sysbox
firecracker
sysbox | firecracker | |
---|---|---|
22 | 75 | |
2,525 | 24,127 | |
2.1% | 1.2% | |
8.6 | 9.9 | |
2 days ago | about 20 hours ago | |
Shell | Rust | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
sysbox
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Podman Desktop: A Free OSS Alternative to Docker Desktop
You are probably referring to Sysbox (https://github.com/nestybox/sysbox), which I believe will meet your requirements (systemd, inner containers, security, etc).
Btw, Sysbox is already supported in Docker-Desktop (business tier only), so you can easily do what you want with this instruction:
$ docker run -it --rm -e SYSBOX_SYSCONT_MODE=TRUE nestybox/ubuntu-focal-systemd-docker:latest bash
Disclaimer: I'm Sysbox's co-creator and currently working for Docker.
- Sysbox: VM-Like Containers
- What companies are using golang and have source code in github?
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SELinux is unmanageable; just turn it off if it gets in your way
One project in this space that looked quite promising to me is sysbox[0]. I've used them once for a gitlab runner set-up similar to what is described in their blog[1].
It's currently working great and I have not had any major crashes/incidents for at least the past 8 months.
[0]: https://github.com/nestybox/sysbox
[1]: https://blog.nestybox.com/2020/10/21/gitlab-dind.html
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Jenkins in Docker: Running Docker in a Jenkins container
Today, things are very different. Docker-in-Docker has a more secure and safe approach with rootless containers and freemium tools like sysbox. Tools like sysbox let you run Docker-in-Docker without the -privileged flag and optimizes specific scenarios, like running multiple nodes of a Kubernetes cluster as ordinary containers.
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Run untrusted code in sandbox
Right now I am going with sysbox rootless containers. https://github.com/nestybox/sysbox
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Real-world stories of how we’ve compromised CI/CD pipelines
We’ve been using Sysbox (https://github.com/nestybox/sysbox) for our Buildkite based CI/CD setup, allows docker-in-docker without privileged containers. Paired with careful IAM/STS design we’ve ended up with isolated job containers with their own IAM roles limited to least-privilege.
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Individual Docker Desktops vs hosting on a server?
A good alternative to the VM approach is to use Kubernetes + Sysbox (a next-gen "runc", free, open-source).
- Sysbox now works on K8s v1.21
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Does running a container with privileged mode turn on allow code to escape into the Host ?
But nowadays there is an option to run such software in containers securely. It's called Sysbox, and it's a new "runc" (the piece of software that creates the containers). I am one of the developers, so I am biased, but I think you'll find it helpful.
firecracker
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Lambda Internals: Why AWS Lambda Will Not Help With Machine Learning
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.
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Show HN: Add AI code interpreter to any LLM via SDK
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...
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Fly.it Has GPUs Now
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...
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MotorOS: a Rust-first operating system for x64 VMs
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
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Virtual Machine as a Core Android Primitive
According to their own FAQ it is indeed: https://github.com/firecracker-microvm/firecracker/blob/main...
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Sandboxing a .NET Script
What about microVMs like firecracker?
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We Replaced Firecracker with QEMU
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...
- I'm looking for a virtual machine that prioritizes privacy and does not include tracking or telemetry.
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Neverflow: Set of C macros that guard against buffer overflows
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.
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Do you use Rust in your professional career?
https://github.com/firecracker-microvm/firecracker is the one that comes to mind, but most of these are internal.
What are some alternatives?
kata-containers - Kata Containers is an open source project and community working to build a standard implementation of lightweight Virtual Machines (VMs) that feel and perform like containers, but provide the workload isolation and security advantages of VMs. https://katacontainers.io/
cloud-hypervisor - A Virtual Machine Monitor for modern Cloud workloads. Features include CPU, memory and device hotplug, support for running Windows and Linux guests, device offload with vhost-user and a minimal compact footprint. Written in Rust with a strong focus on security.
containerd - An open and reliable container runtime
bottlerocket - An operating system designed for hosting containers
dind - Docker in Docker
gvisor - Application Kernel for Containers
libkrun - A dynamic library providing Virtualization-based process isolation capabilities
gatekeeper - 🐊 Gatekeeper - Policy Controller for Kubernetes
krunvm - Create microVMs from OCI images
snekbox - Easy, safe evaluation of arbitrary Python code
deno - A modern runtime for JavaScript and TypeScript.