mgmt VS cue

This is a new provisioning tool built with https://github.com/purpleidea/mgmt/ that I hope both provides great value and also demonstrates the start of a new way to build certain kinds of software.

Thanks for reading!

I've looked briefly into this project before. Some ideas are similar to what I'm doing in https://github.com/purpleidea/mgmt/ but the really weird thing is that I have no idea who's behind this language. A person? A company? A small group? Are they anonymous for some reason or am I oblivious?

I don't generally believe in orchestrators (they miss the point, things are not single computers and neither is the world) and so I have that feedback here but also for:

> Airflow/Cadence/Temporal/Databuilderframework?

Which don't really think about modelling non-centralized things.

This of course doesn't mean they're not useful, it's just that they don't have what I believe is a good long-term value proposition.

I'm incredibly biased because I'm working on programmatic, real-time modelling of distributed systems with https://github.com/purpleidea/mgmt/

The DAG concurrency stuff feels familiar to what I've been doing with our language, mcl. https://github.com/purpleidea/mgmt/

Our goal is NOT a general-purpose turing-complete language like this one is, but we do some amazing lock-free, DAG concurrency things to achieve the processing wins.

I don't think it's good news, but why is anyone surprised? Nobody wants to pay for open source.

Companies want it for free, and individuals don't have enough luxury time to be able to do it themselves.

Prove me wrong and help patch or fund https://github.com/purpleidea/mgmt/ and you'll have an even better replacement for terraform!

Individual here, not a company. We'd love contributors to https://github.com/purpleidea/mgmt/

Eventually decided puppet wasn't a good enough tool to be able to autonomously deploy and continuously manage such clusters. So I started working on this https://github.com/purpleidea/mgmt/ project. Not quite MVP yet, but trying to get there soon. Got distracted along the way with having to work real jobs (Red Hat, Amazon) to pay bills.

Yeah, that project is pretty much at the bottom of my list, unfortunately. My top projects these days are mgmt, klister, recursion-schemes, and hint... And that's already too much!

There are certainly faster alternatives out there (mgmt comes to mind) but then, they're not Ansible.

Where `kube.cue` sets reasonable defaults (e.g. image is /). The "cluster" runs on a mini PC in my basement, and I have a small Digital Ocean VM with a static IP acting as an ingress (networking via Tailscale). Backups to cloud storage with restic, alerting/monitoring with Prometheus/Grafana, Caddy/Tailscale for local ingress.

[1] https://www.talos.dev/

[2] https://cuelang.org/

I've been somewhat surprised that CUE bills itself as "tooling friendly" and doesn't yet have a language server- the number one bit of tooling most devs use for a particular language.

I'm assuming it's becaus CUE is still unstable?

Anyway, if others are interested in CUE's LSP work, I think https://github.com/cue-lang/cue/issues/142 is the issue to subscribe to

This is where I usually pitch in with "Have your heard of CUELang, our lord and savior?": https://cuelang.org/

- Not turing complete

CUE: The core problem CUE solves is "type checking", which is mainly used in configuration constraint verification scenarios and simple cloud native configuration scenarios.

If you really want executable configurations please consider a newer language like https://dascript.org or https://cuelang.org which provide better type safety.

1- https://news.ycombinator.com/item?id=38030778

Markdown and XML are nice, but what about more advanced documentation formats like OpenAPI? For one recent project, I set up automatic generation of the OpenAPI docs from (much more compact and flexible) CUE definitions (https://cuelang.org/) - which has the bonus of also being able to test the API against the definitions. JetBrains has a CUE plugin, but it's really barebones (doesn't even support jumping from the usage of a schema to its definition). Of course the possibilities when generating docs are endless (just think of the various syntaxes for doc comments, embedding examples/tests in source code etc.)...

It doesn't include validators for TOML and INI, but if you're doing JSON and YAML, I would take a look at using or building upon CUE (https://cuelang.org/). It is a different take on schema definition (plus more), and is surprising terse and powerful model.