spawner VS e2core

For the “jhub but for any container that speaks HTTP” use case, you might find our Spawner project interesting: https://github.com/drifting-in-space/spawner

We don’t have a good story for volumes yet, but I’m open to ideas.

Is the appeal of isolates in this case the cold start time or the isolation? We're working on some open source infrastructure for running sandboxed (gVisor) containers on the fly from web services[1], and one of the use cases people have is serving Jupyter notebooks which seems like it might resemble your use case?

[1] https://github.com/drifting-in-space/spawner/

yes! a fellow HN user e-mailed me about his project "Spawner"

https://github.com/drifting-in-space/spawner

check out the demo: https://www.youtube.com/watch?v=aGsxxcQRKa4

Drifting in Space | Full-time | NYC | https://driftingin.space

We make Jamsocket (https://jamsocket.com/), which allows application developers to spin up and connect to server-side compute. This allows browser-based applications to do computationally-intensive things that are otherwise impossible in the browser.

We went through YC and just raised a seed round and are looking to build up our team. We are based in NYC but are open to remote for experience candidates.

Our tech stack includes Rust, NATS, Docker, Postgres, TypeScript. We have lots of fun technical problems that get into the nitty-gritty of networking and operating systems. We are excited to build a diverse team and encourage non-traditional candidates to apply.

Email [email protected] or see more details here: https://www.ycombinator.com/companies/drifting-in-space/jobs...

Hi HN, we’re Paul and Taylor, and we’re launching Drifting in Space (https://driftingin.space). We build server software for performance-intensive browser-based applications. We make it easy to give every user of your app a dedicated server-side process, which starts when they open your application and stops when they close the tab.

Many high-end web apps give every user a dedicated connection to a server-side process. That is how they get the low latency that you need for ambitious products like full-fledged video editing tools and IDEs. This is hard for smaller teams to recreate, though, because it takes a significant ongoing engineering investment. That’s where we come in—we make this architecture available to everyone, so you can focus on your app instead of its infrastructure. You can think of it like Heroku, except that each of your users gets their own server instance.

I realized that something like this was needed while working on data-intensive tools at a hedge fund. I noticed that almost all new application software, whether it was built in-house or third-party SaaS, was delivered as a browser application rather than native. Although browsers are more powerful than ever, I knew from experience that industrial-scale data-heavy apps posed problems, because neither the browser or a traditional stateless server architecture could provide the compute resources needed for low-latency interaction with large datasets. I began talking about this with my friend Taylor, who had encountered similar limitations while working on data analysis and visualization tools at Datadog and Uber. We decided to team up and build a company around solving it.

We have two products, an open source package and a managed platform. Spawner, the open source part, provides an API for web apps to spawn a session-lived process. It manages the process’s lifecycle, exposing it over HTTPS, tracking inbound connections, and shutting it down when it becomes idle (i.e. when the user closes their tab). It’s open source (MIT) and available at https://github.com/drifting-in-space/spawner.

Jamsocket is our managed platform, which uses Spawner internally. It provides the same API, but frees you from having to deal with any cluster or network configuration to ship code. From an app developer’s point of view, using it is similar to using platforms like Netlify or Render. You stay in the web stack and never have to touch Kubernetes.

Here's an example. Imagine you make an application for investigating fraud in a large transaction database. Users want to interactively filter, aggregate, and visualize gigabytes of transactions as a graph. Instead of sending all of the data down to the browser and doing the work there, you would put your code in a container and upload it to our platform. Then, whenever a fraud analyst opens your application, you hit an API we provide to spin up a dedicated backend for that analyst. Your browser code then opens a WebSocket connection directly to that backend, which it uses to stream data as the analyst applies filters or zooms/pans the visualization.

We're different from most managed platforms because we give each user a dedicated process. That said, there are a few other services that do run long-lived processes for each user. Architecturally, we're most similar to Agones. Agones is targeted at games where the client can speak UDP to an arbitrary IP; we target applications that want to connect directly from browsers to a hostname over HTTPS. In the Erlang world, the OTP stack provides similar functionality, but you have to embrace Erlang/Elixir to get the benefits of it; we are entirely language-agnostic. Cloudflare Durable Objects support a form of long-lived processes, but are focused on use cases around program state synchronization rather than arbitrary high-compute/memory use cases.

We have a usage-based billing model, similar to Heroku. We charge you for the compute you use and take a cut. Usage billing scales to zero, so it’s approachable for weekend experiments. We have not solidified a price plan yet, but we’re aiming to provide an instance capable of running VS Code (as an example) for about 10 cents an hour, fractionally metered. High-memory and high-CPU backends will cost more, and heavy users will get volume discounts. Our target customers are desktop-like SaaS apps and internal data tools.

As mentioned, our core API is open source and available at https://github.com/drifting-in-space/spawner. The managed platform is in beta and we’re currently onboarding users from a waitlist, to make sure that we have the server capacity to scale. If you’re interested, you’re welcome to sign up for it here: https://driftingin.space.

Have you built a similar infrastructure for your application? We’re always interested in hearing the approaches people have already taken to this problem and learning what their pain points are.

> If one writes Go or Rust, there are much better ways to run them than targeting WASM

wasm has its place, especially for contained workloads that can be wrapped in its strict capability boundaries (think, file-encoding jobs that shouldn't access anything else but said files: https://news.ycombinator.com/item?id=29112713).

> Containers are still the defacto standard.

wasmedge [0], atmo [1], krustlet [2], blueboat [3] and numerous other projects are turning up the heat [4]!

[0] https://github.com/WasmEdge/WasmEdge

[1] https://github.com/suborbital/atmo

[2] https://github.com/krustlet/krustlet

[3] https://github.com/losfair/blueboat

[4] https://news.ycombinator.com/item?id=30155295

One of the first things we've used it for internally is to run one-off isolated tests on WebAssembly modules instead of feeding them through a production Atmo[0] instance. It basically serves as a dumb pipe for feeding data in and out of a Wasm module.

0: https://github.com/suborbital/atmo

Excited to see Atmo on there 🙂 https://github.com/suborbital/atmo

My open source focus for this year is building Atmo, and there is one aspect of the process that I would like to highlight. Since early 2020 I knew roughly what I wanted to build. The specifics of that thing changed over time, but the core idea of a server-side WebAssembly platform was consistent all throughout the year. I didn't write a single line of code for Atmo until late October, even though that was what I wanted to build the entire time. I want to talk about why.

I am also open to any and all contributions from the community. I am more than happy to meet with anyone interested in working alongside me to build these capabilities so that I can help get you started developing Atmo, Vektor, Grav, Hive, and Subo. Developers with no experience working with WebAssembly, distributed systems, web services, or Go are encouraged to join and I will do whatever I can to help you learn what's needed to contribute. Open Source is not just about developing in the open, it's also about helping others learn.

With SUFA systems, multiple ASGs are created, each designated as a capability group. Each capability group is given access to the resources required for the associated function namespace to operate (such as the datastore or secrets), and can then scale independently of one another. Since the application's functions are decoupled entirely from one another, it's possible for some functions to run on the host that receives the request, and functions from particular namespaces to be meshed into other capability groups. A SUFA framework such as Atmo is responsible for handling the meshed communication, completely absorbing the complexity.

The SUFA pattern was designed in concert with Atmo, which is an all-in-one framework upon which SUFA systems can be built. Atmo uses a file known as a 'Directive' to describe all aspects of your application, including how to chain functions to handle requests. You can write your functions using several languages to be run atop Atmo, as it is built to use WebAssembly modules as the unit of compute. Atmo will automatically scale out to handle your application load, and includes all sorts of tooling and built-in best practices to ensure you're getting the best performance and security without needing to write a single line of boilerplate ever again.