As a minor thought / question – I'm a little surprised that this isn't (yet) wired up for pods to run in Web workers.
I appreciate that there is a Clock mechanism (allowing you to step the cluster), which would be more difficult in that setup, but... I feel like especially with SharedArrayBuffer (which admittedly requires the right COOP/COEP), that could be pulled off with atomics.
Would be very cool to be able to actually thread in earnest with this design!
This is cool. As someone who has authored Kubernetes educational content in a past role, I can definitely see the appeal of building something like this. iirc we first used Katacoda and then used some other similar platform and they were very useful since they spun up a fresh instance on the fly for each user with a specific setup.
Though it seems like right now this is probably better for conceptual/architectural education. The real fun is when you start learning to master kubectl.
Yeah, in a past role this would have been awesome for diagrams to explain how the control plane works, illustrating the degradation and failure modes, or comparing different architectures/ways to deploy onto k8s/
First thing is first, this is really cool.
This feels like the right way to frame LLM-assisted engineering. AI can generate a shocking amount of code, but the actual value is in the review discipline, and tests around it. The browser Kubernetes angle is cool, but what I find more interesting is the workflow, and especially testing behaviour against k8s instead of just trusting “looks right.” I do wonder how many teams are already doing this level of verification for AI-written code. It might be the direction everyone goes in over the next few years.
A meta-trend I find interesting is there's a lot of projects using AI to rewrite existing systems in new programming languages. Most often in Rust.
1. Bun rewritten in Rust
2. Flow rewritten in Rust
3. The react compiler was rewritten in Rust
4. Grit is a new implementation of Git in Rust
5. I've made my own rust rewrite of postgres that passes 100% of the regression and isolation tests[0][1]
I think AI changed the economics of these projects even more than it has the economics for software engineering work in general. Though direct AI code translation is usually slop for me.
One of the many things I did to deal with this was an audit skill that would:
1. Find a small chunk of code to rewrite
2. Have a list of things that it was looking for in each piece of code that's being rewritten
3. Place that next to the code being translated
4. If that document didn't exist and/or didn't say the code was passing the audit, code wouldn't be merged
5. As I found problems and anti-patterns I would add those to the skill over time
This by itself still let a lot of slop slip through, but also preemptively caught a ton of issues as part of my overall process.
Complicated old "boring" infra software might actually be the most AI-rewriteable code right now
I have been experimenting in this general area myself. I started by doing a port of Lua to Rust, then did Valkey to Rust using my Rust Lua for scripting, and now I've been working nginx in Rust.
I was thinking for all of these that the end goal is to take some existing technology and add some novel features rather than just X in Rust so what I have so far.
1. The Lua project bundles Lua 5.1 - 5.5 in one binary and one npm package so it's easy to run in the browser or CloudFlare Worker etc.
2. The Valkey (Redis) port builds something called EdgeStash - lets you run Valkey with Lua scripting in a CloudFlare Durable Object programmable with Lua scripting.
Perhaps to anticipate the multiple jokes about kube complexity, I think there's an interesting argument to make that something like kube is the necessary complexity level for the kinds of tasks that kube is intended to accomplish, ala Fred Brooks' rule about essential complexity vs accidental complexity.
Kube rapidly becomes accidental complexity when you use it to accomplish things that could be done more simply, of course.
So your prior is that token costs are only going to go up. Doesn't stuff like GLM 5.2 and Deepseek change this? I.e. something close to Opus 4.5 that runs 10X + more performantly.
> Is this just slop?
> Almost all of the webernetes code was authored by LLMs
> ...
> I did two things that I think make this a slop-free project:
> 1. I reviewed every line of code.
> 2. I created hundreds of tests that assert webernetes behaves the same as a real cluster.
Interesting project and (possibly more) interesting explanation of the development process. I agree with the author that the primary difference between vibe slop and real engineering is just reading the lines of code. However it does feel like we are just on the cusp of only needing to read the tests and _not_ all the lines of code. Maybe a few more model generations and we will be there.
First of all, this is wonderful stuff!
As a minor thought / question – I'm a little surprised that this isn't (yet) wired up for pods to run in Web workers.
I appreciate that there is a Clock mechanism (allowing you to step the cluster), which would be more difficult in that setup, but... I feel like especially with SharedArrayBuffer (which admittedly requires the right COOP/COEP), that could be pulled off with atomics.
Would be very cool to be able to actually thread in earnest with this design!
This is cool. As someone who has authored Kubernetes educational content in a past role, I can definitely see the appeal of building something like this. iirc we first used Katacoda and then used some other similar platform and they were very useful since they spun up a fresh instance on the fly for each user with a specific setup.
Though it seems like right now this is probably better for conceptual/architectural education. The real fun is when you start learning to master kubectl.
Yeah, in a past role this would have been awesome for diagrams to explain how the control plane works, illustrating the degradation and failure modes, or comparing different architectures/ways to deploy onto k8s/
Investing early in this hn post before it’s a banger. Instant classic
It's Web Scale Technology™
100%
Relatedly, I vibecoded this a few days ago for fun: https://imjasonh.github.io/kubescheduler-the-game/
It was fun.
First thing is first, this is really cool. This feels like the right way to frame LLM-assisted engineering. AI can generate a shocking amount of code, but the actual value is in the review discipline, and tests around it. The browser Kubernetes angle is cool, but what I find more interesting is the workflow, and especially testing behaviour against k8s instead of just trusting “looks right.” I do wonder how many teams are already doing this level of verification for AI-written code. It might be the direction everyone goes in over the next few years.
I mean this is a specific case where you literally have a spec to code against. Not all coding endeavors have that opportunity, unfortunately.
For a lot of us, the spec is Product Market Fit and Profit Dollars.
A meta-trend I find interesting is there's a lot of projects using AI to rewrite existing systems in new programming languages. Most often in Rust.
I think AI changed the economics of these projects even more than it has the economics for software engineering work in general. Though direct AI code translation is usually slop for me.One of the many things I did to deal with this was an audit skill that would:
This by itself still let a lot of slop slip through, but also preemptively caught a ton of issues as part of my overall process.Complicated old "boring" infra software might actually be the most AI-rewriteable code right now
[0] https://pgrust.com
[1] https://github.com/malisper/pgrust
I have been experimenting in this general area myself. I started by doing a port of Lua to Rust, then did Valkey to Rust using my Rust Lua for scripting, and now I've been working nginx in Rust.
I was thinking for all of these that the end goal is to take some existing technology and add some novel features rather than just X in Rust so what I have so far.
1. The Lua project bundles Lua 5.1 - 5.5 in one binary and one npm package so it's easy to run in the browser or CloudFlare Worker etc.
2. The Valkey (Redis) port builds something called EdgeStash - lets you run Valkey with Lua scripting in a CloudFlare Durable Object programmable with Lua scripting.
https://edgestash-valdr.ianmclaughlin1398.workers.dev/ that's a demo of the Edge Valkey node running.
I've been meaning to take take it and do something like yours that is sweet!
+1 CC helped me finally shipped a Rust project I had been sleeping on for years.
Perhaps to anticipate the multiple jokes about kube complexity, I think there's an interesting argument to make that something like kube is the necessary complexity level for the kinds of tasks that kube is intended to accomplish, ala Fred Brooks' rule about essential complexity vs accidental complexity.
Kube rapidly becomes accidental complexity when you use it to accomplish things that could be done more simply, of course.
This is awesome. Wish I had the idea first. I see this as a fun learning and experimental tool.
For a while I have wanted to make a web page where you can do service load balancing and queuing simulations so this would be a great basis for it.
I wonder if stuff like this will also be created when token costs explode.
So your prior is that token costs are only going to go up. Doesn't stuff like GLM 5.2 and Deepseek change this? I.e. something close to Opus 4.5 that runs 10X + more performantly.
No, because those loans still have to be repaid.
Yes, because you can buy infinity tokens for $10,000 with hardware.
wasm should be the "image" type for webernetes
There's even a blog/article write-up with a more succinct demo of Kubernetes: https://ngrok.com/blog/i-ported-kubernetes-to-the-browser
edit: added the slop-free remarksInteresting project and (possibly more) interesting explanation of the development process. I agree with the author that the primary difference between vibe slop and real engineering is just reading the lines of code. However it does feel like we are just on the cusp of only needing to read the tests and _not_ all the lines of code. Maybe a few more model generations and we will be there.
This is great!
And now for a fun game with this: try and delete all the pods!
"Just because one can do a thing does not mean one should do that thing."
Please port Kubernetes to common house flies so that they drop dead out of all the unnecessary overhead. That would be helpful.
what will we port to the spiders whose population will otherwise surely explode?