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

Horizontal pod autoscaling

Kubernetes can watch over your pods and scale them when the CPU utilization, memory, or some other metric crosses a threshold. The autoscaling resource specifies the details (the percentage of CPU and how often to check) and the corresponding autoscaling controller adjusts the number of replicas if needed.

The following diagram illustrates the different players and their relationships:

Figure 8.4: Horizontal pod autoscaling

As you can see, the horizontal pod autoscaler doesn’t create or destroy pods directly. It adjusts the number of replicas in a Deployment or StatefulSet resource and its corresponding controllers take care of actually creating and destroying pods. This is very smart because you don’t need to deal with situations where autoscaling conflicts with the normal operation of those controllers, unaware of the autoscaler efforts.

The autoscaler automatically does what we had to do ourselves before. Without the...