amplify-hosting VS aws-lambda-java-libs

So far our high level architecture diagram wasn't very impressive - we only used AWS Amplify service to host our web application. Of course there are many services under the hood like Route 53, CloudFront, Certificate Manager, Lambda and S3, but Amplify provides level of abstraction, so that we don't have to think about it.

Amplify Web Hosting

AWS Amplify Hosting - the ultimate solution for fast, secure, and scalable web app deployment. Whether you're building a static or server-side rendered app, a mobile app landing page, or a web app, Amplify Hosting's fully managed Continuous Integration and Continuous Deployment (CI/CD) service has everything you need. You can quickly deploy web content with support for modern web frameworks like React, Angular, Vue, Next.js, Gatsby, Hugo, Jekyll, and more.

Details for anyone stumbling upon this : https://github.com/aws-amplify/amplify-hosting/issues/3398

After some diging found someone saying that i should edit `Rewrites and redirects` ( https://github.com/aws-amplify/amplify-hosting/issues/1416 )

Head to AWS Amplify Hosting and click on the Host your web app button. You’ll be redirected to this page.

Just looked up the feature request and looks like they still don’t support it https://github.com/aws-amplify/amplify-hosting/issues/56

As of today, Amplify doesn't support Next.JS@12 fully and because of that, it'd be better and safer to downgrade to version 11 (of course we'd miss some of the awesome features from v12 but that's fine). So I'm making it "next": "11.1.4" in the package.json. Since we're downgrading it to v11, we need to downgrade usage of webpack from 5 to 4 and for doing that we need to add webpack5: false to our next.config.js file. I also add SVG support to that file for the future and it looks like this:

After trying to deploy my company website on it, however, I'd recommend against using Amplify. It has issues with deploying & building as well as with server response times.

The Bearcam Companion application was pretty much ready to go after my last post on Lambdas. The final step (at least for a minimum viable product) was to publish the site. Not surprisingly, I chose to use AWS Amplify Hosting.

So far our high level architecture diagram wasn't very impressive - we only used AWS Amplify service to host our web application. Of course there are many services under the hood like Route 53, CloudFront, Certificate Manager, Lambda and S3, but Amplify provides level of abstraction, so that we don't have to think about it.

Rajesh Pandey outlines key components: "For serverless, AWS Lambda and API Gateway allow you to build low-latency AI APIs without managing servers." Tools like Modal handle GPU deployments.

"Scale to zero" for intermittent workloads: For non-critical internal tools or low-traffic services, consider a serverless approach with AWS Lambda and SageMaker Serverless Inference. While the latency might be slightly higher due to cold starts, you pay absolutely nothing when the service isn't being used. This can result in massive savings over time.

While many cloud providers offer serverless options, my go-to, especially when working with Next.js, is Vercel. Their integration with Next.js API Routes makes developing and deploying serverless functions incredibly intuitive and fast. For more complex, enterprise-level solutions, AWS Lambda is the industry leader, offering immense flexibility and a vast ecosystem of services.

Building an AWS Lambda function to process and update embeddings

In this application, we will create products and retrieve them by their ID and use Amazon DynamoDB as a NoSQL database for the persistence layer. We use Amazon API Gateway which makes it easy for developers to create, publish, maintain, monitor and secure APIs and AWS Lambda to execute code without the need to provision or manage servers. We also use AWS SAM, which provides a short syntax optimised for defining infrastructure as code (hereafter IaC) for serverless applications.

Lambda supports various programming languages, including Node.js, Python, Java, Go, Ruby, .NET, and even custom runtimes via containers. For the most up-to-date list and details, check out the official AWS Lambda documentation.

In this tutorial, you will walk through the process of building, testing, and deploying a multi-agent AI system using LangGraph, Docker, AWS Lambda, and CircleCI. You will develop a research-driven AI workflow where different agents,such as fact-checking, summarization, and search agents, work together seamlessly. You will package this application into a Docker container, deploy it to AWS Lambda, and automate the entire pipeline using CircleCI.

Backend: It handles API functions (e.g. AWS Lambda, Cloudflare Workers, GCP Functions)

Teachers, freelancers, and inbox zero purists rejoice: I built EmailDrop, a one-click AWS deployment that turns incoming emails into automatic Google Drive uploads. With Postmark's new inbound webhooks, AWS Lambda, and a little OAuth wizardry, attachments fly straight from your inbox to your Google Drive. In this post, I’ll walk through how I built it using Postmark, CloudFormation, Google Drive, and serverless tools, and how you can deploy it with zero manual code.