The QA "Developing on AWS" course it's a mix of instructor-led training and hands-on labs to understand how to use the AWS SDK to develop secure and scalable cloud applications. It provides in-depth knowledge about how to interact with AWS using code, and covers key concepts, best practices, and troubleshooting tips.
Links:
- https://www.qa.com/course-catalogue/courses/developing-on-aws-amwsd/ (Course details)
- https://online.vitalsource.com/reader/books/200-DODEVA-45-EN-SG-E (Student Guide)
- https://us-east-1.student.classrooms.aws.training/class/7RyCHRkpqnfX7wZdhcG7V7 (AWS Labs)
- https://aws.amazon.com/podcasts/357-deep-dive-into-observability/
Main Objectives:
- Configure IAM permissions to support your development environment.
- Design, diagram, build, and deploy a cloud-native application using AWS SDKs.
- Monitor and maintain an application by using AWS resources.
Learning Outcomes:
- Set up the AWS SDK and developer credentials for Java, C#/.NET, Python, and JavaScript
- Interact with AWS services and develop solutions by using the AWS SDK
- Use AWS Identity and Access Management (IAM) for service authentication
- Use Amazon Simple Storage Service (Amazon S3) and Amazon DynamoDB as data stores
- Integrate applications and data by using AWS Lambda, Amazon API Gateway, Amazon Simple Queue Service (Amazon SQS), Amazon Simple Notification Service (Amazon SNS), and AWS Step Functions
- Use Web Identity Framework and Amazon Cognito for user authentication
- Use Amazon ElastiCache to improve application scalability
- Use containers in the development process
- Leverage the CI/CD pipeline to deploy applications on AWS
Course Overview:
- Module 1 – Introduction to the course.
- Module 2 – Review the details the AWS architecture used to create a complete cloud-native application.
- Module 3 – Explore the benefits of AWS software development kits (AWS SDKs) when building an application.
- Module 4 – Configure a development environment that supports AWS Identity and Access Management (IAM) permissions.
- Lab 1 – Configure and test IAM permissions in a development environment.
- Module 5 – Compare feature sets and use cases for available AWS storage solutions.
- Module 6 – Deploy a static website to Amazon Simple Storage Service (Amazon S3).
- Lab 2 – Identify the appropriate AWS solutions for application workloads for big data.
- Module 7 – Compare feature sets and use cases for available AWS database options. Configure an Amazon DynamoDB database to store data from a web application.
- Module 8 – Use the DynamoDB SDK to perform the create, read, update, delete (CRUD) operations, and explore database caching options.
- Lab 3 – Configure a DynamoDB database to store data from a web application.
- Module 9 – Compare the feature sets and use cases for available AWS compute solutions. Build an AWS Lambda function to store data from a web application in DynamoDB.
- Lab 4 – Build an AWS Lambda function to store data from a web application in DynamoDB.
- Module 10 – Explore the methods available for Amazon API Gateway to connect AWS resources.
- Lab 5 – Use Amazon API Gateway to connect Lambda and DynamoDB.
- Module 11 – Evaluate the benefits of building a web application using a serverless approach.
- Module 12 – Review how Amazon Cognito controls user access to AWS resources.
- Lab 6 – Create an Amazon Cognito solution that provides users access to a web application.
- Module 13 – Deploy your application.
- Module 14 – Identify the AWS services that support the monitoring of a web application.
- Lab 7 – Deploy, monitor, and maintain a web application using AWS resources.
- Module 15 – Course summary
All the labs use Python. Install python 3: https://www.python.org/downloads/.
This project is licensed under the terms of the MIT License. Please see LICENSE for details.