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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

The rules governing nodes scale-down

Cluster Autoscaler iterates every 10 seconds (configurable through the --scan-interval flag). If the conditions for scaling up are not met, it checks whether there are unneeded nodes.

It will consider a node eligible for removal when all of the following conditions are met.

  • The sum of CPU and memory requests of all Pods running on a node is less than 50% of the node's allocatable resources (configurable through the --scale-down-utilization-threshold flag).
  • All Pods running on the node can be moved to other nodes. The exceptions are those that run on all the nodes like those created through DaemonSets.

Whether a Pod might not be eligible for rescheduling to a different node when one of the following conditions are met.

  • A Pod with affinity or anti-affinity rules that tie it to a specific node.
  • A Pod that uses local storage.
  • A Pod created...
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