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The Complete Kubernetes Guide

You're reading from   The Complete Kubernetes Guide Become an expert in container management with the power of Kubernetes

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Product type Course
Published in May 2019
Publisher Packt
ISBN-13 9781838647346
Length 628 pages
Edition 1st Edition
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Authors (3):
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Jesse White Jesse White
Author Profile Icon Jesse White
Jesse White
Gigi Sayfan Gigi Sayfan
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Gigi Sayfan
Jonathan Baier Jonathan Baier
Author Profile Icon Jonathan Baier
Jonathan Baier
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Table of Contents (26) Chapters Close

Title Page
Copyright and Credits
About Packt
Contributors
Preface
1. Introduction to Kubernetes 2. Understanding Kubernetes Architecture FREE CHAPTER 3. Building a Foundation with Core Kubernetes Constructs 4. Working with Networking, Load Balancers, and Ingress 5. Using Critical Kubernetes Resources 6. Exploring Kubernetes Storage Concepts 7. Monitoring and Logging 8. Monitoring, Logging, and Troubleshooting 9. Operating Systems, Platforms, and Cloud and Local Providers 10. Creating Kubernetes Clusters 11. Cluster Federation and Multi-Tenancy 12. Cluster Authentication, Authorization, and Container Security 13. Running Stateful Applications with Kubernetes 14. Rolling Updates, Scalability, and Quotas 15. Advanced Kubernetes Networking 16. Kubernetes Infrastructure Management 17. Customizing Kubernetes - API and Plugins 18. Handling the Kubernetes Package Manager 19. The Future of Kubernetes 1. Other Books You May Enjoy Index

Horizontal pod autoscaling


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

The following diagram illustrates the different players and their relationships:

As you can see, the horizontal pod autoscaler doesn't create or destroy pods directly. It relies instead on the replication controller or deployment resources. This is very smart because you don't need to deal with situations where autoscaling conflicts with the replication controller or deployments trying to scale the number of pods, unaware of the autoscaler's efforts.

The autoscaler automatically does what we had to do ourselves before. Without the autoscaler, if we had a replication controller with replicas set to 3, but we determined that based on average CPU utilization we actually needed 4, then...

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