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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

Using instrumentation to provide more detailed metrics

We shouldn't just say that the go-demo-5 application is slow. That would not provide enough information for us to quickly inspect the code in search of the exact cause of that slowness. We should be able to do better and deduce which part of the application is misbehaving. Can we pinpoint a specific path that produces slow responses? Are all methods equally slow, or the issue is limited only to one? Do we know which function produces slowness? There are many similar questions we should be able to answer in situations like that. But we can't, with the current metrics. They are too generic, and they can usually only tell us that a specific Kubernetes resource is misbehaving. The metrics we're collecting are too broad to answer application-specific questions.

The metrics we explored so far are a combination of...

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