Amazon EKS - Building a Cloud Native Application

Lab Steps

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Logging in to the Amazon Web Services Console
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Connecting to the Virtual Machine using EC2 Instance Connect
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Reviewing Amazon EKS Resources Automatically Created
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Installing Kubernetes Management Tools and Utilities
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Cloud Native App Architecture Review
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Deploying a Cloud Native Application

The hands-on lab is part of this learning path

Ready for the real environment experience?

DifficultyIntermediate
Time Limit2h
Students54
Ratings
5/5
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Description

Building and deploying Cloud Native Applications in EKS has never been easier. 

In this hands-on lab, you'll learn how to create and deploy a cloud native application into a EKS cluster. Along the way you'll learn how to work with Kubernetes resources such as Deployments, Services, StatefulSets, PVs, PVCs, and Secrets. You'll learn how to use kubectl to configure and integrate all of these resources together to implement a stateful web based voting application.

Learning Objectives

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

  • Use kubectl to deploy resources into an EKS cluster
  • Work with and configure commonly used Kuberenetes resources
  • Expose EKS hosted applications to the Internet

Intended Audience

This lab is intended for:

  • Kubernetes practitioners
  • DevOps Engineers
  • SREs

Lab Prerequisites

You should be familiar with:

  • Basic Linux command line administration
  • Basic Kubernetes and Container-based concepts

Lab Environment

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

  • 1 x EKS cluster - Cluster-1 - provides a fully functional Kubernetes cluster 
    • 1 x NodeGroup
      • 2 x EC2 Worker Nodes
  • 2 x EC2 instances
    • eks.launch.instance - used to launch the EKS cluster
    • cloudacademylabs - used to provide an SSH based terminal

 

About the Author
Students75228
Labs49
Courses110
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Jeremy is a Content Lead Architect and DevOps SME here at Cloud Academy where he specializes in developing DevOps technical training documentation.

He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 25+ years. In recent times, Jeremy has been focused on DevOps, Cloud (AWS, GCP, Azure), Security, Kubernetes, and Machine Learning.

Jeremy holds professional certifications for AWS, GCP, and Kubernetes.