iroh VS firecracker

If you're talking about this https://github.com/n0-computer/iroh ... Iroh is a p2p file syncing protocol. That's not even close to the same wheelhouse as SeaweedFS?

Totally biased founder here, but I work on https://github.com/n0-computer/iroh, a thing that started off as an IPFS implementation in rust, but we broke out & ended up doing our own thing. We're not at the point where the iroh implements "the full IPFS experience" (some parts border on impossible to do while keeping a decentralized promise), but we're getting closer to the "p2p website hosting" use case each week.

if you are looking for something similar to ipfs but a bit more minimalistic and performance oriented, check out iroh https://github.com/n0-computer/iroh .

It is a set of open source libraries for peer to peer networking and content-addressed storage. It is written in rust, but we have bindings to many languages.

One part of iroh is a work in progress implementation of the willow spec. The lower layers include a networking library similar to libp2p and a library for content-addressed storage and replication based on blake3 verified streaming.

Most iroh developers have been active in the ipfs community for many years and have shared similar frustrations... See this talk from me in 2019 :-) https://www.youtube.com/watch?v=Qzu0xtCT-R0

IPFS Protocol Stack: Iroh

We have an initial release out since earlier today: https://github.com/n0-computer/iroh/releases/tag/v0.1.0 but we are still very early, so be gentle :)

(Disclosure: I work for the Filecoin Foundation/Filecoin Foundation for the Decentralized Web).

I do actually agree that the privacy and anonymity aspects of IPFS are not well- conveyed. I think people get hooked on the "censorship-resistant" nature of decentralized systems, without understanding that even if you have multiple sources, for instance in a content-addressable network like IPFS, aggressive censorship systems have other strategies to dissuade dissemination or punish readers. You always have to be thinking a few steps ahead. Services like Tor and, I hope, the IPFS network both try to convey what threat models they are useful for, and which they are not, but it's really hard to stop overenthusiastic re-statements that give them super-powers they do not, in fact, possess.

That said, there's a bunch of careful thinking right now going on about how IPFS's privacy story could be improved: https://blog.ipfs.tech/ipfs-ping-2022-recap/ has a couple of sessions on this, and is a great summary of some other recent developments in the space.

One of those improvements is in the point about nodes being high CPU, RAM, etc. (I actually find this to be more of a challenge when running the full IPFS Go node locally on my desktop, rather than on a VPS; it requires some tweaking.)

The strategy right now is to encourage more implementations of IPFS to cover more use-cases; the original go-ipfs had to do everything, including maintaining some legacy decisions. Nowadays, there's a lot of effort on alternative IPFS implementations that can be slimmer, or optimised for particular scenarios, e.g. on an embedded device, serving a high-load web gateway, or providing millions of files. Protocol Labs recently renamed their canonical go-ipfs to kubo (https://github.com/ipfs/kubo ) to make it more of a peer with other implementations.

Of course, I love all these new generation implementations EQUALLY, but if you pushed me, I've enjoyed playing around with https://github.com/n0-computer/iroh , a modular rust implementation building off the increasingly robust rust libp2p etc libraries. There's some more to pick from here: https://docs.ipfs.tech/basics/ipfs-implementations/

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.