Book Image

Mastering Kubernetes - Fourth Edition

By : Gigi Sayfan
3.3 (3)
Book Image

Mastering Kubernetes - Fourth Edition

3.3 (3)
By: Gigi Sayfan

Overview of this book

The fourth edition of the bestseller Mastering Kubernetes includes the most recent tools and code to enable you to learn the latest features of Kubernetes 1.25. This book contains a thorough exploration of complex concepts and best practices to help you master the skills of designing and deploying large-scale distributed systems on Kubernetes clusters. You’ll learn how to run complex stateless and stateful microservices on Kubernetes, including advanced features such as horizontal pod autoscaling, rolling updates, resource quotas, and persistent storage backends. In addition, you’ll understand how to utilize serverless computing and service meshes. Further, two new chapters have been added. “Governing Kubernetes” covers the problem of policy management, how admission control addresses it, and how policy engines provide a powerful governance solution. “Running Kubernetes in Production” shows you what it takes to run Kubernetes at scale across multiple cloud providers, multiple geographical regions, and multiple clusters, and it also explains how to handle topics such as upgrades, capacity planning, dealing with cloud provider limits/quotas, and cost management. By the end of this Kubernetes book, you’ll have a strong understanding of, and hands-on experience with, a wide range of Kubernetes capabilities.
Table of Contents (21 chapters)
19
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20
Index

Summary

In this chapter, we covered the topics of monitoring, observability, and troubleshooting. We started with a review of the various aspects of monitoring: logs, metrics, error reporting, and distributed tracing. Then, we discussed how to incorporate monitoring capabilities into your Kubernetes cluster. We looked at several CNCF projects, like Fluentd for log aggregation, Prometheus for metrics collection and alert management, Grafana for visualization, and Jaeger for distributed tracing. Then, we explored troubleshooting large distributed systems. We realized how difficult it can be and why we need so many different tools to conquer the issues.

In the next chapter, we will take it to the next level and dive into service meshes. I’m super excited about service meshes because they take much of the complexity related to cloud-native microservice-based applications and externalize them outside of the microservices. That has a lot of real-world value.

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