Navigating a Large Scale Modernization With DDD

In this workshop, we discuss the merits of serverless architecture and how it can be applied to the AI space. We'll explore options around building serverless RAG applications for a more lambda-esque approach to AI. Next, we'll get hands on and build a sample CRUD app that allows you to store information and query it using an LLM with Workers AI, Vectorize, D1, and Cloudflare Workers.

Next.js is a compelling framework that makes many tasks effortless by providing many out-of-the-box solutions. But as soon as our app needs to scale, it is essential to maintain high performance without compromising maintenance and server costs. In this workshop, we will see how to analyze Next.js performances, resources usage, how to scale it, and how to make the right decisions while writing the application architecture.

With the rise of frameworks, such as React, Vue or Angular, the way websites are built changed over the years. Modern applications can be very dynamic and perform multiple API requests to populate a website with fresh content or submit new data to a server. However, this paradigm shift introduced new problems developers need to deal with. When an API request is pending, succeeds, or fails, a user should be presented with meaningful feedback. Other problems can comprise API data caching or syncing the client state with the server. All of these problems require solutions that need to be coded, but these can quickly get out of hand and result in a codebase that is hard to extend and maintain. In this workshop, we will cover how to handle API requests, API states and request cancellation by implementing an API Layer and combining it with React-Query.
Prerequisites: To make the most out of this workshop, you should be familiar with React and Hooks, such as useState, useEffect, etc. If you would like to code along, make sure you have Git, a code editor, Node, and npm installed on your machine.