Arthur Boghossian

We will use AWS CloudFormation, as it is ideal for deploying and replicating infrastructure as code. Amazon CloudWatch Events will be used to send info based on the trigger that initiated the event to developers using Amazon SNS. Amazon SNS will also be used in the AWS CodePipeline after the application has been tested and deployed successfully to the development environment, notifying users to approve the application before it can be deployed to a production environment. AWS CodeBuild will be used for running tests on the application and AWS CodeDeploy will be used to deploy the application to Lambda and Alexa Skills Kit. AWS CodePipeline is a service that will organize the steps taken (building/testing and deployment) when code is pushed to the master branch in our source repository in Github.

For our Compute services, we decided to use AWS Lambda as it is perfect for quick executions (perfect for a bot), is serverless, and is required by Amazon Lex, which we will use as the framework for our bot. We chose Amazon Lex as it integrates well with other #AWS services and uses the same technology as Alexa. This will give customers the ability to purchase licenses through their Alexa device. We chose Amazon DynamoDB to store customer information as it is a noSQL database, has high performance, and highly available. If we decide to train our own models for license recommendation we will either use Amazon SageMaker or Amazon EC2 with AWS Elastic Load Balancing (ELB) and AWS ASG as they are ideal for model training and inference.