During DevOps Engineering on AWS you will learn how to use the combination of cultural philosophies, practices and tools DevOps to increase the organization's ability to develop, deliver and maintain applications and services at high speed 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 templates CloudTraining and CI/CD pipelines that build and deploy applications on Amazon Elastic Compute Cloud (Amazon EC2), serverless applications, and container-based applications. Also included are labs for multi-pipeline workflows and pipelines that deploy to multiple environments.
Participants in this course DevOps Engineering on AWS will learn:
- To use best practices DevOps to develop, deliver and maintain applications and services at high speed on AWS
- List the advantages, roles and responsibilities of small teams DevOps autonomy.
- Design and implement an infrastructure on AWS that supports development projects DevOps
- To use AWS Cloud9 to write, run, and debug code
- To deploy various environments with AWS CloudTraining
- Host secure, highly scalable, and private Git repositories with AWS CodeCommit
- Integrate Git repositories into CI/CD pipelines
- Automate code creation, testing, and packaging with AWS CodeBuild
- Securely store and use Docker images and integrate them into CI/CD pipelines
- Build CI/CD pipelines to deploy applications to Amazon EC2, serverless applications, and container-based applications
- To implement common implementation strategies such as "all at once", "in full" and "blue/green"
- Integrate testing and security into CI/CD pipelines
- Monitor applications and environments using AWS tools and technologies
We recommend that participants in this course DevOps Engineering on AWS:
- Have previous attendance at Systems Operations on AWS or Developing on AWS courses
- Have working knowledge of one or more high-level programming languages such as C#, Java, PHP, Ruby, Python
- Have intermediate knowledge of Linux or Windows system administration at the command line level
- Have 2 or more years of experience provisioning, operating and managing AWS environments
Day 1
Module 0: Course overview
- Objective courses
- Suggested prerequisites
- Course overview breakdown
Module 1: Introduction to DevOps
- What is DevOps?
- The Amazon journey to DevOps
- Foundations for DevOps
Module 2: Infrastructure Automation
- Introduction to Infrastructure Automation
- Diving into the AWS CloudTemplate formation
- Modifying an AWS CloudTemplate formation
- Demo: AWS CloudFormation template structure, parameters, stacks, updates, importing resources, and drift detection
Module 3: AWS Toolkits
- Configuring the AWS CLI
- AWS Software Development Kits (AWS SDKs)
- AWS SAM CLI
- AWS Cloud Development Kit (AWS CDK)
- AWS Cloud9
- Demonstration: AWS CLI and AWS CDK
- Hands-on lab: Using AWS CloudTraining to provision and manage a basic infrastructure
Module 4: Continuous integration and continuous delivery (CI/CD) with development tools
- CI / CD Pipeline and Dev Tools
- 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
Day 2
Module 4: Continuous integration and continuous delivery (CI/CD) with development tools
- AWS CodePipeline
- Demonstration: AWS integration with Jenkins
- Hands-on lab: Automating code deployments using AWS CodePipeline
Module 5: Introduction to Microservices
- Introduction to Microservices
Module 6: DevOps and containers
- Deploying applications with Docker
- Amazon Elastic Container Service and AWS Fargate
- Amazon Elastic Container Registry and Amazon Elastic Kubernetes service
- Demonstration: CI/CD pipeline deployment in a containerized application
Module 7: DevOps and serverless computing
- AWS Lambda and AWS Fargate
- AWS Serverless Application Repository and AWS SAM
- AWS Step Functions
- 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
Module 8: Deployment strategies
- continuous deployment
- Deployments with AWS Services
Module 9: Automated testing
- Introduction to testing
- Tests: Unit, integration, fault tolerance, load, and synthetic
- Product and service integrations
Day 3
Modules 10: Security automation
- Introduction to DevSecOps
- Security of the Pipeline
- Security in the Pipeline
- Threat Detection Tools
- Demonstration: AWS Security Hub, Amazon GuardDuty, AWS Config, and Amazon Inspector
Module 11: Configuration management
- Introduction to the configuration management process
- AWS services and tooling for configuration management
- Hands-on lab: Performing blue/green deployments with CI/CD pipelines and Amazon Elastic Container Service (Amazon ECS)
Module 12: Observability
- Introduction to observability
- AWS tools to assist with observability
- Hands-on lab: Using AWS DevOps tools for CI/CD pipeline automations
Module 13: Reference architecture (Optional module)
- Reference architectures
Module 14: Course summary
- components or DevOps practice
- CI/CD pipeline review
- AWS Certification
AWS Certified DevOps Engineer – Professional (DOP-C01)
AWS Certified Exam DevOps Engineer – Professional is intended for people who fulfill a role of DevOps Engineer with two or more years of experience provisioning, operating and managing AWS environments.
The exam can be taken at a testing center, from home or from the office, through the online proctoring service.
DevOps Engineering on AWS
Course details
FAQ Course DevOps Engineering on AWS
What are the main topics covered in the course DevOps Engineering on AWS?
The course covers essential topics such as implementing CI/CD pipelines using AWS CodePipeline and CodeBuild, infrastructure automation with AWS CloudTraining, monitoring and logging applications with Amazon CloudWatch and AWS X-Ray, as well as security and permission management in AWS. Scalability and resilience of applications across environments is also discussed DevOps.
What skills will I gain from attending the course? DevOps Engineering on AWS?
After the course, you will acquire advanced skills in the implementation and management of processes DevOps on AWS. You'll learn how to automate continuous delivery pipelines, deploy infrastructure as code, monitor and optimize applications, and manage security and compliance across environments DevOps. You will also learn to manage operations in environments cloud scalable and resilient.
How will this course help me optimize the monitoring and logging of my applications on AWS?
The course will teach you how to use AWS CloudWatch, AWS X-Ray and other services to monitor the performance of your applications in real time, collect and analyze logs, and quickly identify problems. You'll learn how to implement automated alerts, visualize data, and optimize application performance and stability through proactive monitoring and intervention.
What career opportunities may arise after completing the course DevOps Engineering on AWS?
After completing this course and becoming AWS Certified DevOps Engineer – Professional, you will be well prepared for roles such as DevOps Engineer, Cloud Engineer, Automation Engineer or Site Reliability Engineer (SRE). These roles are critical for companies looking to optimize software delivery processes and maintain infrastructure cloud efficient and resilient.
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