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Microservices with Spring Boot and Spring Cloud

Microservices with Spring Boot and Spring Cloud - Second Edition

By : Magnus Larsson
4.3 (12)
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Microservices with Spring Boot and Spring Cloud

Microservices with Spring Boot and Spring Cloud

4.3 (12)
By: Magnus Larsson

Overview of this book

Want to build and deploy microservices, but don’t know where to start? Welcome to Microservices with Spring Boot and Spring Cloud. This edition features the most recent versions of Spring, Java, Kubernetes, and Istio, demonstrating faster and simpler handling of Spring Boot, local Kubernetes clusters, and Istio installation. The expanded scope includes native compilation of Spring-based microservices, support for Mac and Windows with WSL2, and an introduction to Helm 3 for packaging and deployment. A revamped security chapter now follows the OAuth 2.1 specification and makes use of the newly launched Spring Authorization Server from the Spring team. You’ll start with a set of simple cooperating microservices, then add persistence and resilience, make your microservices reactive, and document their APIs using OpenAPI. Next, you’ll learn how fundamental design patterns are applied to add important functionality, such as service discovery with Netflix Eureka and edge servers with Spring Cloud Gateway. You’ll deploy your microservices using Kubernetes and adopt Istio, then explore centralized log management using the Elasticsearch, Fluentd, and Kibana (EFK) stack, and then monitor microservices using Prometheus and Grafana. By the end of this book, you'll be building scalable and robust microservices using Spring Boot and Spring Cloud.
Table of Contents (6 chapters)
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Monitoring Microservices

In this chapter, we will learn how to use Prometheus and Grafana to collect, monitor, and alert about performance metrics. As we mentioned in Chapter 1, Introduction to Microservices, in a production environment it is crucial to be able to collect metrics for application performance and hardware resource usage. Monitoring these metrics is required to avoid long response times or outages for API requests and other processes.

To be able to monitor a system landscape of microservices in a cost-efficient and proactive way, we must also be able to define alarms that are triggered automatically if the metrics exceed the configured limits.

In this chapter, we will cover the following topics:

  • Introduction to performance monitoring using Prometheus and Grafana
  • Changes in source code for collecting application metrics
  • Building and deploying the microservices
  • Monitoring microservices using Grafana dashboards
  • Setting up alarms...
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