Uncloud is a bit lower-level, CLI-only (for now), with no central server. If some nodes go offline, the rest keep working and stay manageable.
It also has the WireGuard overlay networking built in so containers across machines get direct connectivity without having to map ports to the host. For example, securely access a database running on another machine. This also allows you to horizontally scale your services to multiple replicas on different machines and distribute traffic between them with minimal configuration.
The current state of Uncloud is the primitives and foundation that could be used to build a more higher-level PaaS-like solution such as Coolify.
>with swarm and traefik, I can define url rewrite rules as container labels. Is something equivalent available?
Yep, you define the mapping between the domain name and the internal container port as `x-ports: app.example.com:8000/https` in the compose file. Or you can specify a custom Caddy config for the service as `x-caddy: Caddyfile` which allows to customise it however you like. See https://uncloud.run/docs/concepts/ingress/publishing-service...
>if I deploy 2 compose 'stacks', do all containers have access to all other containers, even in the other stack?
Yes, there is no network isolation between containers from different services/stacks at the moment. Here is an open discussion on stack/namespace/environment/project concepts and isolation: https://github.com/psviderski/uncloud/discussions/94.
What's your use case and how would you want this to behave?
I like that I can put my containers to be exposed on the traefik-public network, and keep others like databases unreachable from traefik. This organisation of networks is very useful, allowing to make containers reachable across stacks, but also to keep some containers in a stack reachable only from other containers on the same network in that same stack.
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.
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.
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.
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?
Yes, not everyone is allowed to use cloud services. There's also the cost. I haven't spent a cent on infrastructure in 5 years (other than my time). Using cloud services comes with extra costs and meetings to justify those costs. Plus, not everyone is in the USA or 1st world country where those costs are negligible. Necessity is the mother of invention.
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].
No, this thread is about multiple containers across machines. What you describe is multi-master for the server. You can run multple agents across serveral nodes therefore clustering the container workload across multiple container hosting servers. Multi-master is something different.
The very first paragraph of the first comment you replied to is about multi-master HA. The second sentence in that comment is about “every machine is equal”. k3s with sqlite is awesome, but it cannot do that.
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.
How many flawless, painless major version upgrades have you had with literally any flavor of k8s? Because in my experience, that’s always a science experiment that results in such pain people end up just sticking at their original deployed version while praying they don’t hit any critical bugs or security vulnerabilities.
I’ve run Kubernetes since 2018 and I can count on one hand the times there were major issues with an upgrade. Have sensible change management and read the release notes for breaking changes. The amount of breaking changes has also gone way down in recent years.
Same. I think maybe twice in that time frame we've had a breaking change, and those did warn us for several versions. Typically the only "fix" we need to apply is changing the API version on objects that have matured beyond beta.
I applaud you for having a specific complaint. 'You might not need it' 'its complex' and 'for some reason it bothers me' are all these vibes based winges that are so abundant. But with nothing specific, nothing contestable.
My home lab has grown over the years, now consisting of a physical Proxmox cluster, and a handful of servers (RaspPi and micro hosts).
A couple years back I got tired of failures related to host-level Docker issues, so I got a NAS and started using NAS storage for everything I could.
I also re-investigated containerization - weighing Docker Swarm vs K3s - and settled on Docker Swarm.
I’ve hated it ever since. Swarm is a PITA to use and has all kinds of failure modes that are different than regular old Docker Compose.
I’ve considered migrating again - either to Kubernetes, or just back to plain Docker - but haven’t done it. Maybe I should look at Uncloud?
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.
Literally got it in one, here. I’m not knocking Kubernetes, mind, and I don’t think anyone here is, not even the project author. Rather, we’re saying that the excess of K8s can sometimes get in the way of simpler deployments. Even streamlined Kubernetes (microk8s, k3s, etc) still ultimately bring all of Kubernetes to the table, and that invites complexity when the goal is simplicity.
That’s not bad, but I want to spend more time trying new things or enjoying the results of my efforts than maintaining the underlying substrates. For that purpose, K8s is consistently too complicated for my own ends - and Uncloud looks to do exactly what I want.
> Docker Compose is simple: You have a Compose file that just needs Docker (or Podman).
And if you want to use more than one machine then you run `docker swarm init`, and you can keep using the Compose file you already have, almost unchanged.
It's not a K8s replacement, but I'm guessing for some people it would be enough and less effort than a full migration to Kubernetes (e.g. hobby projects).
This is some serious rose colored glasses happening here.
If you have a service with a simple compose file, you can have a simple k8s manifest to do the same thing. Plenty of tools convert right between the two (incl kompose, which k8s literally hands you: https://kubernetes.io/docs/tasks/configure-pod-container/tra...)
Frankly, you're messing up by including kustomize or helm at all in 80% of cases. Just write the (agreed on tedious boilerplate - the manifest format is not my cup of tea) yaml and be done with the problem.
And no - you don't need an ingress. Just spin up a nodeport service, and you have the literal identical experience to exposing ports with compose - it's just a port on the machines running the cluster (any of them - magic!).
You don't need to touch an ingress until you actually want external traffic using a specific hostname (and optionally tls), which is... the same as compose. And frankly - at that point you probably SHOULD be thinking about the actual tooling you're using to expose that, in the same way you would if you ran it manually in compose. And sure - arguably you could move to gateways now, but in no way is the ingress api deprecated. They very clearly state...
> "The Ingress API is generally available, and is subject to the stability guarantees for generally available APIs. The Kubernetes project has no plans to remove Ingress from Kubernetes."
Plenty of valid complaints for K8s (yaml config boilerplate being a solid pick) but most of the rest of your comment is basically just FUD. The complexity scale for K8s CAN get a lot higher than docker. Some organizations convince themselves it should and make it very complex (debatably for sane reasons). For personal needs... Just run k3s (or minikube, or microk8s, or k3ds, or etc...) and write some yaml. It's at exactly the same complexity as docker compose, with a slightly more verbose syntax.
Honestly, it's not even as complex as configuring VMs in vsphere or citrix.
> And no - you don't need an ingress. Just spin up a nodeport service, and you have the literal identical experience to exposing ports with compose - it's just a port on the machines running the cluster (any of them - magic!).
Might need to redefine the port range from 30000-32767. Actually, if you want to avoid the ingress abstraction and maybe want to run a regular web server container of your choice to act as it (maybe you just prefer a config file, maybe that's what your legacy software is built around, maybe you need/prefer Apache2, go figure), you'd probably want to be able to run it on 80 and 443. Or 3000 or 8080 for some other software, out of convenience and simplicity.
Depending on what kind of K8s distro you use, thankfully not insanely hard to change though: https://docs.k3s.io/cli/server#networking But again, that's kind of going against the grain.
If you just want to do development, honestly it's probably better to just use kubectl port-forward (ex - map 3000, or 8080, on your machine to any service/pod you'd like).
As for grabbing 443 or 80, most distros support specifying the port in the service spec directly, and I don't think it needs to be in the range of the reserved nodeports (I've done this on k3s, worked fine last I checked, which is admittedly a few years ago now).
As you grow to more than a small number of exposed services, I think an ingress generally does make sense, just because you want to be able to give things persistent names. But you can run a LONG way on just nodeports.
And even after going with an ingress - the tooling here is pretty straight forward. MetalLB (load balancer) and nginx (ingress, reverse proxy) don't take a ton of time or configuration.
As someone who was around when something like a LAMP stack wasn't "legacy", I think it's genuinely less complicated to setup than those old configurations. Especially because once you get it right in the yaml once, recreating it is very, very easy.
It's not the manifests so much as the mountain of infra underlying it. k8s is an amazing abstraction over dynamic infra resources, but if your infra is fairly static then you're introducing a lot of infra complexity for not a ton of gain.
The network is complicated by the overlay network, so "normal" troubleshooting tools aren't super helpful. Storage is complicated by k8s wanting to fling pods around so you need networked storage (or to pin the pods, which removes almost all of k8s' value). Databases are annoying on k8s without networked storage, so you usually run them outside the cluster and now you have to manage bare metal and k8s resources.
The manifests are largely fine, outside of some of the more abnormal resources like setting up the nginx ingress with certs.
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.
k3s makes it easy to deploy, not to debug any problems with it. It's still essentially adding few hundred thousand lines of code into your infrastructure, and if it is a small app you need to deploy, also wasting a bit of ram
K3s is just a repackaged, simplified k8s distro. You get the same behavior and the same tools as you have any time you operate an on-premises k8s cluster, and these, in my experience, are somewhere between good and excellent. So I can't imagine what you have in mind here.
"It's still essentially adding few hundred thousand lines of code into your infrastructure"
Sure. And they're all there for a reason: it's what one needs to orchestrate containers via an API, as revealed by a vast horde of users and years of refinement.
> K3s is just a repackaged, simplified k8s distro. You get the same behavior and the same tools as you have any time you operate an on-premises k8s cluster, and these, in my experience, are somewhere between good and excellent. So I can't imagine what you have in mind here.
...the fact it's still k8s which is a mountain of complexity compared to near anything else out there ?
Except it isn't just "a way to run a bunch of containers across a few machines".
It seems that way but in reality "resource" is a generic concept in k8s. K8s is a management/collaboration platform for "resources" and everything is a resource. You can define your own resource types too. And who knows, maybe in the future these won't be containers or even linux processes? Well it would still work given this model.
But now, what if you really just want to run a bunch of containers across a few machines?
My point is, it's overcomplicated and abstracts too heavily. Too smart even... I don't want my co workers to define our own resource types, we're not at a google scale company.
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.
There is a `--no-install` flag on both `uc machine init` and `uc machine add` that skips that `curl | bash` install step.
You need to prepare the machine some other way first then, but it's just installing docker and the uncloud service.
I use the `--no-install` option with my own cluster, as I have my own pre-provisioning process that includes some additional setup beyond the docker/uncloud elements.
The correct way would be to publish packages on a proper registry/repository and install them with a package manager. For example, create a 3rd party Debian repository, and import the config & signing key on install. It's more work, sure, but it's been the best practice for decades and I don't see that changing any time soon.
Sure, but it all boils down to trust at the end of the day.
Why would you trust a third-party Debian repository (that e.g. has a different user namespace and no identity linking to GitHub) more than running something from evidently the same user from GitHub, in this specific case?
I'm not arguing that a repository is nice because versioning, signing, version yanking, etc, and I do agree that the process should be more transparent and verifiable for people who care about 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.
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
Thanks! If you're running the ucloud cluster in AWS, service containers should be able to access RDS the same way the underlying EC2 instances can (assuming RDS is in the same VPC or reachable via VPC peering).
The private container IPs will get NATed to the underlying EC2 IPs so requests to RDS will appear as coming from those instances. The appropriate Security Group(s) need to be configured as well. The limitation is that you can't segregate access at the service level, only at the EC2 instance level.
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.
That's really interesting and cool. In that case calling it imperative rather than declarative is underselling it imho. I haven't worked that much with Terraform but in my usage from the cli, that is how it works too and I consider that declarative.
I get that putting the declarative spec in the control plane and having the service autoreconcile continuously is another layer but this is great as a start.
In fact could you not just cron the cli deployment command on the nodes and get an effective poor man's declarative layer to guard against node failures if your ok with a 1 min or 1 sec recovery objective?
> In fact could you not just cron the cli deployment command on the nodes and get an effective poor man's declarative layer
In the project discord, a user recently experimented with a custom setup that sounds very similar to what you describe.
In fact, a big part of uncloud’s appeal to me is that it also provides powerful building blocks for more complex, custom systems like this, not just the streamlined workflow for simpler, standard cases.
> In fact could you not just cron the cli deployment command on the nodes and get an effective poor man's declarative layer to guard against node failures if your ok with a 1 min or 1 sec recovery objective?
Yeah, you absolutely could and someone on our Discord has written a 30-line bash script that essentially runs a reconciliation loop with the CLI.
Thanks for the point on underselling by calling it imperative rather than declarative!
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.
I looked into this yesterday for making Caddy HA on my Proxmox cluster and stumbled upon keepalivd. It will provide you with a virtual IP and failover but not load balancing so you'd need to still point that at something like HAProxy for that.
Could be something interesting to integrate though.
As I mentioned in the sibling comment, please note that in this case you only get round-robin, not failover. If one of the addresses is down, the DNS record will continue returning it and users will hit a dead end.
A proper load balancer or Cloudflare DNS proxy would handle this.
We have similar backgrounds, and I totally agree with your k8s sentiment.
But I wonder what this solves?
Because I stopped abusing k8s and started using more container hosts with quadlets instead, using Ansible or Terraform depending on what the situation calls for.
It works just fine imho. The CI/CD pipeline triggers a podman auto-update command, and just like that all containers are running the latest version.
Great setup! Where Uncloud helps is when you need containers across multiple machines to talk to each other.
Your setup sounds like single-node or nodes that don't need to discover each other. If you ever need multi-node with service-to-service communication, that's where stitching together Ansible + Terraform + quadlets + some networking layer starts to get tedious. Uncloud tries to make that part simple out of the box.
You also get the reverse proxy (Caddy) that automatically reconfigures depending on what containers are running on machines. You just deploy containers and it auto-discovers them. If a container crashes, the configuration is auto-updated to remove the faulty container from the list of upstreams.
Plus a single CLI you run locally or on CI to manage everything, distribute images, stream logs. A lot of convenience that I'm putting together to make the user experience more enjoyable.
But if you don't need that, keep doing what works.
Technically I could allow my web proxy to discover my services today already, but I refuse to have Traefik (in my case) running as the same user as my services. I prefer to only let them talk over TCP/IP and configure them dynamically with Ansible instead.
It always amazed me that people used that feature in Traefik or Caddy, because it essentially requires your web proxy to have container access to all your other services. It seems a bit intimate to me, but maybe I'm old school.
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.
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.
> - 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)
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?
Sure, let's imagine image I get Jitsi Meet and CopyParty running via uncloud, is there a way to e.g save Jitsi Meet chat log of a session to CopyParty?
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.
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.
It's not a k8s replacement. It's for the small dev team with no k8s experience. For people that might not use Docker Swarm because they see it's a pretty dead project. For people who think "everyone uses k8s", so we should, too.
I need to run on-prem, so managed k8s is not an option. Experts tells me I should have 2 FTE to run k8s, which I don't have. k8s has so many components, how should I debug that in case of issues without k8s experience? k8s APIs change continuously, how should I manage that without k8s experience?
It's not a k8s replacement. But I do see a sweet spot for such a solution. We still run Docker Swarm on 5 servers, no hyperscalers, no API changes expected ;-)
How was your Swarm experience so far? It's so disappointing that Docker seems to slowly but steadily abandoning it. There is only a couple dozen mainly maintenance commits in the swarmkit repo for the entire 2025 year :sigh:
Those are all sub-par cloud technologies which perform very badly and do not scale at all.
Some people would rather build their own solutions to do these things with fine-grain control and the ability to handle workloads more complex that a shopping cart website.
I've tried to refrain from commenting but your comment pushed me over the edge. I either want to dismiss your comment as ignorant that amazon is just a shopping cart or ignorant that you even need cloud technologies until you have 1000s of customers. But I must concede there's a chance you fall in that middle area and I'm wrong. It's < 5 percent. But yeah sure.. we have a scale problem and you're right you've identified the nonsense cloud technologies that won't fix it. I'm glad you chimed in to convince us but to build our own for 5000 customers.
Check out https://github.com/psviderski/uncloud I'm building. Multi-machine deployments and a private WireGuard network spanning locations (even behind a NAT) are its core capabilities.
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