This repository provides hands-on lab exercises for Amazon Web Services (AWS) designed to align with AWS Certification levels:
Each lab is designed to provide practical experience and knowledge on using different AWS services as per the related certification level.
This repository is organized into directories, each named after an AWS service, for example AmazonEC2/, AmazonS3/, etc. Each AWS service directory is then divided into four subdirectories based on certification level:
01-foundational/ - These labs focus on the foundational understanding and usage of the service, tailored to the AWS Certified Cloud Practitioner exam.02-associate/ - These labs align with the AWS Certified Solutions Architect Associate, AWS Certified Developer Associate, and AWS Certified SysOps Administrator Associate exams.03-professional/ - These labs deal with advanced use-cases as per AWS Certified Solutions Architect Professional and AWS Certified DevOps Engineer Professional exams.04-specialty/ - These labs cater to specialized technical roles with AWS services, matching with AWS Certified Advanced Networking, AWS Certified Security, AWS Certified Machine Learning, and other specialty exams.Each level directory contains multiple labs, each with its own dedicated directory containing all the necessary scripts, templates and a README.md file explaining the objective of the lab, instructions, and additional notes if any.
To start with these labs, clone this repository to your local system. Navigate to the AWS service and the level you're interested in, then follow the instructions provided in the README.md file of each lab.
git clone https://github.com/MinhHungPhan/aws-hands-on-labs.git
cd aws-hands-on-labs/ServiceName/Level/
Please ensure you have the necessary AWS permissions to perform the tasks in the lab.
We welcome contributions! Please see CONTRIBUTING.md for details on how to contribute.
This project is licensed under the MIT License. See LICENSE.md for details.
Please note that you will be responsible for any AWS costs incurred during the execution of these labs.
$ claude mcp add aws-hands-on-labs \
-- python -m otcore.mcp_server <graph>