llrt VS sst

Any plans to add support for? https://github.com/awslabs/llrt

It would also be nice to have a V8/deno/bun based edge hosting option that supports the Next.js edge and middleware code splitting. That's the missing piece for most homebrew "edge" setups. Production CDNs like Clouflare and Supabase all offer this.

Vlad Ionescu: Scaling containers on AWS in 2022 GitHub: awslabs/llrt AWS Documentation: Understanding the Lambda execution environment Amazon Science: How AWS's Firecracker virtual machines work Lumigo GitHub: MiddyJS

Its refreshing to see all the various JS engines that are out there for various usecases.

I have been working on providing quickjs with more node compatible API through llrt [1] for embedding into applications for plugins.

[1] https://github.com/awslabs/llrt

AWS has open-sourced its JavaScript runtime, called LLRT (Low Latency Runtime), an experimental, lightweight JavaScript runtime designed to address the growing demand for fast and efficient Serverless applications.

FROM --platform=arm64 busybox WORKDIR /var/task/ COPY app.mjs ./ ADD https://github.com/awslabs/llrt/releases/latest/download/llrt-container-arm64 /usr/bin/llrt RUN chmod +x /usr/bin/llrt ENV LAMBDA_HANDLER "app.handler" CMD [ "llrt" ]

Let’s get the simplest use case out of the way: cases where the cold starts are so fast that it’s not an issue for you. That’s usually the case for function that use runtimes such as C++, Go, Rust, and LLRT. However, you must follow the best practices and optimizations in every runtime to maintain a low impact cold start.

But compared to other runtimes, LLRT is not so good in terms of performance when it comes to dealing with large data processing, Monte Carlo simulations, or performing tasks with a large number of iterations. The AWS team says that it is best suited for working with smaller Serverless functions dedicated to tasks such as data transformation, real-time processing, AWS service integrations, authorization, validation, etc. Visit the GitHub repository of this project to learn more information.

And lastly, lean into your cloud vendor. Stop trying to build a better mouse trap. Advances in technology are happening all the time. The speed of AWS' Lambda has been rapidly improving over the past couple of years with the launch of things like SnapStart and LLRT

Modern IoC tools like SST are highly “aware” of the functional side of your codebase. They embed into your app’s logic to make for a streamlined and more failproof development. Modren IoC tools often provide incredibly abstract APIs, which makes it simpler for you and your AI companion to comprehend.

Most projects I know that revolves around Blinks or Blockchain Links often use Next.js's API Routes to develop and deploy Blinks. But did you know that apart from Next.js, you can actually build Blinks on your favorite Node backend? In this article, we'll use Serverless Stack (SST) to develop and deploy our Blinks on AWS!

wow very very interesting. I think we can discuss about it on hours.

1.) What would you think of things like hetzner / linode / digitalocean (if stable work exists)

2.) What do you think of https://sst.dev/ or https://encore.dev/ ? (They support rather easier migration)

3.) Could you please indicate the split of that 1 million $ in devops time and google cloud costs unnecessarily & were there some outliers (like oh our intern didn't add this specific variable and this misconfigured cloud and wasted 10k on gcloud oops! or was it , that bandwidth causes this much more in gcloud (I don't think latter to be the case though))

Looking forward to chatting with you!

SST is a framework that makes it easy to build modern full-stack applications on your own infrastructure. SST v3 uses Pulumi and Terraform – SST Documenation

SST[1] looks pretty cool. Does it replicate the entire infrastructure Vercel attempts to provide you regarding hosting (such as CDN, caching, etc)?

[1]. https://sst.dev/

In case it’s helpful to anyone who has to jump off vercel:

I recently had to transition my company off of vercel for reasons unrelated to this (wanted to use cloud infra primitives that vercel does not provide, and wanted to leverage the large amount of AWS credits my company received) and found that sst.dev [0] to be easy to migrate to and a joy to use in general. It leverages open-next to deploy next.js projects on AWS in a serverless way.

I’ve been enjoying using it so much that for my next project I think I’ll skip vercel altogether and use sst from the start.

[0] https://sst.dev/

We see some great results from using these in conjunction with frameworks such as SST or Serverless, and also some real spaghetti from people who organically proliferate 100’s of functions over time and lose track of how they relate to each other or how to update them safely across time and service. Buyer beware!

> But if you have a sufficiently large enough API surface, doing one lambda per endpoint comes with a lot of pain as well. Packaging and deploying all of those artifacts can be very time consuming, especially if you have a naive approach that does a full rebuild/redeploy every time the pipeline runs.

Yeah, thankfully SST [0] does the heavy lifting for me. I've tried most of the solutions out there and SST was where I was the happiest. Right now I do 1 functions per endpoint. I structure my code like url paths mostly, 1 stack per final folder, so that the "users" folder maps to "/users/*" and inside I have get/getAll/create/update/delete files that map to GET X/id, GET X, POST X, POST X/id, DELETE/id. It works out well, it's easy to reason about, and deploys (a sizable a backend) in about 10min on GitHub Actions (which I'm going to swap out probably for something faster).

I agree with the secrets/permissions aspect and I like that it's stupid-simple for me to attach secrets/permissions at a low level if I want.

I use NodeJS and startup isn't horrible and once it's up the requests as very quick. For my needs, an the nature of the software I'm writing, lambda makes a ton of sense (mostly never used, but when it's used it's used heavily and needs to scale up high).

[0] https://sst.dev

We will start by building a project with SST that provisions an API Gateway, a Lambda, and an S3 bucket. Once implemented, we'll look into testing for concurrent write conflicts or exceeding capacity limits.

I recently deployed a node websocket server using the SST Service construct. Until this point my stack had been functions and buckets. While I had no users 😢, I also had no costs 🤡.