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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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Toc

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

What now?

You know what to do. Destroy the cluster if you created it specifically for this chapter.

Before you leave, you might want to go over the main points of this chapter.

  • For any but the smallest systems, going from one resource to another and from one node to another to find the cause of an issue is anything but practical, reliable, and fast.
  • More often than not, kubectl logs command does not provide us with enough options to perform anything but simplest retrieval of logs.
  • Elasticsearch is excellent, but it does too much. Its lack of focus makes it inferior to Prometheus for storing and querying metrics, as well as sending alerts based on such data.
  • Logs themselves are too expensive to parse, and most of the time they do not provide enough data to act as metrics.
  • We need logs centralized in a single location so that we can explore logs from any part of the system.
  • We...
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