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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

Comparing actual resource usage with defined requests

If we define container resources inside a Pod and without relying on actual usage, we are just guessing how much memory and CPU we expect a container to use. I'm sure that you already know why guessing, in the software industry, is a terrible idea, so I'll focus on Kubernetes aspects only.

Kubernetes treats Pods with containers that do not have specified resources as the BestEffort Quality of Service (QoS). As a result, if it ever runs out of memory or CPU to serve all the Pods, those are the first to be forcefully removed to leave space for others. If such Pods are short lived as, for example, those used as one-shot agents for continuous delivery processes, BestEffort QoS is not a bad idea. But, when our applications are long-lived, BestEffort QoS should be unacceptable. That means that in most cases, we do have...

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