using OpenAPI/Swagger 7. Adding Persistence 8. Developing Reactive Microservices 9. Section 2: Leveraging Spring Cloud to Manage Microservices
10. Introduction to Spring Cloud 11. Adding Service Discovery Using Netflix Eureka and Ribbon 12. Using Spring Cloud Gateway to Hide Microservices Behind an Edge Server 13. Securing Access to APIs 14. Centralized Configuration 15. Improving Resilience Using Resilience4j 16. Understanding Distributed Tracing 17. Section 3: Developing Lightweight Microservices Using Kubernetes
18. Introduction to Kubernetes 19. Deploying Our Microservices to Kubernetes 20. Implementing Kubernetes Features as an Alternative 21. Using a Service Mesh to Improve Observability and Management 22. Centralized Logging with the EFK Stack 23. Monitoring Microservices 24. Other Books You May Enjoy

Trying out the EFK stack

The first thing we need to do before we can try out the EFK stack is initialize Kibana so it knows what search indices to use in Elasticsearch. Once that is done, we will try out the following, in my experience, common tasks:

  1. We will start by analyzing of what types of log records Fluentd has collected and stored in Elasticsearch. Kibana has a very useful visualization capability that can be used for this.
  2. Next, we will learn how to discover log records from different microservices that belong to one and the same processing of an external request to the API. We will use the trace ID in the log records as a correlation ID to find related log records.
  3. Thirdly, we will learn how to use Kibana to perform root cause analysis, that is, find the actual reason for an error.
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