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Overview

DevOps Engineering on AWS demonstrates how to use the most common DevOps patterns to develop, deploy and maintain applications on AWS. The course covers the core principles of the DevOps methodology and examines a number of use cases applicable to startup, small-medium business, and enterprise development scenarios.

Target Audience

This course is intended for:

  • System Administrators
  • Software Developers

Prerequisites

We recommend that attendees of this course have the following prerequisites:

  • Attended System Operations on AWS course
  • Attended Developing on AWS course
  • Working knowledge of one or more high-level programming languages (C#, Java, PHP, Ruby, Python, etc.)
  • Intermediate knowledge of administering Linux or Windows systems at the command-line level
  • Working experience with AWS using both the AWS Management Console and the AWS Command Line Interface (AWS CLI)

Learning Outcomes

This course is designed to teach you how to:

  • Use the principal concepts and practices behind the DevOps methodology.
  • Design and implement an infrastructure on AWS that supports one or more DevOps development projects.
  • Use AWS CloudFormation and AWS OpsWorks to deploy the infrastructure necessary to create development, test, and production environments for a software development project.
  • Use AWS CodeCommit and AWS CodeBuild to understand the array of options for enabling a Continuous Integration environment on AWS.
  • Use AWS CodePipeline to design and implement a Continuous Integration and Delivery pipeline on AWS.
  • Use AWS CodeStar to manage all software development activities in one place.
  • Implement several common Continuous Deployment use cases using AWS technologies, including blue/green deployment and A/B testing.
  • Distinguish between the array of application deployment technologies available on AWS (including AWS CodeDeploy, AWS OpsWorks, AWS Elastic Beanstalk, Amazon EC2 Container Service, and Amazon EC2 Container Registry), and decide which technology best fits a given scenario.
  • Use Amazon EC2 Systems Manager for patch management.
  • Leverage Automated Testing in different stages of a CI/CD pipeline.
  • Fine-tune the applications you deliver on AWS for high performance, and use AWS tools and technologies to monitor your application and environment for potential issues.

Course Outline

Module 1: Introduction to DevOps
Module 2: Infrastructure Automation
Module 3: AWS Toolsets
Module 4: Continuous Integration and Continuous Delivery (CI/CD) with Development Tools
Module 5: Introduction to Microservices
Module 6: DevOps and Containers
Module 7: DevOps and Serverless Computing
Module 8: Deployment Strategies
Module 9: Automated Testing
Module 10: Security Automation
Module 11: Configuration Management
Module 12: Observability
Module 13: Reference Architecture

AWS Learning Paths

Want to boost your career in AWS? Click on the roles below to see QA‘s learning pathways, specially designed to give you the skills to succeed.

= Required
= Certification
Data Scientist
Data Engineer
Developer Software Development
Architect Enterprise Architecture Experience
Administrator DevOps
Administrator Security
Data Engineer Average salary: £70,000*

Total individual course price: £2,775 ex VAT

Bundle price: £2,220 ex VAT

Saving: £555

4 days

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Developer Average salary: £76,250*

Total individual course price: £4,995 ex VAT

Bundle price: £4,020 ex VAT

Saving: £975

7 days

Buy bundle View bundle
Architect Average salary: £90,000*

Total individual course price: £6,880 ex VAT

Bundle price: £5,535 ex VAT

Saving: £1,345

7 days

Buy bundle View bundle
Administrator DevOps Average salary: £45,000*

Total individual course price: £5,265 ex VAT

Bundle price: £4,235 ex VAT

Saving: £1,030

7 days

Buy bundle View bundle
Administrator Security Average salary: £45,000*

Total individual course price: £4,995 ex VAT

Bundle price: £4,020 ex VAT

Saving: £975

7 days

Buy bundle View bundle
Key for bundle contents
= Exam Preparation
= Exam
= Practice Exam
= Exam Voucher
= Tutor Support
= Pre Course Work
*This is based on QA research