firecracker
gvisor
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firecracker | gvisor | |
---|---|---|
75 | 64 | |
24,024 | 15,066 | |
1.7% | 2.8% | |
9.9 | 9.9 | |
6 days ago | 5 days ago | |
Rust | Go | |
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.
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.
gvisor
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Maestro: A Linux-compatible kernel in Rust
Isn't gVisor kind of this as well?
"gVisor is an application kernel for containers. It limits the host kernel surface accessible to the application while still giving the application access to all the features it expects. Unlike most kernels, gVisor does not assume or require a fixed set of physical resources; instead, it leverages existing host kernel functionality and runs as a normal process. In other words, gVisor implements Linux by way of Linux."
https://github.com/google/gvisor
- Google/Gvisor: Application Kernel for Containers
- GVisor: OCI Runtime with Application Kernel
- How to Escape a Container
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Faster Filesystem Access with Directfs
This sort of feels like seeing someone riding a bike and saying: why don’t they just get a car? The simple fact is that containers and VMs are quite different. Whether something uses VMX and friends or not is also a red herring, as gVisor also “rolls it own VMM” [1].
[1] https://github.com/google/gvisor/tree/master/pkg/sentry/plat...
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OS in Go? Why Not
There's two major production-ready Go-based operating system(-ish) projects:
- Google's gVisor[1] (a re-implementation of a significant subset of the Linux syscall ABI for isolation, also mentioned in the article)
- USBArmory's Tamago[2] (a single-threaded bare-metal Go runtime for SOCs)
Both of these are security-focused with a clear trade off: sacrifice some performance for memory safe and excellent readability (and auditability). I feel like that's the sweet spot for low-level Go - projects that need memory safety but would rather trade some performance for simplicity.
[1]: https://github.com/google/gvisor
[2]: https://github.com/usbarmory/tamago
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Tunwg: Expose your Go HTTP servers online with end to end TLS
It uses gVisor to create a TCP/IP stack in userspace, and starts a wireguard interface on it, which the HTTP server from http.Serve listens on. The library will print a URL after startup, where you can access your server. You can create multiple listeners in one binary.
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How does go playground work?
The playground compiles the program with GOOS=linux, GOARCH=amd64 and runs the program with gVisor. Detailed documentation is available at the gVisor site.
- Searchable Linux Syscall Table for x86 and x86_64
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Multi-tenancy in Kubernetes
You could use a container sandbox like gVisor, light virtual machines as containers (Kata containers, firecracker + containerd) or full virtual machines (virtlet as a CRI).
What are some alternatives?
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.
podman - Podman: A tool for managing OCI containers and pods.
bottlerocket - An operating system designed for hosting containers
wsl-vpnkit - Provides network connectivity to WSL 2 when blocked by VPN
libkrun - A dynamic library providing Virtualization-based process isolation capabilities
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/
krunvm - Create microVMs from OCI images
sysbox - An open-source, next-generation "runc" that empowers rootless containers to run workloads such as Systemd, Docker, Kubernetes, just like VMs.
deno - A modern runtime for JavaScript and TypeScript.
containerd - An open and reliable container runtime
rust-raspberrypi-OS-tutorials - :books: Learn to write an embedded OS in Rust :crab:
KubeArmor - Runtime Security Enforcement System. Workload hardening/sandboxing and implementing least-permissive policies made easy leveraging LSMs (BPF-LSM, AppArmor).