polly VS cue

re: Grafana (i'm the author of the linked issue) - i'm quite excited, i do think there's a world of possibilities here.

Two-way sync with a git repo is one possible path, and we've talked a lot internally at GL about how to best support it. My sense is that we can do it with relatively little friction and likely will - but if you're just syncing with a git repo, there's still a lot of arbitrary, opaque repo layout decisions that still have to be made (how do you map a filesystem position for a dashboard to a position in Grafana? In a way that places the dashboards next to the systems they're intended to observe? With many teams? With many Grafana instances?) which induce new kinds of friction at scale.

Fortunately - and not mutually exclusively with the above - by building the system for schema in CUE, we've made a composable thing that we can make into larger systems. That's what we're starting to do with Polly: https://github.com/pollypkg/polly

Conveniently, my parts of a Grafanaconline talk tomorrow discusses both of these https://grafana.com/go/grafanaconline/2021/dashboards-as-cod... :D

I'm continuing to work on https://concise-encoding.org which is a new security-conscious ad-hoc encoding format to replace JSON/XML and friends. I've been at it for 3 years so far and am close to a release.

In a nutshell:

- Edit in text, transmit in binary. One can be seamlessly converted to the other, but binary is far more efficient for processing, storage and transmission, while text is better for humans to read and edit (which happens far less often than the other things).

- Secure by design: Everything is tightly specced and accounted for so that there aren't differences between implementations that can be exploited to compromise your system. https://github.com/kstenerud/concise-encoding/blob/master/ce...

- Real type support because coercing everything into strings sucks (and is another security risk and source of incompatibilities).

XML had a good run but was replaced by JSON which was a big improvement. JSON also had a good run but it's time for it to retire now that the landscape has changed even further: Security and efficiency are the desires of today, and JSON provides neither.

I've got the spec nailed down and can finally see the light at the end of the tunnel for the reference implementation in golang. I still need to come up with a system for schemas, but I'm hoping that https://cuelang.org will fit the bill.

Has anyone taken a look at Cue who can share any experiences?

https://cuelang.org/

It's mentioned on the site as an alternative to Yaml. Recently watched (~half of) this intro to it: https://youtu.be/fR_yApIf6jU

the most interesting summary explanation of cue lang and its differences is from a bug filing - https://github.com/cuelang/cue/issues/33

>CUE is a bit different from the languages used in linguistics and more tailored to the general configuration issue as we've seen it at Google. But under the hood it adheres strictly to the concepts and principles of these approaches and we have been careful not to make the same mistakes made in BCL (which then were copied in all its offshoots). It also means that CUE can benefit from 30 years of research on this topic. For instance, under the hood, CUE uses a first-order unification algorithm, allowing us to build template extractors based on anti-unification (see issue #7 and #15), something that is not very meaningful or even possible with languages like BCL and Jsonnet.

I agree with you. Personally, I think Cue is much better than either YAML, TOML or JSON because it adds the concept of types to the idea of describing configuration.

true, but the tooling and workflow remains the same.

Not sure of any tool that could abstract the details sufficiently to be widely adopted. There is just too much nuance in cloud config.

I'm exploring using CUE (https://cuelang.org) to define TF resources, exporting as JSON for TF. So far it's much nicer

I've been using https://cuelang.org for any configuration / yaml like generation. This link has a GH search with two discussions that talk about Rego: https://github.com/cue-lang/cue/search?q=rego&type=discussio...

I wrote https://github.com/hofstadter-io/hof to use this concept "at scale", i.e. inputting & outputting multiple files & dirs. The main idea was to generate common code across the stack from a single-source-of-truth. Today it inputs CUE only, which has all the things needed to validate the incoming data and also contains the templates, so `hof gen` takes the same args as `cue export`. It uses diff3 so that you can regenerate the output after modifying the input or the generated content, which is something I needed so that when I fill in the generated API handler func, and then change the design a bit, that I can keep the manual work.