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Canonical is just one of several players in this area. There's also k3s and k0s, for example.

I suppose it might depend on what you count as "edge", but we're using kubernetes to distribute a complex product to customers onprem. The product has multiple databases, services, transient processes, scheduled jobs, and machine learning. It needs to be able to run on a single machine or a cluster depending on customer requirements. It needs to support whatever Linux variant the customer allows. Using Kubernetes solves a lot of problems for us.

on-prem is not edge IMO. Edge is something small, far away from datacenters, close to customers with limited compute and storage capacity. Did I get this wrong?

For example, SQLite advertise itself as "database on edge".

"Edge" is kind of a relative term. E.g. relative to a public cloud, anything not in that cloud could be considered edge. Or, if a company's systems are in a shared datacenter somewhere, then the systems in their actual offices might be considered "edge".

Just as an example (not saying it's authoritative):

> "Edge computing is often referred to as 'on-premise.'"

   -- https://dzone.com/articles/demystifying-the-edge-vs-cloud-computing
But these days, people even refer to systems hosted on a company's own cloud account as "on-premise", so these terms get increasingly fuzzy over time.

Btw since you mention SQLite, the k3s system uses SQLite instead of the default etcd used by Kubernetes, for the reason you mention. These systems really are intended to support true edge scenarios. K3s is distributed as a single 40 MB binary, and you can run it on non-PC edge hardware.

For anyone who runs a system that involves multiple containers on a single machine, it can be worth looking at systems like k3s as an alternative to e.g. Docker Compose. There's not much downside other than some learning curve, and it gives you a wealth of capabilities that you otherwise tend to end up hacking together with scripts or whatever.

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