I have been knee deep in deployment space for post 4 years. It is pretty hard problem to solve to the n-th level. Here's my 2 cents.

Single machine deployments are generally easy, you can do it DIY. The complexity arises the moment you have another machine in the setup, scheduling workloading, networking, setup to name a few, starts becoming complicated.

From my perspective, kubernetes was designed for multiple team, working on multiple services and jobs, making operation kind of self serviced. So I can understand the anti-kubernetes sentiment.

There is gap in the market between VM oriented simple deployments and kubernetes based setup.

KronisLV

> There is gap in the market between VM oriented simple deployments and kubernetes based setup.

In my experience, there are actually two platforms that do this pretty well.

First, there's Docker Swarm ( https://docs.docker.com/engine/swarm/ ) - it comes preinstalled with Docker, can handle either single machine deployments or clusters, even multi-master deployments. Furthermore, it just adds a few values to Docker Compose YAML format ( https://docs.docker.com/compose/compose-file/compose-file-v3... ) , so it's incredibly easy to launch containers with it. And there are lovely web interfaces, such as Portainer ( https://www.portainer.io/ ) or Swarmpit ( https://swarmpit.io/ ) for simpler management.

Secondly, there's also Hashicorp Nomad ( https://www.nomadproject.io/ ) - it's a single executable package, which allows similar setups to Docker Swarm, integrates nicely with service meshes like Consul ( https://www.consul.io/ ), and also allows non-containerized deployments to be managed, such as Java applications and others ( https://www.nomadproject.io/docs/drivers ). The only serious downsides is having to use the HCL DSL ( https://github.com/hashicorp/hcl ) and their web UI being read only in the last versions that i checked.

There are also some other tools, like CapRover ( https://caprover.com/ ) available, but many of those use Docker Swarm under the hood and i personally haven't used them. Of course, if you still want Kubernetes but implemented in a slightly simpler way, then there's also the Rancher K3s project ( https://k3s.io/ ) which packages the core of Kubernetes into a smaller executable and uses SQLite by default for storage, if i recall correctly. I've used it briefly and the resource usage was indeed far more reasonable than that of full Kubernetes clusters (like RKE).

proxysna

Nomad also scales really well. In my experience swarm had a lot of issues with going above 10 machines in a cluster. Stuck containers, containers that are there but swarm can't see them and more. But still i loved using swarm with my 5 node arm cluster, it is a good place to start when you hit the limit of a single node.

> The only serious downsides is having to use the HCL DSL ( https://github.com/hashicorp/hcl ) and their web UI being read only in the last versions that i checked.

1. IIRC you can run jobs directly from UI now, but IMO this is kinda useless. Running a job is simple as 'nomad run jobspec.nomad'. You can also run a great alternative UI ( https://github.com/jippi/hashi-ui ).

2. IMO HCL > YAML for job definitions. I've used both extensively and HCL always felt much more human friendly. The way K8s uses YAML looks to me like stretching it to it's limits and barely readable at times with templates.

One thing that makes nomad a go-to for me is that it is able to run workloads pretty much anywhere. Linux, Windows, FreeBSD, OpenBSD, Illumos and ofc Mac.