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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

Scaling up the cluster

The objective is to scale the nodes of our cluster to meet the demand of our Pods. We want not only to increase the number of worker nodes when we need additional capacity, but also to remove them when they are underused. For now, we'll focus on the former, and explore the latter afterward.

Let's start by taking a look at how many nodes we have in the cluster.

 1  kubectl get nodes

The output, from GKE, is as follows.

NAME             STATUS ROLES  AGE   VERSION
gke-devops25-... Ready  <none> 5m27s v1.9.7-gke.6
gke-devops25-... Ready  <none> 5m28s v1.9.7-gke.6
gke-devops25-... Ready  <none> 5m24s v1.9.7-gke.6

In your case, the number of nodes might differ. That's not important. What matters is to remember how many you have right now since that number will change soon.

Let's take a look at the definition of the go-demo...

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