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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

Can we scale up too much or de-scale to zero nodes?

If we let Cluster Autoscaler do its "magic" without defining any thresholds, our cluster or our wallet might be at risk.

We might, for example, misconfigure HPA and end up scaling Deployments or StatefulSets to a huge number of replicas. As a result, Cluster Autoscaler might add too many nodes to the cluster. As a result, we could end up paying for hundreds of nodes, even though we need much less. Luckily, AWS, Azure, and GCP limit how many nodes we can have so we cannot scale to infinity. Nevertheless, we should not allow Cluster Autoscaler to go over some limits.

Similarly, there is a danger that Cluster Autoscaler will scale down to too few nodes. Having zero nodes is almost impossible since that would mean that we have no Pods in the cluster. Still, we should maintain a healthy minimum of nodes, even if that means...

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