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.

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.

That’s awesome if k3s works for you, nothing wrong with this. You’re simply not the target user then.

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

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.

Perhaps it feels so easy given your familiarity with it.

I have struggled to get things like this stood up and hit many footguns along the way

Indeed, it seems a knee jerk response without justification. k3s is pretty damn minimal.

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.

+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...

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.

Curious, what would be an ideal (secure) approach for you to install this (or similar) tool?

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:

    current_context: default
    contexts:
      default:
        connections:
          - ssh: admin@192.168.0.10
            ssh_key_file: ~/.ssh/uncloud
          - ssh: admin@192.168.0.11
            ssh_key_file: ~/.ssh/uncloud
          - ssh: administrator@93.x.x.x
            ssh_key_file: ~/.ssh/uncloud
          - ssh: sysadmin@65.x.x.x
            ssh_key_file: ~/.ssh/uncloud

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.

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.

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.

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.

podman-compose works fine. It’s a very simple format.

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.

Do you have an example of what you mean? I'm not entirely clear on your question.

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?

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 ;-)

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.