raml-spec VS cue

Taking this concept further one could model in RAML [0] to define both the types (flat or nested) and api definitions. It's based on YAML 1.2 with enough maturity to provide capabilities such as union types, extensions, includes, user-defined facets, etc.

The AMF project [1] can be used to parse and transform to/from RAML, OpenAPI, GraphQL, and json schema. Code generation to languages of choice can be bolted on from there.

I'm using this approach to define canonical data models. Subsequent code generation scaffolds internal application integration apis, master data management (MDM) entities, and SQL/OLAP artifacts for ETL / BI purposes.

This approach keeps overall end-to-end data architecture consistent, in sync, and versioned under source control. Additionally, flat types as required by relational systems are re-used and composed into nested complex types more appropriate for apis. Metadata is layered on as needed to refine the models for system-specific needs, for example to add user-facing field groups, descriptions, and formats for BI datasets, sensitivity levels and other data security controls, business rule definitions for MDM, etc.

[0] https://github.com/raml-org/raml-spec/blob/master/versions/r...

> Do you use JSON Schema?

At one point I did, but then discovered RAML[0] and it subsumed the value of what JSON Schema provides as well as being easier to work with than OpenAPI[1]. Also, generating JSON Schema from RAML definitions has proven to be a fairly straightforward process.

The usual caveats apply... Your mileage may vary, my experiences do not speak for any others, my opinion does not detract from the value of JSON Schema, etc.

0 - https://github.com/raml-org/raml-spec/blob/master/versions/r...

1 - https://swagger.io/specification/

If you are in a situation where you have a backend and you want to expose an API and then you would eventually want a client, you would need format specs as the starting point where server and clients are generated from that one source.

At the moment, OpenAPI with YAML is the only way to go but you can't easily split the spec into separate files as you would do any program with packages, modules and what not.

There are third party tools[0] which are archived and the libraries they depend upon are up for adoption.

In that space, either you can use something like cue language 1] or something like TypeSpec which is purpose built for this so yet, this seems like a great tool although I have not tried it yet myself.

[0]. https://github.com/APIDevTools/swagger-cli

[1]. https://cuelang.org/

EDIT: formating

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.