Reimagine Frontend in the Serverless Era

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.

This workshop teaches you the basics of serverless application development with TypeScript. We'll start with a simple Lambda function, set up the project and the infrastructure-as-a-code (AWS CDK), and learn how to organize, test, and debug a more complex serverless application.
Table of contents:        - How to set up a serverless project with TypeScript and CDK        - How to write a testable Lambda function with hexagonal architecture        - How to connect a function to a DynamoDB table        - How to create a serverless API        - How to debug and test a serverless function        - How to organize and grow a serverless application


Materials referred to in the workshop:
https://excalidraw.com/#room=57b84e0df9bdb7ea5675,HYgVepLIpfxrK4EQNclQ9w
DynamoDB blog Alex DeBrie: https://www.dynamodbguide.com/
Excellent book for the DynamoDB: https://www.dynamodbbook.com/
https://slobodan.me/workshops/nodecongress/prerequisites.html

Intro to serverlessPrior Art: Docker, Containers, and KubernetesActivity: Build a Dockerized application and deploy it to a cloud providerAnalysis: What is good/bad about this approach?Why Serverless is Needed/BetterActivity: Build the same application with serverlessAnalysis: What is good/bad about this approach?

Welcome to Fauna! This workshop helps GraphQL developers build performant applications with Fauna that scale to any size userbase. You start with the basics, using only the GraphQL playground in the Fauna dashboard, then build a complete full-stack application with Next.js, adding functionality as you go along.

In the first section, Getting started with Fauna, you learn how Fauna automatically creates queries, mutations, and other resources based on your GraphQL schema. You learn how to accomplish common tasks with GraphQL, how to use the Fauna Query Language (FQL) to perform more advanced tasks.

In the second section, Building with Fauna, you learn how Fauna automatically creates queries, mutations, and other resources based on your GraphQL schema. You learn how to accomplish common tasks with GraphQL, how to use the Fauna Query Language (FQL) to perform more advanced tasks.

This workshop discusses the challenges Enterprises are facing when scaling the data tier to support multi-region deployments and serverless environments. Serverless edge functions and lightweight container orchestration enables applications and business logic to be easily deployed globally, often leaving the database as the latency and scaling bottleneck.
Join us to understand how PolyScale.ai solves these scaling challenges intelligently caching database data at the edge, without sacrificing transactionality or consistency. Get hands on with PolyScale for implementation, query observability and global latency testing with edge functions.
Table of contents- Introduction to PolyScale.ai- Enterprise Data Gravity- Why data scaling is hard- Options for Scaling the data tier- Database Observability- Cache Management AI- Hands on with PolyScale.ai

In this workshop, we will be building a testing environment for a pre-built application, then we will write and automate end-to-end tests for our serverless application. And in the final step, we will demonstrate how easy it is to understand the root cause of an erroneous test using distributed testing and how to debug it in our CI/CD pipeline with Thundra Foresight.

Table of contents:
- How to set up and test your cloud infrastructure
- How to write and automate end-to-end tests for your serverless workloads
- How to debug, trace, and troubleshot test failures with Thundra Foresight in your CI/CD pipelines