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Mastering Kubernetes

You're reading from   Mastering Kubernetes Dive into Kubernetes and learn how to create and operate world-class cloud-native systems

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781804611395
Length 746 pages
Edition 4th Edition
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Author (1):
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Gigi Sayfan Gigi Sayfan
Author Profile Icon Gigi Sayfan
Gigi Sayfan
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Table of Contents (21) Chapters Close

Preface 1. Understanding Kubernetes Architecture 2. Creating Kubernetes Clusters FREE CHAPTER 3. High Availability and Reliability 4. Securing Kubernetes 5. Using Kubernetes Resources in Practice 6. Managing Storage 7. Running Stateful Applications with Kubernetes 8. Deploying and Updating Applications 9. Packaging Applications 10. Exploring Kubernetes Networking 11. Running Kubernetes on Multiple Clusters 12. Serverless Computing on Kubernetes 13. Monitoring Kubernetes Clusters 14. Utilizing Service Meshes 15. Extending Kubernetes 16. Governing Kubernetes 17. Running Kubernetes in Production 18. The Future of Kubernetes 19. Other Books You May Enjoy
20. Index

Additional extension points

There are some additional extension points that don’t fit into the categories we have discussed so far.

Providing custom metrics for horizontal pod autoscaling

Prior to Kubernetes 1.6, custom metrics were implemented as a Heapster model. In Kubernetes 1.6, new custom metrics APIs landed and matured gradually. As of Kubernetes 1.9, they are enabled by default. As you may recall, Keda (https://keda.sh) is a project that focuses on custom metrics for autoscaling. However, if for some reason Keda doesn’t meet your needs, you can implement your own custom metrics. Custom metrics rely on API aggregation. The recommended path is to start with the custom metrics API server boilerplate, available here: https://github.com/kubernetes-sigs/custom-metrics-apiserver.

Then, you can implement the CustomMetricsProvider interface:

type CustomMetricsProvider interface {
    // GetRootScopedMetricByName fetches a particular metric for a particular...
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