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)
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Index

Monitoring Kubernetes Clusters

In the previous chapter, we looked at serverless computing and its manifestations on Kubernetes. A lot of innovation happens in this space, and it is both super useful and fascinating to follow the evolution.

In this chapter, we’re going to talk about how to make sure your systems are up and running and performing correctly, and how to respond when they’re not. In Chapter 3, High Availability and Reliability, we discussed related topics. The focus here is on knowing what’s going on in your system and what practices and tools you can use.

There are many aspects to monitoring, such as logging, metrics, distributed tracing, error reporting, and alerting. Practices like auto-scaling and self-healing depend on monitoring to detect that there is a need to scale or to heal.

The topics we will cover in this chapter include:

  • Understanding observability
  • Logging with Kubernetes
  • Recording metrics with Kubernetes...