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The DevOps 2.5 Toolkit

You're reading from   The DevOps 2.5 Toolkit Monitoring, Logging, and Auto-Scaling Kubernetes: Making Resilient, Self-Adaptive, And Autonomous Kubernetes Clusters

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Product type Paperback
Published in Nov 2019
Publisher Packt
ISBN-13 9781838647513
Length 322 pages
Edition 1st Edition
Concepts
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Author (1):
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Viktor Farcic Viktor Farcic
Author Profile Icon Viktor Farcic
Viktor Farcic
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Table of Contents (9) Chapters Close

1. Autoscaling Deployments and StatefulSets Based on Resource Usage FREE CHAPTER 2. Auto-scaling Nodes of a Kubernetes Cluster 3. Collecting and Querying Metrics and Sending Alerts 4. Debugging Issues Discovered Through Metrics and Alerts 5. Extending HorizontalPodAutoscaler with Custom Metrics 6. Visualizing Metrics and Alerts 7. Collecting and Querying Logs 8. What Did We Do? 9. Other Books You May Enjoy

Cluster Autoscaler compared in GKE, EKS, and AKS

Cluster Autoscaler is a prime example of the differences between different managed Kubernetes offerings. We'll use it to compare the three major Kubernetes-as-a-Service providers.

I'll limit the comparison between the vendors only to the topics related to Cluster Autoscaling.

GKE is a no-brainer for those who can use Google to host their cluster. It is the most mature and feature-rich platform. They started Google Kubernetes Engine (GKE) long before anyone else. When we combine their head start with the fact that they are the major contributor to Kubernetes and hence have the most experience, it comes as no surprise that their offering is way above others.

When using GKE, everything is baked into the cluster. That includes Cluster Autoscaler. We do not have to execute any additional commands. It simply works out of the...

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