Book Image

Mastering Service Mesh

By : Anjali Khatri, Vikram Khatri
Book Image

Mastering Service Mesh

By: Anjali Khatri, Vikram Khatri

Overview of this book

Although microservices-based applications support DevOps and continuous delivery, they can also add to the complexity of testing and observability. The implementation of a service mesh architecture, however, allows you to secure, manage, and scale your microservices more efficiently. With the help of practical examples, this book demonstrates how to install, configure, and deploy an efficient service mesh for microservices in a Kubernetes environment. You'll get started with a hands-on introduction to the concepts of cloud-native application management and service mesh architecture, before learning how to build your own Kubernetes environment. While exploring later chapters, you'll get to grips with the three major service mesh providers: Istio, Linkerd, and Consul. You'll be able to identify their specific functionalities, from traffic management, security, and certificate authority through to sidecar injections and observability. By the end of this book, you will have developed the skills you need to effectively manage modern microservices-based applications.
Table of Contents (31 chapters)
1
Section 1: Cloud-Native Application Management
4
Section 2: Architecture
8
Section 3: Building a Kubernetes Environment
10
Section 4: Learning about Istio through Examples
18
Section 5: Learning about Linkerd through Examples
24
Section 6: Learning about Consul through Examples

Summary

As we have seen in this chapter, the Linkerd observability feature is simple and out of the box, which means it doesn't need any special configuration. It presents the key performance indicators for the deployment, pod, and route levels through both the CLI and the dashboard. Its integration with Prometheus through a built-in panel for Grafana is an easy way to drill down from a higher level to a lower level, as shown in the exercises in this chapter.

One of the interesting and useful features of Linkerd is that it can aggregate and show Key Performance Indicators (KPI) such as RPS, P50, P95, P99, and Success Rate (SR). These KPIs can be very helpful to SRE team members when they need to investigate problems.

With this chapter, we have explored the various features of the Linkerd service mesh. In the next chapter, we will go through the third service mesh –...