AWS DevOps Professional 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 and medium-sized business, and enterprise development scenarios.

Course Objectives

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 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
  • 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
  • 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

Intended Audience

This course is intended for:

  • System Administrators
  • Software Developers


We recommend that attendees of this course have the following prerequisites

  • Attended AWS Developer Associate  or AWS SysOps Associate
  • 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)

Delivery Method

  • Instructor-Led Training (ILT)
  • Hands-on Labs

Course Outline

Day 1

Domain 1: Continuous Delivery and Process Automation

1.1  Demonstrate an understanding of application lifecycle management:

  • Application deployment management strategies such as rolling deployments and A/B
  • Version control, testing, build tools and bootstrapping.

1.2 Demonstrate an understanding of infrastructure configuration and automation.

1.3 Implement and manage continuous delivery processes using AWS services.

1.4 Develop and manage scripts and tools to automate operational tasks using the AWS SDKs, CLI, and APIs.

Domain 2: Monitoring, Metrics, and Logging

2.1  Monitor availability and performance.

2.2  Monitor and manage billing and cost optimization processes.

2.3  Aggregate and analyze infrastructure, OS and application log files.

2.4  Use metrics to drive the scalability and health of infrastructure and applications.

2.5  Analyze data collected from monitoring systems to discern utilization patterns.

2.6  Manage the lifecycle of application and infrastructure logs

2.7  Leverage the AWS SDKs, CLIs and APIs for metrics and logging.

Day 2

Domain 3: Security, Governance, and Validation

3.1  Implement and manage Identity and Access Management and security controls.

3.2  Implement and manage protection for data in-flight and at rest.

3.3  Implement, automate and validate cost controls for AWS resources.

3.4  Implement and manage automated network security and auditing.

3.5  Apply the appropriate AWS account and billing set-up options based on business requirements.

3.6  Implement and manage AWS resource auditing and validation.

3.7  Use AWS services to implement IT governance policies.


Day 3

Domain 4: High Availability and Elasticity

4.1  Determine appropriate use of multi- Availability Zone versus multi-region architectures.

4.2  Implement self-healing application architectures.

4.3  Implement the most appropriate front-end scaling architecture.

4.4  Implement the most appropriate middle-tier scaling architecture.

4.5  Implement the most appropriate data storage scaling architecture.

4.6  Demonstrate an understanding of when to appropriately apply vertical and horizontal scaling concepts.