DevOps Engineering on AWS
DevOps Engineering on AWS teaches you how to use the combination of DevOps cultural philosophies, practices, and tools to increase your organization's ability to develop, deliver, and maintain applications and services at high velocity on AWS. This course covers Continuous Integration (CI), Continuous Delivery (CD), infrastructure as code, microservices, monitoring and logging, and communication and collaboration. Hands-on labs give you experience building and deploying AWS CloudFormation templates and CI/CD pipelines that build and deploy applications on Amazon Elastic Compute Cloud (Amazon EC2), serverless applications, and container-based applications. Labs for multi-pipeline workflows and pipelines that deploy to multiple environments are also included.
What you will learn
- Use DevOps best practices to develop, deliver, and maintain applications and services at high velocity on AWS
- List the advantages, roles and responsibilities of small autonomous DevOps teams
- Design and implement an infrastructure on AWS that supports DevOps development projects
- Leverage AWS Cloud9 to write, run and debug your code
- Deploy various environments with AWS CloudFormation
- Host secure, highly scalable, and private Git repositories with AWS CodeCommit
- Integrate Git repositories into CI/CD pipelines
- Automate build, test, and packaging code with AWS CodeBuild
- Securely store and leverage Docker images and integrate them into your CI/CD pipelines
- Build CI/CD pipelines to deploy applications on Amazon EC2, serverless applications, and container-based applications
- Implement common deployment strategies such as "all at once,” “rolling,” and “blue/green"
- Integrate testing and security into CI/CD pipelines
- Monitor applications and environments using AWS tools and technologies
Prerequisites
- Previous attendance at the Systems Operations on AWS or Developing on AWS courses
- Working knowledge of one or more high-level programming languages, such as C#, Java, PHP, Ruby, Python
- Intermediate knowledge of administering Linux or Windows systems at the command-line level
- Two or more years of experience provisioning, operating, and managing AWS environments
Target audience
- DevOps engineers, DevOps architects, Operations engineers, System administrators, Developers
Training Program
15 modules to master the fundamentals
Topics covered
- →Course objective
- →Suggested prerequisites
- →Course overview breakdown
Topics covered
- →What is DevOps?
- →The Amazon journey to DevOps
- →Foundations for DevOps
Topics covered
- →Introduction to Infrastructure Automation
- →Diving into the AWS CloudFormation template
- →Modifying an AWS CloudFormation template
Activities
Demonstration: AWS CloudFormation template structure, parameters, stacks, updates, importing resources, and drift detection
Topics covered
- →Configuring the AWS CLI
- →AWS Software Development Kits (AWS SDKs)
- →AWS SAM CLI
- →AWS Cloud Development Kit (AWS CDK)
- →AWS Cloud9
Activities
Demonstration: AWS CLI and AWS CDK
Hands-on lab: Using AWS CloudFormation to provision and manage a basic infrastructure
Topics covered
- →CI/CD Pipeline and Dev Tools
- →AWS CodePipeline
Activities
Demonstration: CI/CD pipeline displaying some actions from AWS CodeCommit, AWS CodeBuild, AWS CodeDeploy and AWS CodePipeline
Hands-on lab: Deploying an application to an EC2 fleet using AWS CodeDeploy
Demonstration: AWS integration with Jenkins
Hands-on lab: Automating code deployments using AWS CodePipeline
Topics covered
- →Introduction to Microservices
Topics covered
- →Deploying applications with Docker
- →Amazon Elastic Container Service and AWS Fargate
- →Amazon Elastic Container Registry and Amazon Elastic Kubernetes service
Activities
Demonstration: CI/CD pipeline deployment in a containerized application
Topics covered
- →AWS Lambda and AWS Fargate
- →AWS Serverless Application Repository and AWS SAM
- →AWS Step Functions
Activities
Demonstration: AWS Lambda and characteristics
Demonstration: AWS SAM quick start in AWS Cloud9
Hands-on lab: Deploying a serverless application using AWS Serverless Application Model (AWS SAM) and a CI/CD Pipeline
Topics covered
- →Continuous Deployment
- →Deployments with AWS Services
Topics covered
- →Introduction to testing
- →Tests: Unit, integration, fault tolerance, load, and synthetic
- →Product and service integrations
Topics covered
- →Introduction to DevSecOps
- →Security of the Pipeline
- →Security in the Pipeline
- →Threat Detection Tools
Activities
Demonstration: AWS Security Hub, Amazon GuardDuty, AWS Config, and Amazon Inspector
Topics covered
- →Introduction to the configuration management process
- →AWS services and tooling for configuration management
Activities
Hands-on lab: Performing blue/green deployments with CI/CD pipelines and Amazon Elastic Container Service (Amazon ECS)
Topics covered
- →Introduction to observability
- →AWS tools to assist with observability
Activities
Hands-on lab: Using AWS DevOps tools for CI/CD pipeline automations
Topics covered
- →Reference architectures
Topics covered
- →Components of DevOps practice
- →CI/CD pipeline review
- →AWS Certification
Quality Process
SFEIR Institute's commitment: an excellence approach to ensure the quality and success of all our training programs. Learn more about our quality approach
- Lectures / Theoretical Slides — Presentation of concepts using visual aids (PowerPoint, PDF).
- Technical Demonstration (Demos) — The instructor performs a task or procedure while students observe.
- Guided Labs — Guided practical exercises on software, hardware, or technical environments.
The achievement of training objectives is evaluated at multiple levels to ensure quality:
- Continuous Knowledge Assessment : Verification of knowledge throughout the training via participatory methods (quizzes, practical exercises, case studies) under instructor supervision.
- Progress Measurement : Comparative self-assessment system including an initial diagnostic to determine the starting level, followed by a final evaluation to validate skills development.
- Quality Evaluation : End-of-session satisfaction questionnaire to measure the relevance and effectiveness of the training as perceived by participants.
Train multiple employees
- Volume discounts (multiple seats)
- Private or custom session
- On-site or remote