magic-modules VS dhall-kubernetes

Given: https://registry.terraform.io/providers/hashicorp/google/5.3...

how would any reasonable person know what https://registry.terraform.io/providers/hashicorp/google/5.3... to enable without (a) trying it and squinting at the error message (b) clicking on the <> then realizing it, also, does not mention run.googleapis.com, click on "supported service endpoints" <https://cloud.google.com/run/docs/reference/rest#rest_endpoi...> and only then learning about https://cloud.google.com/run/docs/reference/rest#service:-ru...

Repeat for https://registry.terraform.io/providers/hashicorp/google/5.3... although in both cases I guess the astute reader may have spotted the run.googleapis.com in the forbidden service labels and cloudidentity.googleapis.com in the example

Since, to the best of my knowledge those bindings are auto generated <https://github.com/GoogleCloudPlatform/magic-modules#magic-m...>, I would hypothesize it is not insurmountable drop in the seemingly existing declaration of APIs required: https://github.com/GoogleCloudPlatform/magic-modules/blob/7d... https://github.com/GoogleCloudPlatform/magic-modules/blob/7d...

In the case of the Google Cloud Platform provider, folks at Google built magic modules with the explicit goal of being able to generate schemas and behaviors for a Terraform provider and for other systems with similar needs. Since the vendor was explicitly aiming to support Terraform, this was the most ideal case where the schema could be designed to contain all of the information needed to generate a functional, usable provider.

I think the "Developing the provider" instructions in this provider's repository are rather stale, because they still talk about GOPATH even though that's been obsolete for several Go versions now. Note also that much of the code in that repository is auto-generated from an upstream repository googleCloudPlatform/magic-modules, and so for some changes it may be better to contribute there once you've tested the modifications more directly inside the provider repository.

For GCP, both ansible modules and terraform modules are actually generated from https://github.com/GoogleCloudPlatform/magic-modules, so their "production readiness" are the same.

I understand that mitchellh himself personally created a bunch of cloud modules for terraform at the beginning, and those were likely of higher quality than whatever created by some internal developers assigned by Google/Microsoft, and might be slightly better than the AWS modules maintained by community.

Anyway, when it comes to ansible versus terraform, we shall move the discourse to states management instead. With ansible, you don't have to deal with states, but will need to clean up the cloud resources separately. With terraform, you can use the tool to clean up the cloud resources easily, but then you also have the headache of managing states. Plus, whenever you change something, there is always the nagging feeling that it will do a destroy/recreate instead of an in-place update.

The Terraform provider for Google Cloud uses partial autogeneration, here is the repo that does the autogeneration for multiple automation tools:

https://github.com/GoogleCloudPlatform/magic-modules

I hate yaml with a passion. It marginally better than xml for reading (wins huge on comment syntax) and worse for everything else. It makes zero sense we somehow ended up with it as standard configuration serialization format.

Note yaml is not a DSL. It's a tree serialization format! Everything interesting is happening after it is parsed. Extreme examples point to e.g. github actions conditions.

Anyway, back on topic - maybe not prolog for CDK, but still quite interesting: Dhall-kubernetes - https://github.com/dhall-lang/dhall-kubernetes

At this point, if it’s painful enough, why isn’t compiling-to-yml tools more popular?

Example: https://github.com/dhall-lang/dhall-kubernetes

Haven’t used dhall myself but I’d definitely prefer a DSL on top of yaml.

Dhall provides https://github.com/dhall-lang/dhall-kubernetes which is exactly this: statically type-checked kubernetes config generation.

Dhall is my favorite configuration language that I never get around to using.

I manage DNS in Terraform, and since every Terraform provider uses different objects definitions, and every object definition is rather verbose, Dhall would be a way to specify my own DRY types and leave the provider-specific details in one place. Adding new DNS entries and moving several domains between providers would be a matter of changing fewer lines.

Dhall also has Kubernetes bindings:

https://github.com/dhall-lang/dhall-kubernetes

Although I'm tempted to just stick to Helm here, even though it's less type-safe.

Not Helm directly, but does something like Dhall fit your question? https://github.com/dhall-lang/dhall-kubernetes

Have you heard about Dhall? It’s a programming language used for generating configuration files for a variety of purposes. One of them is to replace old and limited formats such as JSON and YAML. It is DRYable, secure, and even suitable for creating K8s manifests. The latter option isn’t something for anyone: you have to learn a new language and deal with its peculiarities, but it might be really helpful when you have tons of YAML configs. I’ve recently made a short intro to Dhall for K8s in this review.

Best thing is Dhall that I am aware of. Same situation, working as a consultant, forced to use broken things.

https://github.com/dhall-lang/dhall-kubernetes

Lets look at a specific example. Take Kubernetes: everything is yaml, with complete schemas, all the way down. From your perspective this is configuration utopia, right? Meanwhile back in reality k8s is the poster child of "yaml hell". From the day it was released, people took one look at it, gave it a giant NOPE and instantly spawned half a dozen templating languages. The most popular of these is helm, which has a terrible, no good, very bad design: full of potential injection attacks from purely textual string substitution, manually specified indentation to embed parameterized blocks, virtually no intermediate validation, no way to validate unused features, etc etc

Compare to dhall which publishes a complete set of dhall-k8s schema mappings which enables you to factor out any design you want down to as few configuration variables as you like, while validating the configuration generators themselves at design time. https://github.com/dhall-lang/dhall-kubernetes#more-modular-...

The solution I like is Dhall. They even have a Kubernetes solution that will catch a lot of issues at compile-time, before you try to apply it to Kubernetes. At earthly we aren't actually using it though. Our Kubernetes guru found it to be a bit slow but I am hopeful it or something like it will be the future.