Simplifying Kubernetes Deployments using Kustomize

Lab Steps

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Logging in to the Amazon Web Services Console
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Connecting to the CloudAcademy Web based IDE
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Deploy Base
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Deploy Staging
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Deploy Production

Ready for the real environment experience?

DifficultyIntermediate
Time Limit1h 30m
Students10
Ratings
5/5
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Description

Kustomize is a tool for customizing Kubernetes configurations, simplifying the rollout and deployment of applications into clusters. It has the following features to manage application configuration files:

  • generating resources from other sources
  • setting cross-cutting fields for resources
  • composing and customizing collections of resources

In this Lab scenario, you'll learn how to use Kustomize Bases and Overlays to deploy 3 different versions (Baseline, Staging, and Production) of the same sample web application into a provided Kubernetes cluster. 

 

Lab Objectives

Upon completion of this Lab, you will be able to:

  • Use Kustomize to deploy a basic web application which has been packaged already into a docker image (hosted on DockerHub). 
  • Understand how to use configure and work with Kustomize Bases and Overlays
  • Use Kustomize to generate 3 different enviroment specific deployments:
    • Baseline - the baseline deployment version of the webapp
    • Staging - uses a Kustomize overlay to change the baseline deployment settings
    • Production - uses a Kustomize overlay to change the baseline deployment settings
  • Test and validate the Base, Staging, and Production deployed cluster resources using the curl command and your workstations browser

You should:

  • Be comfortable with basic Linux command line administration
  • Be comfortable with basic Kubernetes and Container based concepts

Lab Environment

This Lab will start with the following AWS resources provisioned automatically for you:

  • 2 x EC2 instances - each assigned a public IP address:
    • ide.cloudacademy.platform.instance - provides a web-based IDE with integrated terminal
    • k8s.cloudacademy.platform.instance - provides a fully functional and running Kubernetes cluster

To achieve the Lab end state, you will be walked through the process of:

  • Using your local workstation browser to remotely connect to the ide.cloudacademy.platform.instance
  • Using the web-based IDE and integrated terminal, you'll complete the remainder of the stated Lab Objectives (above)

About the Author
Students38883
Labs34
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Jeremy is the DevOps Content Lead at Cloud Academy where he specializes in developing technical training documentation for DevOps.

He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 20+ years. In recent times, Jeremy has been focused on DevOps, Cloud, Security, and Machine Learning.

Jeremy holds professional certifications for both the AWS and GCP cloud platforms.