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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

Measuring containers memory and CPU usage

If you are familiar with Kubernetes, you understand the importance of defining resource requests and limits. Since we already explored kubectl top pods command, you might have set the requested resources to match the current usage, and you might have defined the limits as being above the requests. That approach might work on the first day. But, with time, those numbers will change and we will not be able to get the full picture through kubectl top pods. We need to know how much memory and CPU containers use when on their peak loads, and how much when they are under less stress. We should observe those metrics over time, and adjust periodically.

Even if we do somehow manage to guess how much memory and CPU a container needs, those numbers might change from one release to another. Maybe we introduced a feature that requires more memory or...

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