Authors Noah Gift, founder of Pragmatic AI Labs, and James Charlesworth, engineering manager at Pendo, take you through the depth and breadth of .NET development on AWS.
This technical guide covers considerations for refactoring a monolithic ASP.NET application into a microservice-based architecture.
In this guide we cover the common approaches our customers use to modernize their Windows-based and .NET applications and tools, services, and the support AWS has to help you in your modernization journey.
Below you will find links to sample applications that utilize .NET and a variety of AWS services. Each link will take you to a GitHub repository containing everything you need such as important prerequisites, workflow diagrams, and how to instructions. Before using some of the sample applications you must log into your AWS account or create an AWS account. You can find more code examples on the AWS Developer Code Examples page.
Bob's Used Books is a sample application built on ASP.NET Core 6.0 that represents a real-world application. It is a monolithic n-tier application with an ASP.NET Core MVC front end and a Microsoft SQL Server database backend. The MVC application contains a customer portal and an administration portal. The customer portal enables customers to search for books, select and add them to a shopping cart, and work through a simulated check-out process. Customers can also offer their own books for resale through the website.
Amazon Web Services empower your applications with AI capabilities. These examples illustrate facial analysis from an image using Amazon Rekognition, automated document processing with Amazon Textract, batch and real-time document translation with Amazon Translate, and how to uncover insights from documents using Amazon Comprehend.
Using an AWS Text-to-Speech assistant you can upload a PDF file, have the text in that file read and then converted to an MP3 file. This process is completed using an Amazon Simple Storage Service (S3) to receive the upload, Amazon Textract to read the text and then Amazon Polly to convert the text to an MP3 file.
In this sample application you can use .NET on AWS to compare a photo against several other photo images. When the user uploads the image to an Amazon Simple Storage Service (S3) bucket, a notification is sent to Amazon EventBridge and EventBridge triggers an AWS Step Functions workflow. Amazon Rekognition then compares the photo against several other photos.
This sample app teaches you how to build an application which analyzes customer reviews. The analysis begins when a review is submitted to the Amazon API Gateway which passes the HTTP request to AWS Step Functions. After the request is made Amazon Comprehend is invoked using an Amazon EventBridge rule and determines if a review is positive or negative. A message is then sent to the reviewer using Amazon Simple Notification Service and if the review is negative a customer service representative is notified. The process ends when a complete audit trail is saved in Amazon DynamoDB.
Amazon Rekognition enables you to catalog and analyze an image to determine if it contains offensive material. The sample app uses Amazon Rekognition to detect the content of the image and build a cross reference between the items discovered and stored images.
This sample demonstrates two ways to solve the issue of AWS Lambda functions connecting to both a non-publicly accessible database on a virtual private cloud (VPC) and AWS Secrets Manager. The first approach uses an Amazon VPC NAT Gateway to give your VPC connected Lambda function access to the internet. The second uses an Amazon VPC Endpoint to give your VPC connected Lambda function access to the AWS Secrets Manager service only