cap-std VS firecracker

I believe you mean capability based, like cap-std.

There might be another reason to prefer async-std right now: the Bytecode Alliance is working on a version of std with support for capability-based security (called cap-std: https://github.com/bytecodealliance/cap-std ), and their async version is based on async-std (called cap-async-std: https://github.com/bytecodealliance/cap-std/tree/main/cap-async-std ). Given the clout that the Bytecode Alliance has, async-std might end up carving a niche out in the Wasm domain.

Would love to see something like this implemented around creating a Process in cap-std ( https://github.com/bytecodealliance/cap-std/issues/190 )

I think it's not discussed enough how things like language features shape how library APIs are formed. People usually seem to only consider the question "how would I use this feature?" and not "how would the standard library look like with this feature?", which is surprising given how much builtin libraries affect the pleasantness of a language.

One of the things I'm excited to see is the cap-std project for Rust [0] given what Pony [1] has demonstrated is possible with capabilities. I'm also hoping that languages like Koka [2] and OCaml [3] will demonstrate interesting use cases for algebraic effects.

[0] https://github.com/bytecodealliance/cap-std

[1] https://www.ponylang.io/discover

[2] https://koka-lang.github.io

[3] https://github.com/ocaml-multicore/effects-examples

I'm not sure you could hack the control flow when running bytecode on the JVM, but I strongly doubt that. (The JVM is "high-level" as pointed out previously and doesn't execute ASM like code. So there is no of the attack surface you have to care on the ASM level).

And capabilities are anyway something that belongs into the OS — and than programs need to be written accordingly. The whole point of the capability-security model is that you can't add it after the fact. That's why UNIX isn't, and never will be, a capability secure OS.

But "sanboxing" some process running on a VM is completely independent of that!

WASM won't get you anything beyond a "simple sanbox" ootb. Exactly the same as you have in the other major VM runtimes.

If you want capability-secure Rust, there is much more to that. You have to change a lot of code, and use an alternative std. lib¹. Of course you can't than use any code (or OS functionality) when it isn't also capability-secure. Otherwise the model breaks.

To be capability-secure you have actually to rewrite the world…

¹ https://github.com/bytecodealliance/cap-std

The type system could definitely help. There's all sorts of things we can do. One really cool project is https://github.com/bytecodealliance/cap-std

On the topic of unsafe being used to describe raw file descriptors, on one hand, there is a sense in which file descriptors are pointers, into another memory. They can leak, dangle, alias, or be forged, in exactly the same way. On the other, there is an open issue about this.

This architecture leverages microVMs for rapid scaling and high-density workloads. But does it work for GPU? The answer is no. You can look at the old 2019 GitHub issue and the comments to it to get the bigger picture of why it is so.

Hi, I'm the CEO of the company that built this SDK.

We're a company called E2B [0]. We're building and open-source [1] secure environments for running untrusted AI-generated code and AI agents. We call these environments sandboxes and they are built on top of micro VM called Firecracker [2].

You can think of us as giving small cloud computers to LLMs.

We recently created a dedicated SDK for building custom code interpreters in Python or JS/TS. We saw this need after a lot of our users have been adding code execution capabilities to their AI apps with our core SDK [3]. These use cases were often centered around AI data analysis so code interpreter-like behavior made sense

The way our code interpret SDK works is by spawning an E2B sandbox with Jupyter Server. We then communicate with this Jupyter server through Jupyter Kernel messaging protocol [4].

We don't do any wrapping around LLM, any prompting, or any agent-like framework. We leave all of that on users. We're really just a boring code execution layer that sats at the bottom that we're building specifically for the future software that will be building another software. We work with any LLM. Here's how we added code interpreter to Claude [5].

Our long-term plan is to build an automated AWS for AI apps and agents.

Happy to answer any questions and hear feedback!

[0] https://e2b.dev/

[1] https://github.com/e2b-dev

[2] https://github.com/firecracker-microvm/firecracker

[3] https://e2b.dev/docs

[4] https://jupyter-client.readthedocs.io/en/latest/messaging.ht...

[5] https://github.com/e2b-dev/e2b-cookbook/blob/main/examples/c...

As far as I know, Fly uses Firecracker for their VMs. I've been following Firecracker for a while now (even using it in a project), and they don't support GPUs out of the box (and have no plan to support it [1]).

I'm curious to know how Fly figured their own GPU support with Firecracker. In the past they had some very detailed technical posts on how they achieved certain things, so I'm hoping we'll see one on their GPU support in the future!

[1]: https://github.com/firecracker-microvm/firecracker/issues/11...

I pass through a GPU and USB hub to a VM running on a machine in the garage. An optical video cable and network compatible USB extender brings the interface to a different room making it my primary “desktop” computer (and an outdated laptop as a backup device). Doesn’t get more silent and cool than this. Another VM on the garage machine gets a bunch of hard drives passed through to it.

That said, hardware passthrough/VFIO is likely out of the current realistic scope for this project. VM boot times can be optimized if you never look for hardware to initialize in the first place. Though they are still likely initializing a network interface of some sort.

“MicroVM” seems to be a term used when as much as possible is stripped from a VM, such as with https://github.com/firecracker-microvm/firecracker

According to their own FAQ it is indeed: https://github.com/firecracker-microvm/firecracker/blob/main...

What about microVMs like firecracker?

Dynamic memory management - Firecracker's RAM footprint starts low, but once a workload inside allocates RAM, Firecracker will never return it to the host system. After running several workloads inside, you end up with an idling VM that consumes 32 GB of RAM on the host, even though it doesn't need any of it.

Firecracker has a balloon device you can inflate (ie: acquire as much memory inside the VM as possible) and then deflate... returning the memory to the host.

https://github.com/firecracker-microvm/firecracker/blob/main...

Very few things in those companies are being written in Rust, and half of those projects chose Rust around ideological reasons rather than technical, with plenty of 'unsafe' thrown in for performance reasons

https://github.com/firecracker-microvm/firecracker/search?q=...

The fact that 'unsafe' even exists in Rust means it's no better than C with some macros.

Don't get me wrong, Rust has it's place, like all the other languages that came about for various reasons, but it's not going to gain wide adoption.

Future of programming consists of 2 languages - something like C that has a small instruction set for adopting to new hardware, and something that is very high level, higher than Python with LLM in the background. Everything in the middle is fodder.

https://github.com/firecracker-microvm/firecracker is the one that comes to mind, but most of these are internal.