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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

Collecting and Querying Metrics and Sending Alerts

Insufficient facts always invite danger.

- Spock

So far, we explored how to leverage some of Kubernetes core features. We used HorizontalPodAutoscaler and Cluster Autoscaler. While the former relies on Metrics Server, the latter is not based on metrics, but on Scheduler's inability to place Pods within the existing cluster capacity. Even though Metrics Server does provide some basic metrics, we are in desperate need for more.

We have to be able to monitor our cluster and Metrics Server is just not enough. It contains a limited amount of metrics, it keeps them for a very short period, and it does not allow us to execute anything but simplest queries. I can't say that we are blind if we rely only on Metrics Server, but that we are severely impaired. Without increasing the number of metrics we're collecting, as well...

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