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Kubernetes and Docker - An Enterprise Guide

You're reading from   Kubernetes and Docker - An Enterprise Guide Effectively containerize applications, integrate enterprise systems, and scale applications in your enterprise

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Product type Paperback
Published in Nov 2020
Publisher Packt
ISBN-13 9781839213403
Length 526 pages
Edition 1st Edition
Tools
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Authors (2):
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Marc Boorshtein Marc Boorshtein
Author Profile Icon Marc Boorshtein
Marc Boorshtein
Scott Surovich Scott Surovich
Author Profile Icon Scott Surovich
Scott Surovich
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Toc

Table of Contents (20) Chapters Close

Preface 1. Section 1: Docker and Container Fundamentals
2. Chapter 1: Docker and Container Essentials FREE CHAPTER 3. Chapter 2: Working with Docker Data 4. Chapter 3: Understanding Docker Networking 5. Section 2: Creating Kubernetes Development Clusters, Understanding objects, and Exposing Services
6. Chapter 4: Deploying Kubernetes Using KinD 7. Chapter 5: Kubernetes Bootcamp 8. Chapter 6: Services, Load Balancing, and External DNS 9. Section 3: Running Kubernetes in the Enterprise
10. Chapter 7: Integrating Authentication into Your Cluster 11. Chapter 8: RBAC Policies and Auditing 12. Chapter 9: Deploying a Secured Kubernetes Dashboard 13. Chapter 10: Creating PodSecurityPolicies 14. Chapter 11: Extending Security Using Open Policy Agent 15. Chapter 12: Auditing using Falco and EFK 16. Chapter 13: Backing Up Workloads 17. Chapter 14: Provisioning a Platform 18. Assessments 19. Other Books You May Enjoy

Chapter 4: Deploying Kubernetes Using KinD

One of the largest obstacles to learning Kubernetes is having enough resources to create a cluster for testing or development. Like most IT professionals, we like to have a Kubernetes cluster on our laptops for demonstrations and for testing products in general.

Often, you may have a need to run multiple clusters for a complex demonstration, such as a multi-cluster service mesh or testing kubefed2. These scenarios would require multiple servers to create the necessary clusters, which, in turn, would require a lot of RAM and a hypervisor.

To do full testing on a multiple cluster scenario, you would need to create six nodes for each cluster. If you created the clusters using virtual machines, you would need to have enough resources to run 6 virtual machines. Each of the machines would have an overhead including disk space, memory, and CPU utilization.

But what if you could create a cluster using just containers? Using containers,...

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