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DevOps Engineering on AWS teaches you to streamline the design, development, deployment, and maintenance of applications on AWS using a DevOps methodology. DevOps is a combination of cultural philosophies, practices, and tools that enables your company to deliver new application features and improved services to customers at a higher velocity. In this course, you will build a Continuous Integration and Continuous Delivery (CI/CD) pipeline to deploy applications to various AWS compute environments. You will identify AWS services that allow you to establish DevOps practices, determine deployment strategies to use, and provide opportunities to automate or simplify manual processes. Using hands-on labs, you will build infrastructure on AWS and deploy sample web, serverless, and containerized applications to the AWS cloud using CI/CD pipelines, with the opportunity to enhance the security and observability features

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What You'll Learn

  • Apply concepts and practices behind DevOps methodology: Continuous Integration (CI), Continuous Delivery (CD), Infrastructure as Code (IaC), Monitoring and Logging
  • Leverage AWS Cloud9 to write, run, debug your code, and share your cloud-based IDE with your development teams
  • Design and provision infrastructure on AWS using AWS CloudFormation to support DevOps development projects
  • Host secure, highly scalable private Git repositories using AWS CodeCommit
  • Develop Git branching strategies and integrate with CI/CD pipeline for various environments
  • Automate building, testing, and packaging code using AWS CodeBuild
  • Store Docker images securely to Amazon Elastic Container Registry (Amazon ECR) and integrate with AWS CodeBuild and Amazon Elastic Container Service (Amazon ECS)
  • Automate software deployments to Amazon Elastic Compute Cloud (Amazon EC2), AWS ECS, and AWS Lambda with AWS CodeDeploy
  • Implement common deployment strategies and configurations such as "in place", "blue/green, "all at once," "rolling," and "canary"
  • Configure AWS CodePipeline with multiple stages (source, build, deploy) to automate your release workflow
  • Simplify building and deploying serverless applications using AWS Serverless Application Model
  • Integrate security into the CI/CD pipelines
  • Use AWS Lambda to automate deployment and security testing
  • Explain how AWS Systems Manager and AWS Config manage application and infrastructure configuration
  • Monitor, observe, and troubleshoot your application and environment using AWS tools such as AWS X-Ray, AWS DevOps Guru

 

Who Should Attend

This course is intended for:

  • DevOps engineers
  • DevOps architects
  • Operations engineers
  • System administrators
  • Developers
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Prerequisites

We recommend that attendees of this course have:

  • Attended  Cloud Operations on AWS or
  • Attended  Developing on AWS
  • Working knowledge of one or more high-level programing 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

Learning Journey

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

  • Cloud Administrator
  • Cloud DevOps Architect
  • Cloud DevOps Engineer
  • Cloud Operations Manager
  • DevSecOps Engineer
  • Machine Learning Operations Engineer

Machine Learning Operations Engineer

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Module 00: Course Overview

  • Welcome and logistics
  • Student resources - books and lab access
  • Course agenda

Module 01: Introduction to DevOps

  • List the benefits of implementing DevOps
  • Describe Amazon's own transformation to DevOps
  • Describe how AWS supports teams with DevOps Knowledge Check

Module 02: Infrastructure Automation

  • Explain the benefits of Infrastructure as Code
  • Define key components of a CloudFormation template
  • Use AWS CloudFormation to model, provision, and manage AWS and third-party resources
  • Explain how to manage and control changes to infrastructure Knowledge Check

Module 03: AWS Toolsets

  • List and describe some AWS tools that support automation
  • Describe how Amazon Q accelerates your software development lifecycle
  • Configure and use AWS CLI to manage AWS services
  • Explain the benefits of AWS CDK in defining infrastructure Knowledge Check
  • Lab 1: Use AWS CloudFormation to provision and manage a basic infrastructure
  • Build AWS CloudFormation templates in YAML to define infrastructure resources
  • Create a CloudFormation stack to provision infrastructure and review the outputs
  • Detect changes made to your resources and generate drift reports
  • Update your infrastructure using CloudFormation change sets

Module 04-Part 1: CI/CD with Development Tools

  • Describe Continuous Integration, Continuous Deployment and Delivery in the release workflow.
  • Describe source code controls best practices
  • Configure AWS CodeBuild to implement continuous integration tasks
  • Configure AWS CodeDeploy to perform application deployments for various
  • compute environments Knowledge Check
  • Lab 2: Deploy an application to an EC2 fleet using AWS CodeDeploy
  • Make systematic deployments to a fleet of EC2 servers using CodeDeploy
  • Verify CodeDeploy agent is installed and running on a Windows server
  • Create a deployment application and group in CodeDeploy
  • Review and prepare deployment package to be installed by CodeDeploy
  • Monitor deployment status in CodeDeploy and deployment targets

Day 2

Module 04- Part 2: CI/CD with Development Tools

  • Day 1 Recap
  • Implement Continuous Integration and Continuous Deployment for your applications using AWS DevOps tools.
  • Build and configure AWS CodePipeline to orchestrate CI/CD workflow of application deployments
  • Describe best practices involved in application delivery and deployments Knowledge Check
  • Lab 3: Automating code deployments using AWS CodePipeline
  • Package application code and upload the revision to an Amazon S3 bucket.
  • Build a multi-stage AWS CodePipeline with Amazon S3 as the source stage and AWS CodeDeploy as the deployment stage.
  • Review the deployment configurations and perform an automatic code deployment using AWS CodeDeploy.
  • Verify automatic deployment was successful using AWS Systems Manager Session Manager.

Module 05: Microservices

  • Describe the benefits of microservices in the software lifecycle
  • Explain the architectural requirements of microservices
  • Explore AWS services that help building microservices Knowledge Check

Module 06: DevOps and Containers

  • Describe the basics of Docker and containerization
  • Describe how to use Amazon Elastic Container Service (ECS) service to manage containerized applications
  • Differentiate between AWS container services: Amazon ECS, AWS Fargate,
  • Amazon Elastic Container Registry, Amazon Elastic Kubernetes Service.
  • Describe how AWS container services support DevOps efforts and improving
  • performance, scaling, and efficiency. Knowledge Check

Module 07: DevOps and Serverless Computing

  • Describe how AWS serverless computing simplifies development and deployment
  • List key AWS services that support serverless computing
  • Use Lambda functions to develop quick automation solutions
  • Configure Serverless Application Model (SAM) to deploy serverless solutions Knowledge Check
  • Lab 4: Deploying a serverless application using AWS SAM and a CI/CD pipeline
  • Build and locally test a serverless application using AWS SAM
  • Package and deploy a serverless application using AWS SAM CLI
  • Set up a CI/CD pipeline to automate the deployment of a sample serverless
  • application using AWS CodePipeline and AWS CodeDeploy Verify the deployment results

Module 08: Deployment Strategies

  • Differentiate between deployment configurations available for each compute platform with CodeDeploy
  • Define different strategies to implement in continuous deployment
  • Configure Blue/Green deployments with CodeDeploy
  • Identify AWS services that support various deployment configurations and explain how they are used in deployment Knowledge Check

Module 09: Automated Testing

  • Describe testing and automation options in a CI/CD pipeline
  • Describe various testing scenarios and best practices
  • Use the pipeline for continuous testing Knowledge Check

Day 3

Module 10: Security Automation

  • Day 1 & 2 Recap
  • Describe DevSecOps principles
  • Outline how to integrate security into the pipeline workflow
  • Explain steps and tools for ensuring security of and in CI/CD pipeline
  • Describe and configure AWS security services to build secure applications and solutions
  • Knowledge Check

Module 11: Configuration Management

  • Describe need for configuration management
  • Explain use of AWS Config and AWS Config Rules
  • Describe AWS Systems Manager and AWS Systems Manager Automation
  • Explain Amazon Machine Image Management (AMI)Knowledge Check
  • Lab 5: Performing blue/green deployments with CI/CD pipelines and Amazon ECS
  • Build custom container images using AWS CodeBuild and store them in Amazon ECR
  • Set up a CI/CD to build and automate application container image creation using AWS CodePipeline
  • Host and run a containerized web application using Amazon ECS and AWS Fargate
  • Configure AWS CodeDeploy to perform a blue/green deployment
  • Set up a CI/CD to automate the build and deployment of a containerized web application

Module 12: Observability

  • Differentiate between observability and monitoring
  • Describe AWS Services for observability
  • Describe Amazon DevOps Guru service for automated monitoring of AWS resources
  • Explain Amazon DevOps Guru workflow Knowledge Check
  • Lab 6: Using AWS DevOps tools for CI/CD pipeline automations
  • Build a CI/CD release pipeline using AWS CloudFormation to orchestrate deployment of a sample web application
  • Perform basic troubleshooting and fix AWS CodePipeline as needed
  • Automate static checks and verifications using AWS Lambda functions
  • Integrate various AWS DevOps tools into an automated workflow
  • Review service map and trace events from an AWS Lambda function using AWS XRay

Module 13: Course Summary

  • Course recap
  • Options for continuing your learning
  • Course feedback

AWS Certified DevOps Engineer – Professional (DOP-C02).

This credential showcases advanced technical expertise in provisioning, operating, and managing distributed application systems on AWS, giving you increased confidence and credibility with peers, colleagues, and customers.
The exam has the following content domains and weightings:
  • Content Domain 1: SDLC Automation (22% of scored content)
  • Content Domain 2: Configuration Management and IaC (17% of scored content)
  • Content Domain 3: Resilient Cloud Solutions (15% of scored content)
  • Content Domain 4: Monitoring and Logging (15% of scored content)
  • Content Domain 5: Incident and Event Response (14% of scored content)
  • Content Domain 6: Security and Compliance (17% of scored content)
Organizations with these qualified professionals can ensure speedy delivery of secure and compliant systems that are highly available and scalable.
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Frequently Asked Questions (FAQs)

  • Why get AWS certified?

    AWS certifications validate your expertise in cloud computing and your proficiency in using AWS services.

    These certifications are globally recognized and highly sought after by employers, as they demonstrate your ability to design, deploy, and manage scalable and secure cloud solutions on the AWS platform.

    AWS-certified professionals are in high demand, opening doors to new career opportunities and higher earning potential.

  • What to expect for the examination?

    AWS offers a variety of certification exams at different levels (Foundational, Associate, Professional, and Specialty) covering various domains and services.

    The exams typically consist of multiple-choice and multiple-response questions, and some may include scenario-based questions that assess your ability to apply your knowledge in real-world situations.

    Note: Certification requirements and policies may be updated by AWS from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • How long is AWS certification valid for?

    AWS certifications are valid for three years from the date of passing the exam.

    To maintain your certification, you will need to recertify by passing the latest version of the exam or completing the AWS Cloud Quest game-based training (if option is applicable).

    Note: Certification requirements and policies may be updated by AWS from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • Why take this course with Trainocate?

    Here’s what sets us apart:

    - Global Reach, Localized Accessibility: Benefit from our geographically diverse training hubs in 24 countries (and counting!).

    - Top-Rated Instructors: Our team of subject matter experts (with high average CSAT and MTM scores) are passionate to help you accelerate your digital transformation.

    - Customized Training Solutions: Choose from on-site, virtual classrooms, or self-paced learning to fit your organization and individual needs.

    - Experiential Learning: Dive into interactive training with our curated lesson plans. Participate in hands-on labs, solve real-world challenges, and take on comprehensive assessments.

    - Learn From The Best: With 30+ authorized training partnerships and countless awards from Microsoft, AWS, Google – you're guaranteed learning from the industry's elite.

    - Your Bridge To Success: We provide up-to-date course materials, helpful exam guides, and dedicated support to validate your expertise and elevate your career.

Keep Exploring

Course Curriculum

Course Curriculum

Training Schedule

Training Schedule

Exam & Certification

Exam & Certification

FAQs

Frequently Asked Questions

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