Microservices with Spring Boot and Spring Cloud

Build resilient and scalable microservices using Spring Cloud, Istio, and Kubernetes, 2nd Edition

Magnus Larsson

• Éditeur: Packt Publishing
• Année: 2021
• ISBN:
  9781801079150
• Édition: 2
• Sujet: Computer Science
• Sous-sujet: Programming in Java

Create and deploy production-quality microservices-based applications — New edition updated for the smooth running of Spring, Java, Kubernetes, and Istio, with an introduction to Helm 3 and support for Mac and Windows with WSL2

Key Features

• Build cloud-native production-ready microservices with this comprehensively updated guide
• Understand the challenges of building large-scale microservice architectures
• Learn how to get the best out of Spring Cloud, Kubernetes, and Istio in combination

Book Description

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.

What you will learn

• Build reactive microservices using Spring Boot
• Develop resilient and scalable microservices using Spring Cloud
• Use OAuth 2.1/OIDC and Spring Security to protect public APIs
• Implement Docker to bridge the gap between development, testing, and production
• Deploy and manage microservices with Kubernetes
• Apply Istio for improved security, observability, and traffic management
• Write and run automated microservice tests with JUnit, testcontainers, Gradle, and bash

Who this book is for

If you're a Java or Spring Boot developer learning how to build microservice landscapes from scratch, then this book is for you. You don't need any prior knowledge about microservices architecture to get started, but a solid grasp and enough experience in Java and Spring Boot to build apps autonomously is a must.

18

Using a Service Mesh to Improve Observability and Management

In this chapter, you will be introduced to the concept of a service mesh and see how its capabilities can be used to handle challenges in a system landscape of microservices, in areas including security, policy enforcement, resilience, and traffic management. A service mesh can also be used to provide observability, the capability to visualize how traffic flows between microservices.

A service mesh overlaps partly with the capabilities of Spring Cloud and Kubernetes that we learned about earlier in this book. But most of the functionality in a service mesh complements Spring Cloud and Kubernetes, as we will see in this chapter.

The following topics will be covered in this chapter:

• An introduction to the service mesh concept and Istio, a popular open source implementation
• Deploying Istio in Kubernetes
• Creating, observing, and securing a service mesh
• Ensuring that a service mesh is resilient
• Performing zero-downtime updates
• Testing the microservice landscape using Docker Compose to ensure that the source code in the microservices is not locked into either Kubernetes or Istio

Technical requirements

For instructions on how to install tools used in this book and how to access the source code for this book, see:

• Chapter 21 for macOS
• Chapter 22 for Windows

The code examples in this chapter all come from the source code in $BOOK_HOME/Chapter18.

If you want to view the changes applied to the source code in this chapter, that is, see what it took to create a service mesh using Istio, you can compare it with the source code for Chapter 17, Implementing Kubernetes Features to Simplify the System Landscape. You can use your favorite diff tool and compare the two folders, $BOOK_HOME/Chapter17 and $BOOK_HOME/Chapter18.

Introducing service meshes using Istio

A service mesh is an infrastructure layer that controls and observes the communication between services, for example, microservices. The capabilities in a service mesh, for example, observability, security, policy enforcement, resilience, and traffic management, are implemented by controlling and monitoring all internal communication inside the service mesh, that is, between the microservices in the service mesh.

One of the core components in a service mesh is a lightweight proxy component that is injected into each microservice that will be part of the service mesh. All traffic in and out of a microservice is configured to go through its proxy component. The proxy components are configured at runtime by a control plane in the service mesh, using APIs exposed by the proxy. The control plane also collects telemetry data through these APIs from the proxies to visualize how the traffic flows in the service mesh.

A service mesh also contains a data plane, consisting of the proxy components together with separate components for handling external traffic to and from the service mesh, known as an ingress gateway and an egress gateway. The gateway components also communicate with the control plane using a proxy component. This is illustrated by the following diagram:

Figure 18.1: Service mesh with a control plane and a data plane

The first publicly available implementation of a service mesh was the open source project Linkerd, managed by Buoyant (https://linkerd.io), having its origins in Twitter's Finagle project (http://twitter.github.io/finagle). It was launched in 2016 and, one year later, in 2017, IBM, Google, and Lyft launched the open source project Istio (https://istio.io). Since then, several service mesh projects have been launched. For an overview of available implementations, see the service mesh category in CNCF's cloud-native landscape map: https://landscape.cncf.io/card-mode?category=service-mesh&grouping=category. In this book, we will use Istio.

Introducing Istio

Istio can be deployed on a number of Kubernetes distributions and platforms using various installation tools as described in https://istio.io/docs/setup. We will use Istio's CLI tool, istioctl, to install Istio in our Minikube-based, single-node Kubernetes cluster.

Istio is, as explained previously, divided into a control plane and a data plane. As an operator, we will define the desired state by creating Istio objects in the Kubernetes API server, for example, declaring routing rules. The control plane will read these objects and send commands to the proxies in the data plane to take actions according to the desired state, for example, configuring routing rules. The proxies handle the actual communication between the microservices and report back telemetry data to the control plane. The telemetry data is used in the control plane to visualize what's going on in the service mesh.

When deploying Istio on Kubernetes, most of its runtime components are deployed in a sep...