Book Image

Mastering Kubernetes - Third Edition

By : Gigi Sayfan
Book Image

Mastering Kubernetes - Third Edition

By: Gigi Sayfan

Overview of this book

The third edition of Mastering Kubernetes is updated with the latest tools and code enabling you to learn Kubernetes 1.18’s latest features. This book primarily concentrates on diving deeply into complex concepts and Kubernetes best practices to help you master the skills of designing and deploying large clusters on various cloud platforms. The book trains you to run complex stateful microservices on Kubernetes including advanced features such as horizontal pod autoscaling, rolling updates, resource quotas, and persistent storage backend. With the two new chapters, you will gain expertise in serverless computing and utilizing service meshes. As you proceed through the chapters, you will explore different options for network configuration and learn to set up, operate, and troubleshoot Kubernetes networking plugins through real-world use cases. Furthermore, you will understand the mechanisms of custom resource development and its utilization in automation and maintenance workflows. By the end of this Kubernetes book, you will graduate from an intermediate to advanced Kubernetes professional.
Table of Contents (19 chapters)
17
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18
Index

High availability, scalability, and capacity planning

Highly available systems must also be scalable. The load on most complicated distributed systems can vary dramatically based on the time of day, weekdays versus weekends, seasonal effects, marketing campaigns, and many other factors. Successful systems will have more users over time and accumulate more and more data. That means that the physical resources of the clusters—mostly nodes and storage—will have to grow over time too. If your cluster is under-provisioned, it will not be able to satisfy all the demand and it will not be available because requests will time out or be queued up and not processed fast enough.

This is the realm of capacity planning. One simple approach is to over-provision your cluster. Anticipate the demand and make sure you have enough of a buffer for spikes of activity. But be aware that this approach suffers from several deficiencies:

  • For highly dynamic and complicated distributed...