Hello, I'm building a replacement for docker containers with a virtual machine with the ergonomics of containers + subsecond start times.
I worked in AWS previously in the container space + with firecracker. I realized the container is an unnecessary layer that slowed things down + firecracker was a technology designed for AWS org structure + usecase.
So I ended up building a hybrid taking the best of containers with the best of firecracker.
That's the one feature of similar systems that always gets left out. I understand why: it's not a priority for "cloud native" workloads. The world, however, has work loads that are not cloud native, because that comes at a high cost, and it always will. So if you'd like a real value-add differentiator for your micro-VM platform (beyond what I believe you already have,) there you go.
It helps if you offer a concrete use case, as in how large the heap is, what kinda of blackout period you can handle, and whether the app can handle all of it's open connections being destroyed, etc. The more an app can handle resetting some of it's own state, the easier LM is going to be to implement. If your workload jives with CRIU https://github.com/checkpoint-restore/criu you could do this already.
By what I assume is your definition, there are plenty of "non cloud native" workloads running on clouds that need live migration. Azure and GCP use LM behind the scenes to give the illusion of long uptime hosts. Guest VMs are moved around for host maintenance.
Hey this is super cool. I've been researching tech like this for my AI sandboxing solution, ended up with Lima+Incus: https://github.com/JanPokorny/locki
My problem with microVMs was that they usually won't run docker / kubernetes, I work on apps that consist of whole kubernetes clusters and want the sandbox to contain all that.
Does your solution support running k3s for example?
+1. i built something similar called shuru.run because i wanted an easy way to set up microVM sandboxes to run some of my AI apps, and firecracker wasn't available for macOS (and, as you said, it is just too heavy for normal user-level workloads).
Nice work on Shuru — I remember looking at it when I was researching this space. You went with a Rust wrapper on Apple’s Virtualization framework right?
I believe anyone with a spare linux box should be able to carve it into isolated programmable machines, without having to worry about provisioning them or their lifecycle.
The documentation’s still early but I have been using it for orchestrating parallel work (with deploy previews), offloading browser automation for my agents etc. An auction bought heztner server is serving me quite well :)
Yes, having a light-weight solution for local devices as well is one primary goal of the design. Another one is to make it easy for hosting, self or managed
hi, great project! Windows support is sorely lacking, though. As someone working a lot with sandboxed LLMs right now, the options-space on windows for sandboxing is _extremely lacking_. Any plans to support it?
Hey, thanks so much! yah we will definitely add windows support later. We are exploring how to get this work with WSL and will release it asap.
Stay tuned and thanks!
smolvm is awesome. The team is highly responsive and very experienced. They clearly know what they’re doing.
I’m currently evaluating smolvm for my project, https://withcave.ai, where I’m using Incus for isolation. The initial integration results look very promising!
question: why do you report that qemu is 15s<x<30s?
for instance with katacontainers, you can run fast microvms, and even faster with unikernels. what was your setup?
We’re using smolmachines to create environments for our agents to execute code. It’s been great so far and the team is super responsive. The dev ergonomics are also great.
Basically any open source project nowadays run their software stack in containers often requiring docker compose. Unfortunatley Smol machines do not support Docker inside the microvms and they also do not support nested VMs for things that use Vagrant. I think this is a big drawback.
I tried something like this already, also including nested kvm. I think this will increase the boot time quiet a bit.
Also libkrun is not secure by default. From their README.md:
> The libkrun security model is primarily defined by the consideration that both the guest and the VMM pertain to the same security context. For many operations, the VMM acts as a proxy for the guest within the host. Host resources that are accessible to the VMM can potentially be accessed by the guest through it.
> While defining the security implementation of your environment, you should think about the guest and the VMM as a single entity. To prevent the guest from accessing host's resources, you need to use the host's OS security features to run the VMM inside an isolated context. On Linux, the primary mechanism to be used for this purpose is namespaces. Single-user systems may have a more relaxed security policy and just ensure the VMM runs with a particular UID/GID.
> While most virtio devices allow the guest to access resources from the host, two of them require special consideration when used: virtio-fs and virtio-vsock+TSI.
> When exposing a directory in a filesystem from the host to the guest through virtio-fs devices configured with krun_set_root and/or krun_add_virtiofs, libkrun does not provide any protection against the guest attempting to access other directories in the same filesystem, or even other filesystems in the host.
Great job with the comparison table. Immediately I was like “neat sounds like firecracker” then saw your table to see where it was similar and different. Easy!
What are you actually doing on top of libkrun? Providing really small machine images that boot quickly? If I run the smolvm run --image alpine example, what is "alpine?" Where is that image coming from? Does this have some built-in default registry of machine images it pulls from? Does it need an Internet connection that allows outbound access to wherever this registry runs? Is it one of a default set of pre-built images that comes with the software itself and is stored on my own filesystem? Where are the builds for these images? Where do these machine images end up? ~/.local/share/smolvm/?
@binsquare basically brute-force trimmed down unnecessary linux kernel modules, tried to get the vm started with just bare minimum. There are more rooms for improvement for sure. We will keep trying!
Yes. files on the disks are kept across stop and restart. We also have a pack command to compress the machine as a single file so that it can shipped and rehydrated elsewhere
I worked in AWS previously in the container space + with firecracker. I realized the container is an unnecessary layer that slowed things down + firecracker was a technology designed for AWS org structure + usecase.
So I ended up building a hybrid taking the best of containers with the best of firecracker.
Let me know your thoughts, thanks!
That's the one feature of similar systems that always gets left out. I understand why: it's not a priority for "cloud native" workloads. The world, however, has work loads that are not cloud native, because that comes at a high cost, and it always will. So if you'd like a real value-add differentiator for your micro-VM platform (beyond what I believe you already have,) there you go.
Otherwise this looks pretty compelling.
By what I assume is your definition, there are plenty of "non cloud native" workloads running on clouds that need live migration. Azure and GCP use LM behind the scenes to give the illusion of long uptime hosts. Guest VMs are moved around for host maintenance.
Thanks
My problem with microVMs was that they usually won't run docker / kubernetes, I work on apps that consist of whole kubernetes clusters and want the sandbox to contain all that.
Does your solution support running k3s for example?
I have been working on something similar but on top of firecracker, called it bhatti (https://github.com/sahil-shubham/bhatti).
I believe anyone with a spare linux box should be able to carve it into isolated programmable machines, without having to worry about provisioning them or their lifecycle.
The documentation’s still early but I have been using it for orchestrating parallel work (with deploy previews), offloading browser automation for my agents etc. An auction bought heztner server is serving me quite well :)
also, yes, shuru was (still) a wrapper over the Virtualization.framework, but it now supports Linux too (wrapper over KVM lol)
WSL2 runs a linux virtual machine. Need to take some time and care to wire that up, but definitely feasible.
Probably a lot of other neat usecases for this, too
Electron ships your web app bundled with a browser.
Smol machines ship your software packaged with a linux vm. No need for dependency management or compatibility issues because it is baked in.
I think this is how Codex or Claude Code should be shipped by default, to avoid any isolation issues tbh
I’m currently evaluating smolvm for my project, https://withcave.ai, where I’m using Incus for isolation. The initial integration results look very promising!
question: why do you report that qemu is 15s<x<30s? for instance with katacontainers, you can run fast microvms, and even faster with unikernels. what was your setup?
thanks a lot
Also libkrun is not secure by default. From their README.md:
> The libkrun security model is primarily defined by the consideration that both the guest and the VMM pertain to the same security context. For many operations, the VMM acts as a proxy for the guest within the host. Host resources that are accessible to the VMM can potentially be accessed by the guest through it.
> While defining the security implementation of your environment, you should think about the guest and the VMM as a single entity. To prevent the guest from accessing host's resources, you need to use the host's OS security features to run the VMM inside an isolated context. On Linux, the primary mechanism to be used for this purpose is namespaces. Single-user systems may have a more relaxed security policy and just ensure the VMM runs with a particular UID/GID.
> While most virtio devices allow the guest to access resources from the host, two of them require special consideration when used: virtio-fs and virtio-vsock+TSI.
> When exposing a directory in a filesystem from the host to the guest through virtio-fs devices configured with krun_set_root and/or krun_add_virtiofs, libkrun does not provide any protection against the guest attempting to access other directories in the same filesystem, or even other filesystems in the host.
https://docs.docker.com/reference/cli/sbx/
I'm building a different virtual machine.
Nice job! This looks really cool
Can you pipe into one? It would be cute if I could wget in machine 1 and send that result to offline machine 2 for processing.
Yes! GPU passthrough is being actively worked on and will land in next major release: https://github.com/smol-machines/smolvm/pull/96
Yea just tried piping, it works:
``` smolvm machine exec --name m1 -- wget -qO- https://example.com/data.csv \ | smolvm machine exec --name m2 -i -- python3 process.py ```
*yes, FreeBSD is specifically developed against Firecracker which is specifically avoided w "Smol machines", but interesting nonetheless
[0] https://github.com/NetBSDfr/smolBSD
[1] https://www.usenix.org/publications/loginonline/freebsd-fire...
microvm space is still underserved.
Colins FreeBSD work or Emiles NetBSD work?
Cheers!
Edit: I see this appears to be a contributor to the project as well. It was not obvious to me.
@binsquare is this one: https://github.com/BinSquare
Though my version was only tested on Linux hosts