Uncloud[0] is a container orchestrator without a control plane. Think multi-machine Docker Compose with automatic WireGuard mesh, service discovery, and HTTPS via Caddy. Each machine just keeps a p2p-synced copy of cluster state (using Fly.io's Corrosion), so there's no quorum to maintain.
I’m building Uncloud after years of managing Kubernetes in small envs and at a unicorn. I keep seeing teams reach for K8s when they really just need to run a bunch of containers across a few machines with decent networking, rollouts, and HTTPS. The operational overhead of k8s is brutal for what they actually need.
A few things that make it unique:
- uses the familiar Docker Compose spec, no new DSL to learn
- builds and pushes your Docker images directly to your machines without an external registry (via my other project unregistry [1])
- imperative CLI (like Docker) rather than declarative reconciliation. Easier mental model and debugging
- works across cloud VMs, bare metal, even a Raspberry Pi at home behind NAT (all connected together)
"I keep seeing teams reach for K8s when they really just need to run a bunch of containers across a few machines"
Since k8s is very effective at running a bunch of containers across a few machines, it would appear to be exactly the correct thing to reach for. At this point, running a small k8s operation, with k3s or similar, has become so easy that I can't find a rational reason to look elsewhere for container "orchestration".
I can only speak for myself, but I considered a few options, including "simple k8s" like [Skate](https://skateco.github.io/), and ultimately decided to build on uncloud.
It was as much personal "taste" than anything, and I would describe the choice as similar to preferring JSON over XML.
For whatever reason, kubernetes just irritates me. I find it unpleasant to use. And I don't think I'm unique in that regard.
> For whatever reason, kubernetes just irritates me. I find it unpleasant to use. And I don't think I'm unique in that regard.
I feel the same. I feel like it's a me problem. I was able to build and run massive systems at scale and never used kubernetes. Then, all of a sudden, around 2020, any time I wanted to build or run or do anything at scale, everywhere said I should just use kubernetes. And then when I wanted to do anything with docker in production, not even at scale, everywhere said I should just use kubernetes.
Then there was a brief period around 2021 where everyone - even kubernetes fans - realised it was being used everywhere, even when it didn't need to be. "You don't need k8s" became a meme.
And now, here we are, again, lots of people saying "just use k8s for everything".
I've learned it enough to know how to use it and what I can do with it. I still prefer to use literally anything else apart from k8s when building, and the only time I've ever felt k8s has been really needed to solve a problem is when the business has said "we're using k8s, deal with it".
It's like the Javascript or WordPress of the infrastructure engineering world - it became the lazy answer, IMO. Or the me problem angle: I'm just an aged engineer moaning at having to learn new solutions to old problems.
100%. I’m really not sure why K8S has become the complexity boogeyman. I’ve seen CDK apps or docker compose files that are way more difficult to understand than the equivalent K8S manifests.
Docker Compose is simple: You have a Compose file that just needs Docker (or Podman).
With k8s you write a bunch of manifests that are 70% repetitive boilerplate. But actually, there is something you need that cannot be achieved with pure manifest, so you reach for Kustomize. But Kustomize actually doesn't do what you want, so you need to convert the entire thing to Helm.
You also still need to spin up your k8s cluster, which itself consists of half a dozen pods just so you have something where you can run your service. Oh, you wanted your service to be accessible from outside the cluster? Well, you need to install an ingress controller in your cluster. Oh BTW, the nginx ingress controller is now deprecated, so you have to choose from a handful of alternatives, all of which have certain advantages and disadvantages, and none of which are ideal for all situations. Have fun choosing.
But that's not what anyone is arguing here, nor what (to me it seems at least) uncloud is about. It's about simpler HA multinode setup with a single/low double digit containers.
If you already know k8s, this is probably true. If you don't it's hard to know what bits you need, and need to learn about, to get something simple set up.
I don't understand the point? You can say that about anything, and that's the whole reason why it's good that alternatives exist.
The clear target of this project is a k8s-like experience for people who are already familiar with Docker and docker compose but don't want to spend the energy to learn a whole new thing for low stakes deployments.
I really like what is on offer here - thank you for building it. Re the private network it builds with Wireguard, how are services running within this private network supposed to access AWS services such as RDS securely? Tailscale has this: https://tailscale.com/kb/1141/aws-rds
Totally valid concern. That was a shortcut to iterate quickly in early development. It’s time to do it properly now. Appreciate the feedback. This is exactly the kind of thing I need to hear before more people try it.
Very cool! I think I'll have some opportunity soon to give it a shot, I have just the set of projects that have been needing a tool like this. One thing I think I'm missing after perusing the docs however is, how does one onboard other engineers to the cluster after it has been set up? And similarly, how does deployment from a CI/CD runner work? I don't see anything about how to connect to an existing cluster from a new machine, or at least not that I'm recognizing.
There isn't a cli function for adding a connection (independently of adding a new machine/node) yet, but they are in a simple config file (`~/.config/uncloud/config.yaml`) that you can copy or easily create manually for now. It looks like this:
I took some inspiration from Kamal, e.g. the imperative model but kamal is more a deployment tool.
In addition to deployments, uncloud handles clustering - connects machines and containers together. Service containers can discover other services via internal DNS and communicate directly over the secure overlay network without opening any ports on the hosts.
As far as I know kamal doesn’t provide an easy way for services to communicate across machines.
Services can also be scaled to multiple replicas across machines.
Thanks! I noticed afterwards that you mention Kamal in your readme, but you may want to add a comparison section that you link to where you compare your solution to others.
Are you working on this full time and if so, how are you funding it? Are you looking to monetize this somehow?
I’m working full time on this, yes. Funding from my savings at the moment and don’t have plans for any external funding or VC.
For monetisation, considering building a self-hosted and managed (SaaS) webUI for managing remote clusters and apps on them with value-added PaaS-like features.
I don't know what the specific requirements for the distributed erlang/elixir but I believe the networking should support it. Containers get unique IPs on a WireGuard mesh with direct connectivity and DNS-based service discovery.
Thanks for the both great tools. just i didn't understand one thing ?
the request flow, imaging we have 10 servers where we choose this request goes to server 1 and the other goes to 7 for example. and since its zero down time, how it says server 5 is updating so till it gets up no request should go there.
I think there are two different cases here. Not sure which one you’re talking about.
1. External requests, e.g. from the internet via the reverse proxy (Caddy) running in the cluster.
The rollout works on the container, not the server level. Each container registers itself in Caddy so it knows which containers to forward and distribute requests to.
When doing a rollout, a new version of container is started first, registers in caddy, then the old one is removed. This is repeated for each service container. This way, at any time there are running containers that serve requests.
It doesn’t say any server that requests shouldn’t go there. It just updates upstreams in the caddy config to send requests to the containers that are up and healthy.
2. Service to service requests within the cluster. In this case, a service DNS name is resolved to a list of IP addresses (running containers). And the client decides which one to send a request to or whether to distribute requests among them.
When the service is updated, the client needs to resolve the name again to get the up-to-date list of IPs.
Many http clients handle this automatically so using http://service-name as an endpoint typically just works. But zero downtime should still be handled by the client in this case.
> - uses the familiar Docker Compose spec, no new DSL to learn
But this goes with assumption that one already know docker compose spec. For exact same reason I'm in love for `podman kube play` to just use k8s manifests to quickly test run on local machine - and not bother with some "legacy" compose.
(I never liked Docker Inc. so I never learned THEIR tooling, it's not needed to build/run containers)
Awesome tool! Does it provide some basic features that you would get from running a control plane.
Like rescheduling automatically a container on another server if a server is down? Deploying on the less filled server first if you have set limits in your containers?
There is no automatic rescheduling in uncloud by design. At least for now. We will see how far we can get without it.
If you want your service to tolerate a host going down, you should deploy multiple replicas for that service on multiple machines in advance. 'uc scale' command can be used to run more replicas for an already deployed service.
Regarding deploying on the less filled machine first is doable but not supported right now. By default, it picks the first machine randomly and tries to distributes replicas evenly among all available machines. You can also manually specify what target machine(s) each service should run on in your Compose file.
I want to avoid recreating the complexity with placement constraints, (anti-)affinity, etc. that makes K8s hard to reason about. There is a huge class of apps that need more or less static infra, manual placement, and a certain level of redundancy. That's what I'm targeting with Uncloud.
You have a graph that shows a multi provider setup for a domain. Where would routing to either machine happen? As in which ip would you use on the dns side?
For the public cluster with multiple ingress (caddy) nodes you'd need a load balancer in front of them to properly handle routing and outage of any of them. You'd use the IP of the load balancer on the DNS side.
Note that a DNS A record with multiple IPs doesn't provide failover, only round robin. But you can use the Cloudflare DNS proxy feature as a poor man's LB. Just add 2+ proxied A records (orange cloud) pointing to different machines. If one goes down with a 52x error, Cloudflare automatically fails over to the healthy one.
So you build an insecure version of nomad/kubernetes and co?
If you do anything professional, you better choose proven software like kubernetes or managed kubernetes or whatever else all the hyperscalers provide.
And the complexity you are solving now or have to solve, k8s solved. IaC for example, Cloud Provider Support for provisioning a LB out of the box, cert-manager, all the helm charts for observability, logging, a ecosystem to fall back to (operators), ArgoCD <3, storage provisioning, proper high availability, kind for e2e testing on cicd, etc.
I'm also aways lost why people think k8s is so hard to operate. Just take a managed k8s. There are so many options out there and they are all compatible with the whole k8s ecosystem.
Look if you don't get kubernetes, its use casees, advantages etc. fine absolutly fine but your solution is not an alternative to k8s. Its another container orchestrator like nomad and k8s and co. with it own advantages and disadvantages.
Neat, as you include quite a few tool for services to be reachable together (not necessarily to the outside), do you also have tooling to make those services more interoperable?
So it's a kind of better Docker Swarm? It's interesting, but honestly I'd rather have something declarative, so I can use it with Pulumi, would it be complicated to add a declarative engine on top of the tool? Which discovers what services are already up, do a diff with the new declaration, and handles changes?
The main difference with Docker Swarm is that the reconciliation process is run on your local/CI machine as part of the 'uc deploy' CLI command execution, not on the control plane nodes in the cluster.
And it's not running in the loop automatically. If the command fails, you get an instant feedback with the errors you can address or rerun the command again.
It should be pretty straightforward to wrap the CLI logic in a Terraform or Pulumi provider. The design principals are very similar and it's written in Go.
I'm no expert, so I'm not sure if I'll explain it correctly. But I've been using docker swarm in a server, I use traefik as reverse proxy, and it just doesn't seem to work (I've tried a lot) with ipv6 (issue that might be related https://github.com/moby/moby/issues/24379)
A really cool way to do it is how Yggdrasil project does it (https://yggdrasil-network.github.io/implementation.html#how-...). They basically use public keys as identities and they deterministically create an IPv6 address from the public key. This is beautiful and works for private networks, as well as for their global overlay IPv6 network.
What do you think about the general approach in Uncloud? It almost feels like a cousin of Swarm. Would love to get your take on it.
Having spent most of my career in kubernetes (usually managed by cloud), I always wonder when I see things like this, what is the use case or benefit of not having a control plane?
To me, the control plane is the primary feature of kubernetes and one I would not want to go without.
I know this describes operational overhead as a reason, but how it relates to the control plane is not clear to me. even managing a few hundred nodes and maybe 10,000 containers, relatively small - I update once a year and the managed cluster updates machine images and versions automatically. Are people trying to self host kubernetes for production cases, and that’s where this pain comes from?
Not rude at all. The benefit is a much simpler model where you simply connect machines in a network where every machine is equal. You can add more, remove some. No need to worry about an HA 3-node centralised “cluster brain”. There isn’t one.
It’s a similar experience when a cloud provider manages the control plane for you. But you have to worry about the availability when you host everything yourself. Losing etcd quorum results in an unusable cluster.
Many people want to avoid this, especially when running at a smaller scale like a handful of machines.
The cluster network can even partition and each partition continues to operate allowing to deploy/update apps individually.
That’s essentially what we all did in a pre-k8s era with chef and ansible but without the boilerplate and reinventing the wheel, and using the learnings from k8s and friends.
If you are a small operation and trying to self host k3s or k8s or any number of out of the box installations that are probably at least as complex as docker compose swarms, for any non trivial production case, presents similar problems in monitoring and availability as ones you’d get with off the shelf cloud provider managed services, except the managed solutions come without the pain in the ass. Except you don’t have a control plane.
I have managed custom server clusters in a self hosted situation. the problems are hard, but if you’re small, why would you reach for such a solution in the first place? you’d be better off paying for a managed service. What situation forces so many people to reach to self hosted kubernetes?
This thread is about using multi-machine clusters, and sqlite cannot be used for multi-machine clusters in k3s. etcd is the default when starting k3s in cluster mode [1].
> a few hundred nodes and maybe 10,000 containers, relatively small
That feels not small to me. For something I'm working on I'll probably have two nodes and around 10 containers. If it works out and I get some growth, maybe that will go up to, say, 5-7 nodes and 30 or so containers? I dunno. I'd like some orchestration there, but k8s feels way too heavy even for my "grown" case.
I feel like there are potentially a lot of small businesses at this sort of scale?
Of course they are…? That’s half the point of k8s - if you want to self host, you can, but it’s just like backups: if you never try it, you should assume you can’t do it when you need to
On cloud, in my experience, you are mostly paying for compute with managed kubernetes instances. The overhead and price is almost never kubernetes itself, but the compute and storage you are provisioning, which, thanks to the control plane, you have complete control over. what am i missing?
I wouldn’t dare try to with a small shop try to self host a production kubernetes solution unless i was under duress. But I just dont see what the control plane has to do with it. It’s the feature that makes kubernetes worth it.
Nomad still has a tangible learning curve, which (in my very biased opinion) is almost non-existent with Uncloud assuming the user has already heard about Docker and Compose.
They had quite a few release in the last year so it's not dead that's for sure, but unclear how many new customers they are able to sign up. And with IBM in charge, it's also unclear at what moment they will loose interest.
Very cool, so sort of like Dokku but simpler/easier to use?
Looks like the docs assume the management of a single cluster. What if you want to manage multiple/distinct clusters from the same uc client/management env?
> What if you want to manage multiple/distinct clusters
Uncloud supports having multiple contexts (think - clusters) in the same configuration file, or you can also use separate config files (via --uncloud-config attribute).
I know just enough about Kubernetes to not sound like an idiot when I’m in the room and mostly I deploy Docker containers to various managed services on AWS - Lambda, ECS, etc.
But, as a lead for implementations, I just couldn’t in good conscience permit something that is not an industry standard and not supported by my cloud provider. First from a self interested standpoint, it looks a lot better on their resume to say “I did $x using K8s”.
From an onboarding standpoint, just telling a new employee “we use K8s -here you go” means nothing new to learn.
If you are part of the industry, just suck it up and learn Kubernetes. Your future self won’t regret it - coming from someone who in fact has not learn K8s.
This is a challenge any new framework is going to have.
Fair points on the career and onboarding angle. It’s hard to argue against "everyone knows it".
But with that mentality, we'd never challenge anything. COBOL was the industry standard once. So were bare metal servers or fat VMs without containers. Someone had to say "this is more painful than it needs to be and I want to try something different because I can".
I know how to use k8s but I really don't enjoy it. It feels so distasteful to me that it triggered me to make an attempt at designing a nicer experience, because why not. I remember how much fun I had trying Docker when it first came out. That inspires me to at least try. It doesn't seem like the k8s community is even trying unfortunately.
The enterprise equivalent of COBOL today is Java and to a much lesser extent C#. Those were both championed by large corporations - Sun and Microsoft.
The move to VMs at first and then to the cloud were also marketed by existing companies with huge budgets where people who made decisions had the “No one ever got fired for choosing $LargeWellknownCompany that is in the upper right corner of Gartner’s Magic Square”.
I love Docker. I think everyone going to EKS before they need to is dumb. There are dozens of services out there that let you give it a Docker container and just run it.
And I think that spending energy avoiding “cloud lock-in” is dumb. Choose your infrastructure and build. Migrations are going to be a pain at any decent scale anyway and you are optimizing for the wrong thing if you are worried about lock in.
As an individual especially in today’s market, it’s foolish (not referring to you - any developer or adjacent) not to always be thinking of what keeps you the most employable if the rug gets pulled from under you.
As a decision maker who is held accountable for architecture and when things go wrong they look at or when the next person has to come along to maintain it, they are going to look at me like I am crazy if I choose a non industry standard solution just because I was too lazy to choose the industry standard.
Again I don’t mean that you are being “lazy”. That’s how people think.
But if I were hiring someone - and I’m often interviewing people for cloudy/devOps type roles. Why would I hire someone with experience with a Docker orchestration framework I never heard of over someone who knew K8s?
And the final question you should ask yourself is why are you really doing this?
Is it to scratch an itch out of passion and it’s something that you feel the world should have? If so in all sincerity, I wish you luck on your endeavor. You might get lucky like Bun just did. I had effusive praise for them doing something out of passion instead of as VC bait.
Are you doing it for financial gain? If so, you have to come up with a strategy to overcome resistance from people like Ive outlined.
Does it support a way to bundle things close to each other, for example, not having a database container hosted in a different datacenter than the web app?
The `compose.yaml` spec for services let's you specify which machines to deploy it on, so you could target the database and web app to the same machine (or subset of machines).
There is also an internal DNS for service discovery and it supports a `nearest.` prefix, which will preferentially use instances of a service running on the same machine. For example, I run a globally replicated NATS service and then connect to it from other services using the `nearest.nats.internal` address to connect to the machine-local NATS node.
This is extremely interesting to me. I've been using docker swarm, but there is this growing feeling of staleness. Dokku feels a bit too light, K8 absolutely too heavy. This proposition strikes my sweet spot - especially the part where I keep my existing docker compose declarations
Come join our cozy Discord server https://uncloud.run/discord. There is one guy joined recently who is migrating his homelab setup from Swarm right now.
It supports docker swarm, but I've never used it like that.
As I may need multi node in the future, I was asking the question to see if it would make it 'easy' to orchestrate multiple containers.
The simplicity of Dokku is hard to beat, however.
edit: Well, it would appear that the very maintainer of Dokku himself replied to the parent comment. My information is clearly outdated and I'd only look at this comment[0] to get the proper info.
Dokku is multi node. It supports docker-local (single node) and k3s (multi-node) as schedulers, with most features implemented as expected when deploying to k3s.
Uncloud is not a Kubernetes distribution and doesn't use K8s primitives (although there are of course some similarities). It's closer to Compose/Swarm in how you declare and manage your services. Which has pros and cons depending on what you need and what your (or your team's) experience with Kubernetes is.
Uncloud is lower-level. Dokploy seems to be positioning as a PaaS with a web UI using Docker Swarm under the hood for multi-node container management. Uncloud operates at that same layer as Swarm but with a simpler operating model that's friendlier for troubleshooting, WireGuard mesh networking built in, and the ability to connect nodes from different clouds or locations.
No UI yet (planned) so if that's critical, Dokploy is likely a better choice for now.
However, some unique features like building and pushing images directly to your nodes without an external registry give Uncloud a PaaS-like feel, just CLI-first. Really depends on what you're hosting and what you're optimising for.
Hey, creator here. Thanks for sharing this!
Uncloud[0] is a container orchestrator without a control plane. Think multi-machine Docker Compose with automatic WireGuard mesh, service discovery, and HTTPS via Caddy. Each machine just keeps a p2p-synced copy of cluster state (using Fly.io's Corrosion), so there's no quorum to maintain.
I’m building Uncloud after years of managing Kubernetes in small envs and at a unicorn. I keep seeing teams reach for K8s when they really just need to run a bunch of containers across a few machines with decent networking, rollouts, and HTTPS. The operational overhead of k8s is brutal for what they actually need.
A few things that make it unique:
- uses the familiar Docker Compose spec, no new DSL to learn
- builds and pushes your Docker images directly to your machines without an external registry (via my other project unregistry [1])
- imperative CLI (like Docker) rather than declarative reconciliation. Easier mental model and debugging
- works across cloud VMs, bare metal, even a Raspberry Pi at home behind NAT (all connected together)
- minimal resource footprint (<150MB ram)
[0]: https://github.com/psviderski/uncloud
[1]: https://github.com/psviderski/unregistry
"I keep seeing teams reach for K8s when they really just need to run a bunch of containers across a few machines"
Since k8s is very effective at running a bunch of containers across a few machines, it would appear to be exactly the correct thing to reach for. At this point, running a small k8s operation, with k3s or similar, has become so easy that I can't find a rational reason to look elsewhere for container "orchestration".
I can only speak for myself, but I considered a few options, including "simple k8s" like [Skate](https://skateco.github.io/), and ultimately decided to build on uncloud.
It was as much personal "taste" than anything, and I would describe the choice as similar to preferring JSON over XML.
For whatever reason, kubernetes just irritates me. I find it unpleasant to use. And I don't think I'm unique in that regard.
> For whatever reason, kubernetes just irritates me. I find it unpleasant to use. And I don't think I'm unique in that regard.
I feel the same. I feel like it's a me problem. I was able to build and run massive systems at scale and never used kubernetes. Then, all of a sudden, around 2020, any time I wanted to build or run or do anything at scale, everywhere said I should just use kubernetes. And then when I wanted to do anything with docker in production, not even at scale, everywhere said I should just use kubernetes.
Then there was a brief period around 2021 where everyone - even kubernetes fans - realised it was being used everywhere, even when it didn't need to be. "You don't need k8s" became a meme.
And now, here we are, again, lots of people saying "just use k8s for everything".
I've learned it enough to know how to use it and what I can do with it. I still prefer to use literally anything else apart from k8s when building, and the only time I've ever felt k8s has been really needed to solve a problem is when the business has said "we're using k8s, deal with it".
It's like the Javascript or WordPress of the infrastructure engineering world - it became the lazy answer, IMO. Or the me problem angle: I'm just an aged engineer moaning at having to learn new solutions to old problems.
100%. I’m really not sure why K8S has become the complexity boogeyman. I’ve seen CDK apps or docker compose files that are way more difficult to understand than the equivalent K8S manifests.
Docker Compose is simple: You have a Compose file that just needs Docker (or Podman).
With k8s you write a bunch of manifests that are 70% repetitive boilerplate. But actually, there is something you need that cannot be achieved with pure manifest, so you reach for Kustomize. But Kustomize actually doesn't do what you want, so you need to convert the entire thing to Helm.
You also still need to spin up your k8s cluster, which itself consists of half a dozen pods just so you have something where you can run your service. Oh, you wanted your service to be accessible from outside the cluster? Well, you need to install an ingress controller in your cluster. Oh BTW, the nginx ingress controller is now deprecated, so you have to choose from a handful of alternatives, all of which have certain advantages and disadvantages, and none of which are ideal for all situations. Have fun choosing.
Managing hundreds or thousands of containers across hundreds or thousands of k8s nodes has a lot of operational challenges.
Especially in-house on bare metal.
But that's not what anyone is arguing here, nor what (to me it seems at least) uncloud is about. It's about simpler HA multinode setup with a single/low double digit containers.
Which is fine because it absolutly matches the result.
You would not be able to operate hundreds or thousand of any nodes without operation complexlity and k8s helps you here a lot.
Talos has made this super easy in my experience.
I don't think that argument matches with they "just need to run a bunch of containers across a few machines"
That’s awesome if k3s works for you, nothing wrong with this. You’re simply not the target user then.
If you already know k8s, this is probably true. If you don't it's hard to know what bits you need, and need to learn about, to get something simple set up.
you could say that about anything…
I don't understand the point? You can say that about anything, and that's the whole reason why it's good that alternatives exist.
The clear target of this project is a k8s-like experience for people who are already familiar with Docker and docker compose but don't want to spend the energy to learn a whole new thing for low stakes deployments.
Uncloud is so far away from k8s, its not k8s like.
A normal person wouldn't think 'hey lets use k8s for the low stakes deployment over here'.
Indeed, it seems a knee jerk response without justification. k3s is pretty damn minimal.
I really like what is on offer here - thank you for building it. Re the private network it builds with Wireguard, how are services running within this private network supposed to access AWS services such as RDS securely? Tailscale has this: https://tailscale.com/kb/1141/aws-rds
This is a cool tool, I like the idea. But the way `uc machine init` works under the hood is really scary. Lot's of `curl | bash` run as root.
While I would love to test this tool, this is not something I would run on any machine :/
+1 on this
I wanted to try it out but was put off by this[0]. It’s just straight up curl | bash as root from raw.githubusercontent.com.
If this is the install process for a server (and not just for the CLI) I don’t want to think about security in general for the product.
Sorry, I really wanted to like this, but pass.
[0] https://github.com/psviderski/uncloud/blob/ebd4622592bcecedb...
Totally valid concern. That was a shortcut to iterate quickly in early development. It’s time to do it properly now. Appreciate the feedback. This is exactly the kind of thing I need to hear before more people try it.
Curious, what would be an ideal (secure) approach for you to install this (or similar) tool?
It's deploying a script, which then downloads uncloud using curl.
The alternative is, deploying the script and with it have the uncloud files it needs.
Very cool! I think I'll have some opportunity soon to give it a shot, I have just the set of projects that have been needing a tool like this. One thing I think I'm missing after perusing the docs however is, how does one onboard other engineers to the cluster after it has been set up? And similarly, how does deployment from a CI/CD runner work? I don't see anything about how to connect to an existing cluster from a new machine, or at least not that I'm recognizing.
There isn't a cli function for adding a connection (independently of adding a new machine/node) yet, but they are in a simple config file (`~/.config/uncloud/config.yaml`) that you can copy or easily create manually for now. It looks like this:
And you really just need one entry for typical use. The subsequent entries are only used if the previous node(s) are down.For CI/CD, check out this GitHub Action: https://github.com/thatskyapplication/uncloud-action.
You can either specify one of the machine SSH target in the config.yaml or pass it directly to the 'uc' CLI command, e.g.
uc --connect user@host deploy
How's this similar to and different from Kamal? https://kamal-deploy.org/
I took some inspiration from Kamal, e.g. the imperative model but kamal is more a deployment tool.
In addition to deployments, uncloud handles clustering - connects machines and containers together. Service containers can discover other services via internal DNS and communicate directly over the secure overlay network without opening any ports on the hosts.
As far as I know kamal doesn’t provide an easy way for services to communicate across machines.
Services can also be scaled to multiple replicas across machines.
Thanks! I noticed afterwards that you mention Kamal in your readme, but you may want to add a comparison section that you link to where you compare your solution to others.
Are you working on this full time and if so, how are you funding it? Are you looking to monetize this somehow?
Thank you for the suggestion!
I’m working full time on this, yes. Funding from my savings at the moment and don’t have plans for any external funding or VC.
For monetisation, considering building a self-hosted and managed (SaaS) webUI for managing remote clusters and apps on them with value-added PaaS-like features.
That sounds interesting, maybe I could help on the business side of things somehow. I'll email you my calendar link.
Awesome, will reach out!
This is neat, regarding clustering - can this work with distributed erlang/elixir?
I don't know what the specific requirements for the distributed erlang/elixir but I believe the networking should support it. Containers get unique IPs on a WireGuard mesh with direct connectivity and DNS-based service discovery.
Thanks for the both great tools. just i didn't understand one thing ? the request flow, imaging we have 10 servers where we choose this request goes to server 1 and the other goes to 7 for example. and since its zero down time, how it says server 5 is updating so till it gets up no request should go there.
I think there are two different cases here. Not sure which one you’re talking about.
1. External requests, e.g. from the internet via the reverse proxy (Caddy) running in the cluster.
The rollout works on the container, not the server level. Each container registers itself in Caddy so it knows which containers to forward and distribute requests to.
When doing a rollout, a new version of container is started first, registers in caddy, then the old one is removed. This is repeated for each service container. This way, at any time there are running containers that serve requests.
It doesn’t say any server that requests shouldn’t go there. It just updates upstreams in the caddy config to send requests to the containers that are up and healthy.
2. Service to service requests within the cluster. In this case, a service DNS name is resolved to a list of IP addresses (running containers). And the client decides which one to send a request to or whether to distribute requests among them.
When the service is updated, the client needs to resolve the name again to get the up-to-date list of IPs. Many http clients handle this automatically so using http://service-name as an endpoint typically just works. But zero downtime should still be handled by the client in this case.
> - uses the familiar Docker Compose spec, no new DSL to learn
But this goes with assumption that one already know docker compose spec. For exact same reason I'm in love for `podman kube play` to just use k8s manifests to quickly test run on local machine - and not bother with some "legacy" compose.
(I never liked Docker Inc. so I never learned THEIR tooling, it's not needed to build/run containers)
podman-compose works fine. It’s a very simple format.
Awesome tool! Does it provide some basic features that you would get from running a control plane.
Like rescheduling automatically a container on another server if a server is down? Deploying on the less filled server first if you have set limits in your containers?
Thank you! That's actually the trade off.
There is no automatic rescheduling in uncloud by design. At least for now. We will see how far we can get without it.
If you want your service to tolerate a host going down, you should deploy multiple replicas for that service on multiple machines in advance. 'uc scale' command can be used to run more replicas for an already deployed service.
Longer term, I'm thinking we can have a concept of primary/standby replicas for services that can only have one running replica, e.g. databases. Something similar to how Fly.io does this: https://fly.io/docs/apps/app-availability/#standby-machines-...
Regarding deploying on the less filled machine first is doable but not supported right now. By default, it picks the first machine randomly and tries to distributes replicas evenly among all available machines. You can also manually specify what target machine(s) each service should run on in your Compose file.
I want to avoid recreating the complexity with placement constraints, (anti-)affinity, etc. that makes K8s hard to reason about. There is a huge class of apps that need more or less static infra, manual placement, and a certain level of redundancy. That's what I'm targeting with Uncloud.
You have a graph that shows a multi provider setup for a domain. Where would routing to either machine happen? As in which ip would you use on the dns side?
For the public cluster with multiple ingress (caddy) nodes you'd need a load balancer in front of them to properly handle routing and outage of any of them. You'd use the IP of the load balancer on the DNS side.
Note that a DNS A record with multiple IPs doesn't provide failover, only round robin. But you can use the Cloudflare DNS proxy feature as a poor man's LB. Just add 2+ proxied A records (orange cloud) pointing to different machines. If one goes down with a 52x error, Cloudflare automatically fails over to the healthy one.
Not OP, but you could do "simple" dns load balancing between both endpoints.
So you build an insecure version of nomad/kubernetes and co?
If you do anything professional, you better choose proven software like kubernetes or managed kubernetes or whatever else all the hyperscalers provide.
And the complexity you are solving now or have to solve, k8s solved. IaC for example, Cloud Provider Support for provisioning a LB out of the box, cert-manager, all the helm charts for observability, logging, a ecosystem to fall back to (operators), ArgoCD <3, storage provisioning, proper high availability, kind for e2e testing on cicd, etc.
I'm also aways lost why people think k8s is so hard to operate. Just take a managed k8s. There are so many options out there and they are all compatible with the whole k8s ecosystem.
Look if you don't get kubernetes, its use casees, advantages etc. fine absolutly fine but your solution is not an alternative to k8s. Its another container orchestrator like nomad and k8s and co. with it own advantages and disadvantages.
Neat, as you include quite a few tool for services to be reachable together (not necessarily to the outside), do you also have tooling to make those services more interoperable?
Do you have an example of what you mean? I'm not entirely clear on your question.
So it's a kind of better Docker Swarm? It's interesting, but honestly I'd rather have something declarative, so I can use it with Pulumi, would it be complicated to add a declarative engine on top of the tool? Which discovers what services are already up, do a diff with the new declaration, and handles changes?
This is exactly how it works now. The Compose file is the declarative specification of your services you want to run.
When you run 'uc deploy' command:
- it reads the spec from your compose.yaml
- inspects the current state of the services in the cluster
- computes the diff and deployment plan to reconcile it
- executes the plan after the confirmation
Please see the docs and demo: https://uncloud.run/docs/guides/deployments/deploy-app
The main difference with Docker Swarm is that the reconciliation process is run on your local/CI machine as part of the 'uc deploy' CLI command execution, not on the control plane nodes in the cluster.
And it's not running in the loop automatically. If the command fails, you get an instant feedback with the errors you can address or rerun the command again.
It should be pretty straightforward to wrap the CLI logic in a Terraform or Pulumi provider. The design principals are very similar and it's written in Go.
does it support ipv6?
There is an open issue that confirms enabling ipv6 for containers works: https://github.com/psviderski/uncloud/issues/126 But this hasn’t been enabled by default.
What specifically do you mean by ipv6 support?
I'm no expert, so I'm not sure if I'll explain it correctly. But I've been using docker swarm in a server, I use traefik as reverse proxy, and it just doesn't seem to work (I've tried a lot) with ipv6 (issue that might be related https://github.com/moby/moby/issues/24379)
> What specifically do you mean by ipv6 support?
This question does not make sense. This is equivalent to asking "What specifically do you mean by ipv4 support"
These days both protocols must be supported, and if there is a blocker it should be clearly mentioned.
How do you want to allocate ipv6 addresses to containers? Turns out there are lots of answers. Some people even want to do ipv6 NAT.
A really cool way to do it is how Yggdrasil project does it (https://yggdrasil-network.github.io/implementation.html#how-...). They basically use public keys as identities and they deterministically create an IPv6 address from the public key. This is beautiful and works for private networks, as well as for their global overlay IPv6 network.
What do you think about the general approach in Uncloud? It almost feels like a cousin of Swarm. Would love to get your take on it.
haha, uncloud does have a control plane: the mind of the person running "uc" CLI commands
> I’m building Uncloud after years of managing Kubernetes
did you manage Kubernetes, or did you make the fateful mistake of managing microk8s?
Having spent most of my career in kubernetes (usually managed by cloud), I always wonder when I see things like this, what is the use case or benefit of not having a control plane?
To me, the control plane is the primary feature of kubernetes and one I would not want to go without.
I know this describes operational overhead as a reason, but how it relates to the control plane is not clear to me. even managing a few hundred nodes and maybe 10,000 containers, relatively small - I update once a year and the managed cluster updates machine images and versions automatically. Are people trying to self host kubernetes for production cases, and that’s where this pain comes from?
Sorry if it is a rude question.
Not rude at all. The benefit is a much simpler model where you simply connect machines in a network where every machine is equal. You can add more, remove some. No need to worry about an HA 3-node centralised “cluster brain”. There isn’t one.
It’s a similar experience when a cloud provider manages the control plane for you. But you have to worry about the availability when you host everything yourself. Losing etcd quorum results in an unusable cluster.
Many people want to avoid this, especially when running at a smaller scale like a handful of machines.
The cluster network can even partition and each partition continues to operate allowing to deploy/update apps individually.
That’s essentially what we all did in a pre-k8s era with chef and ansible but without the boilerplate and reinventing the wheel, and using the learnings from k8s and friends.
If you are a small operation and trying to self host k3s or k8s or any number of out of the box installations that are probably at least as complex as docker compose swarms, for any non trivial production case, presents similar problems in monitoring and availability as ones you’d get with off the shelf cloud provider managed services, except the managed solutions come without the pain in the ass. Except you don’t have a control plane.
I have managed custom server clusters in a self hosted situation. the problems are hard, but if you’re small, why would you reach for such a solution in the first place? you’d be better off paying for a managed service. What situation forces so many people to reach to self hosted kubernetes?
k3s uses sqlite, so not etcd.
It can use sqlite (single master), or for cluster it can use pg, or mysql, but etcd by default
No, it's not. Read the docs[1] - sqlite is the default.
"Lightweight datastore based on sqlite3 as the default storage backend. etcd3, MySQL, and Postgres are also available."
[1]https://docs.k3s.io/
This thread is about using multi-machine clusters, and sqlite cannot be used for multi-machine clusters in k3s. etcd is the default when starting k3s in cluster mode [1].
[1] https://docs.k3s.io/datastore
> a few hundred nodes and maybe 10,000 containers, relatively small
That feels not small to me. For something I'm working on I'll probably have two nodes and around 10 containers. If it works out and I get some growth, maybe that will go up to, say, 5-7 nodes and 30 or so containers? I dunno. I'd like some orchestration there, but k8s feels way too heavy even for my "grown" case.
I feel like there are potentially a lot of small businesses at this sort of scale?
> Are people trying to self host kubernetes
Of course they are…? That’s half the point of k8s - if you want to self host, you can, but it’s just like backups: if you never try it, you should assume you can’t do it when you need to
Kubernetes is not only an orchestrator but a scheduler.
Is a way to run arbitrary processes on a bunch of servers.
But what if your processes are known beforehand? Than you don't need a scheduler, nor an orchestrator.
If it's just your web app with two containers and nothing more?
Try it on bare metal where you're managing the distributed storage and the hardware and the network and the upgrades too :)
Why would you want to do that though?
On cloud, in my experience, you are mostly paying for compute with managed kubernetes instances. The overhead and price is almost never kubernetes itself, but the compute and storage you are provisioning, which, thanks to the control plane, you have complete control over. what am i missing?
I wouldn’t dare try to with a small shop try to self host a production kubernetes solution unless i was under duress. But I just dont see what the control plane has to do with it. It’s the feature that makes kubernetes worth it.
Tinkerbell / MetalKube, ClusterAPI, Rook, Cilium?
A control plane makes controlling machines easier, that's the point of a control plane.
If not K8S, why not Nomad (https://github.com/hashicorp/nomad)?
Nomad still has a tangible learning curve, which (in my very biased opinion) is almost non-existent with Uncloud assuming the user has already heard about Docker and Compose.
Nomad is great, but you will still end up with a control plane.
Isn't Nomad pretty much dead now?
They had quite a few release in the last year so it's not dead that's for sure, but unclear how many new customers they are able to sign up. And with IBM in charge, it's also unclear at what moment they will loose interest.
Very cool, so sort of like Dokku but simpler/easier to use?
Looks like the docs assume the management of a single cluster. What if you want to manage multiple/distinct clusters from the same uc client/management env?
> What if you want to manage multiple/distinct clusters
Uncloud supports having multiple contexts (think - clusters) in the same configuration file, or you can also use separate config files (via --uncloud-config attribute).
https://uncloud.run/docs/cli-reference/uc_ctx
Very nice!
This would have been my choice had it existed three months ago. Now it feels like I learned kubernetes in vain xD
really need to disclose the status of this application. It's ridiculous to pipe curl | bash in the actual code.
Gonna burn bridges with this lack of transparency. I love the intent but the implementation is so bad that I probably wont look back.
I know just enough about Kubernetes to not sound like an idiot when I’m in the room and mostly I deploy Docker containers to various managed services on AWS - Lambda, ECS, etc.
But, as a lead for implementations, I just couldn’t in good conscience permit something that is not an industry standard and not supported by my cloud provider. First from a self interested standpoint, it looks a lot better on their resume to say “I did $x using K8s”.
From an onboarding standpoint, just telling a new employee “we use K8s -here you go” means nothing new to learn.
If you are part of the industry, just suck it up and learn Kubernetes. Your future self won’t regret it - coming from someone who in fact has not learn K8s.
This is a challenge any new framework is going to have.
Fair points on the career and onboarding angle. It’s hard to argue against "everyone knows it". But with that mentality, we'd never challenge anything. COBOL was the industry standard once. So were bare metal servers or fat VMs without containers. Someone had to say "this is more painful than it needs to be and I want to try something different because I can".
I know how to use k8s but I really don't enjoy it. It feels so distasteful to me that it triggered me to make an attempt at designing a nicer experience, because why not. I remember how much fun I had trying Docker when it first came out. That inspires me to at least try. It doesn't seem like the k8s community is even trying unfortunately.
The enterprise equivalent of COBOL today is Java and to a much lesser extent C#. Those were both championed by large corporations - Sun and Microsoft.
The move to VMs at first and then to the cloud were also marketed by existing companies with huge budgets where people who made decisions had the “No one ever got fired for choosing $LargeWellknownCompany that is in the upper right corner of Gartner’s Magic Square”.
I love Docker. I think everyone going to EKS before they need to is dumb. There are dozens of services out there that let you give it a Docker container and just run it.
And I think that spending energy avoiding “cloud lock-in” is dumb. Choose your infrastructure and build. Migrations are going to be a pain at any decent scale anyway and you are optimizing for the wrong thing if you are worried about lock in.
As an individual especially in today’s market, it’s foolish (not referring to you - any developer or adjacent) not to always be thinking of what keeps you the most employable if the rug gets pulled from under you.
As a decision maker who is held accountable for architecture and when things go wrong they look at or when the next person has to come along to maintain it, they are going to look at me like I am crazy if I choose a non industry standard solution just because I was too lazy to choose the industry standard.
Again I don’t mean that you are being “lazy”. That’s how people think.
But if I were hiring someone - and I’m often interviewing people for cloudy/devOps type roles. Why would I hire someone with experience with a Docker orchestration framework I never heard of over someone who knew K8s?
And the final question you should ask yourself is why are you really doing this?
Is it to scratch an itch out of passion and it’s something that you feel the world should have? If so in all sincerity, I wish you luck on your endeavor. You might get lucky like Bun just did. I had effusive praise for them doing something out of passion instead of as VC bait.
Are you doing it for financial gain? If so, you have to come up with a strategy to overcome resistance from people like Ive outlined.
Does it support a way to bundle things close to each other, for example, not having a database container hosted in a different datacenter than the web app?
The `compose.yaml` spec for services let's you specify which machines to deploy it on, so you could target the database and web app to the same machine (or subset of machines).
There is also an internal DNS for service discovery and it supports a `nearest.` prefix, which will preferentially use instances of a service running on the same machine. For example, I run a globally replicated NATS service and then connect to it from other services using the `nearest.nats.internal` address to connect to the machine-local NATS node.
This is extremely interesting to me. I've been using docker swarm, but there is this growing feeling of staleness. Dokku feels a bit too light, K8 absolutely too heavy. This proposition strikes my sweet spot - especially the part where I keep my existing docker compose declarations
Come join our cozy Discord server https://uncloud.run/discord. There is one guy joined recently who is migrating his homelab setup from Swarm right now.
Also another community member shared his homelab with a couple dozen services migrated from Docker Compose to Uncloud: https://github.com/dasunsrule32/docker-compose-configs/tree/...
As a happy user of coolify, what’s the difference between these two?
Even coolify lets you add as many machines as you want and then manage docker containers in all machines from one coolify installation.
Vendor lock-in, Kubernetes is future proof.
Wow this looks really cool. Congratulations!
How does this compare to something like Dokku?
Is dokku multi node?
It supports docker swarm, but I've never used it like that. As I may need multi node in the future, I was asking the question to see if it would make it 'easy' to orchestrate multiple containers. The simplicity of Dokku is hard to beat, however.
edit: Well, it would appear that the very maintainer of Dokku himself replied to the parent comment. My information is clearly outdated and I'd only look at this comment[0] to get the proper info.
[0] https://news.ycombinator.com/item?id=46144275#46145919
Dokku is multi node. It supports docker-local (single node) and k3s (multi-node) as schedulers, with most features implemented as expected when deploying to k3s.
How does this compare to k3s?
Uncloud is not a Kubernetes distribution and doesn't use K8s primitives (although there are of course some similarities). It's closer to Compose/Swarm in how you declare and manage your services. Which has pros and cons depending on what you need and what your (or your team's) experience with Kubernetes is.
Looks lovely.. I'll definitely will give it a try when time comes.
I'm using Dokploy, would that be very similar, or quite different?
Uncloud is lower-level. Dokploy seems to be positioning as a PaaS with a web UI using Docker Swarm under the hood for multi-node container management. Uncloud operates at that same layer as Swarm but with a simpler operating model that's friendlier for troubleshooting, WireGuard mesh networking built in, and the ability to connect nodes from different clouds or locations.
No UI yet (planned) so if that's critical, Dokploy is likely a better choice for now.
However, some unique features like building and pushing images directly to your nodes without an external registry give Uncloud a PaaS-like feel, just CLI-first. Really depends on what you're hosting and what you're optimising for.
See short deploy demo: https://uncloud.run/docs/guides/deployments/deploy-app
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