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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

Combining AWS CloudWatch with an EKS cluster

Unlike GKE that has a logging solution baked into a cluster, EKS requires us to set up a solution. It does provide CloudWatch service, but we need to ensure that the logs are shipped there from our cluster.

Just as before, we'll use Fluentd to collect logs and ship them to CloudWatch. Or, to be more precise, we'll use a Fluentd tag built specifically for CloudWatch. As you probably already know, we'll also need an IAM policy that will allow Fluentd to communicate with CloudWatch.

All in all, the setup we are about to make will be very similar to the one we did with Papertrail, except that we'll store the logs in CloudWatch, and that we'll have to put some effort into creating AWS permissions.

Before we proceed, I'll assume that you still have the environment variables AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY...

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