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  • Book Overview & Buying Kubernetes Autoscaling
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Kubernetes Autoscaling

Kubernetes Autoscaling

By : Christian Melendez
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Kubernetes Autoscaling

Kubernetes Autoscaling

By: Christian Melendez

Overview of this book

Kubernetes is the backbone of modern containerized infrastructure, but scaling it efficiently remains a challenge. Kubernetes Autoscaling equips cloud professionals with this comprehensive guide to dynamically scaling applications and infrastructure using the powerful combination of Kubernetes Event-Driven Autoscaler (KEDA) and Karpenter, AWS’s next-generation cluster autoscaler. You’ll begin with autoscaling fundamentals, move through HPA and VPA, and then get hands-on KEDA for event-driven workloads and Karpenter for data plane scaling. With the help of real-world use cases, best practices, and detailed patterns, you’ll deploy resilient, scalable, and cost-effective Kubernetes clusters across production environments. By the end of this book, you’ll be able to implement practical autoscaling strategies to improve performance, reduce cloud costs, and eliminate over-provisioning.
Table of Contents (20 chapters)
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1
Part 1: Getting started with Kubernetes Autoscaling
5
Part 2: Workload Autoscaling and KEDA
9
Part 3: Node Autoscaling and Karpenter
14
Part 4: Use Cases, Patterns, and Recommendations
18
Other Books You May Enjoy
19
Index

Technical Requirements

To practice what you'll be learning throughout this book, you need to have access to a Kubernetes cluster. In this chapter, I'm offering two options for cluster creation: a local setup and a cloud-based solution in AWS. If you're just starting out or you want to focus solely on workload scaling in the upcoming chapters, the local option using Kind (Kubernetes in Docker) is a good choice. Alternatively, you could use Docker Desktop and turn on Kubernetes or use a Kubernetes playground like Killercoda or Play with Kubernetes.However, if you're eager to dive into the full cloud experience from the start, I'll also provide instructions for setting up an Amazon EKS cluster using Terraform. This option will give you a more realistic environment, closely mimicking production scenarios. Just remember, if you choose this route, to delete all resources after your study sessions to avoid unnecessary charges.To make the process as smooth as possible...

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Kubernetes Autoscaling
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