krunvm VS firecracker

Lots of cool hybrid container/VM ideas are being developed!

Bootable Container Images are a standard for launching VMs from OCI images: https://containers.github.io/bootable/

crun-vm (https://github.com/containers/crun-vm) is similar to RunCVM in that it can launch container images (or VM disk images) in VMs. It's an OCI runtime so it fits into the podman, Docker, or Kubernetes model.

krunvm (https://github.com/containers/krunvm) is a standalone tool with a similar workflow where you can launch a VM from an OCI image. It predates Bootable Container Images, so I think it injects its own kernel.

This project creates self-hosted (ephemeral) GitHub runners based on krunvm [1]. krunvm creates microVMs, so the project enables fully isolated runners inside your infrastruture. MicroVMs boot fast, providing an experience close to running containers. The project starts VMs based on the multi-platform OCI images that it creates -- ubuntu [2](default) or fedora [3]. The default is to create far-less capable runners than the GitHub runners, but most settings are similar to when running at GitHub: same user ID, member of the `docker` group, password-less `sudo`, etc. Since krunvm runs on MacOS, this should also run on MacOS -- although I haven't been able to test it: reports and/or PRs are welcome.

[1]: https://github.com/containers/krunvm

An interesting alternative is krunvm. On my MacBook Pro M1 it takes less than a second to start a VM and get a Linux shell prompt with krunvm . When I boot up a Fedora CoreOS on the same computer it takes about 17 seconds. Note though that krunvm is for managing lightweight VMs created from OCI images.

Well, FireCracker has a jailer process: https://github.com/firecracker-microvm/firecracker/blob/main...

Hello, I'm the CEO of the company that built this - E2B [0]. We're building infrastructure for AI code interpreting. Companies like Perplexity are using us.

We're using Firecrackers [1] to power our sandboxes. Funnily enough, we had this repo sitting on our GitHub for about 6 months. We originally made this for one of our customers because they were running evals on the desktop-like environment with GUI for their model.

You can use PyAutoGUI [2] to control the whole environment programmatically.

The desktop-like environment is based on Linux and Xfce [3] at the moment. We chose Xfce because it's a fast and lightweight environment that's also popular and actively supported. However, this Sandbox template is fully customizable and you can create your own desktop environment.

Let me know if you have any questions!

[0] https://e2b.dev

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

[2] https://pyautogui.readthedocs.io/

[3] https://www.xfce.org/

What he said is true, AWS uses Rust heavily in some of AWS core systems https://aws.amazon.com/blogs/devops/why-aws-is-the-best-plac....

Some of the open source projects you can find are AWS Firecracker https://github.com/firecracker-microvm/firecracker and Cloudflare Pingora https://github.com/cloudflare/pingora

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?