About This Course

Get an overview of the content of this course and learn about its target audience.

In this course, we'll explore the drawbacks of waterfall methodology and learn how DevOps helps address those issues. We'll explore the different phases that make up a DevOps delivery pipeline and the services provided by AWS for each phase. Moreover, we'll also learn how to make our delivery pipeline more agile and resilient using other supporting services provided by AWS. As a bonus toward the end, this course will cover the various deployment strategies that a project team can use in a DevOps pipeline to maintain high availability.


The first chapter of this course will give an overview of DevOps, its importance, and the benefits of implementing DevOps in a production project. In the subsequent chapters, we'll zoom into each DevOps phase and examine the AWS service used. Each chapter will have many lessons with an interactive terminal where we can apply what we learn and see it in action.

Intended audience

This course is designed for the following professionals:

  • Developers who currently run their projects in AWS.

  • DevOps engineers who need to enhance their software delivery pipeline.

  • An architect looking to improve the quality of deliverables.

  • A software development manager who wants to increase the delivery frequency and gain customer trust and loyalty.


To gain maximum benefit from this course, you should be familiar with the following:

  • Git basics

  • Linux basics

  • YAML basics

  • Exposure to any software delivery methodology

Learning outcomes

By the end of this course, the learner will be able to understand the following:

  • Choosing the right AWS service to use at each phase of software delivery.

  • Configuring them using AWS CLI.

  • Validating the outputs from the AWS Console.

  • Implementing a project from the coding to the deployment phase by leveraging the Developer tools AWS services.

We'll also learn how to automate the deployment process using the popular infrastructure as code model and maintain high availability using popular deployment strategies.