tofu-controller VS jsonnet

We stumbled upon a project for maintaining Terraform with CRDs that we could deploy with Helm. That project is now called Tofu-Controller - another WeaveWorks project, so it integrated great with our existing Flux setup.

https://github.com/weaveworks/tf-controller/issues/1166#issu...

Weave's TF-Controller, which also has fewer bugs, much better adoption, and it looks like it's actually being developed by someone. But requires a weird argocd <-> flux interop boilerplate. It's a "controller for flux" and not a Kubernetes controller, and I don't really get such ambiguous targeting , but meh...

Wrt tools, I wanted to integrate terraform with Flux thanks to their tf-controller. Conciling the core gitops features with terraform would be great imho.

I'm using Flux instead of Argo which has support for running terraform from a given Git Repo or OCI artifact so essentially I still fall back on Terraform when needed and it's applied via GitOps.

tf-controller which is integrated with Flux GitOps and reconciles Terraform files in a control loop

While searching for alternatives for running Terraform using Kubernetes, I found several controllers and operators, but none that I felt had as much potential as the tf-controller from Weaveworks. We are already using Flux as our GitOps tool, and the tf-controller works by utilizing some of the core functionality from Flux, and has a custom resource for Terraform deployments. The source controller takes care of fetching our modules, the kustomize controllers apply the Terraform resources, and then the controller spin up static pods (called runners) that runs your Terraform commands.

For us, GitOps is a vital part of how we operate, and it is the magic sauce that fuels our platform offering. Not only do we use it for application deployments, but by utilizing the Weaveworks tf-controller, we can create services using Terraform to automate our infrastructure deployments.

Some further research brought me to Weaveworks' TF-Controller which appears to be able to do what I want at least for the initial deployment step. Flux CD (also by Weaveworks) integrates with KEDA now, so it would be great if it could also integrate with KEDA to manage terraform-deployed Azure resources.

jsonnet[1] and kapitan[2] are the tools I currently use. Their learning curve is not optimal (and I tried to contribute to smoothen it with a jsonnet course[3] and a 'get started wit kapitan' blog post[4]), but once used to it it's hard to do without, and their combination makes them even more useful (esp. if you deploy K8s).

In Ruud's case, Jsonnet might have been worth looking at as Hashicorp tools can be configured with json in addition to HCL. But that would have been less fun I guess ;-)

I hope for Ruud it finds its niche, there's quite some competition in this field!

1: https://jsonnet.org/

Kubernetes config is a decent example. I had ChatGPT generate a representative silly example -- the content doesn't matter so much as the structure:

https://gist.github.com/cstrahan/528b00cd5c3a22e3d8f057bb1a7...

Now consider 100s (if not 1000s) of such files.

I haven't given Pkl an in depth look yet, but I can say that the Industry Standard™ of "simple YAML" + string substitution (with delicate, error prone indentation -- since YAML is indentation sensitive) is easily beat by any of:

- https://jsonnet.org/

- https://nickel-lang.org/

- https://nixos.org/manual/nix/stable/language/index.html

- https://dhall-lang.org/

- (insert many more here, probably including Pkl)

jsonnet cli: link

Jsonnet: A data template language implemented in C++, suitable for application and tool developers, can generate configuration data and organize, simplify and manage large configurations without side effects.

[Language: Jsonnet] (on GitHub)

Maybe you'd like jsonnet: https://jsonnet.org/

I find it particularly useful for configurations that often have repeated boilerplate, like ansible playbooks or deploying a bunch of "similar-but" services to kubernetes (with https://tanka.dev).

Dhall is also quite interesting, with some tradeoffs: https://dhall-lang.org/

A few years ago I did a small comparison by re-implementing one of my simpler ansible playbooks: https://github.com/retzkek/ansible-dhall-jsonnet

Apologies for the lack of context, and for missing this comment until today.

Both are tools for defining kubernetes manifests (which are YAML) in a reusable manner.

Jsonnet is a formally specified extension of JSON. It’s essentially a functional programming language (w/some object oriented features) that generates config files in JSON/YAML/etc, so it’s straightforward to determine whether an input file is valid, and to throw an error that points to an exact line if it’s not. It has a high learning curve, especially for people whose only experience is with imperative languages.

https://jsonnet.org/

Helm charts also generate YAML/JSON config files, but they use Go templating. This is easier and faster to understand, since it’s mostly string substitution and not much logic (there’s conditionals, iterators, and very basic helper functions). Unfortunately a simple typo or mistake can cause errors that are difficult to diagnose (the message may indicate a problem far away in code from the actual mistake). It can also generate output that’s valid according to the string templating rules, but not what was intended, which can be very confusing to debug.

Despite these shortcomings, the vast majority of kubernetes applications are distributed as helm charts. I understand why things ended up this way, but I still wish it were more common for people to invest the upfront effort to learn the superior tool, so it could be more widespread.

I like Google's Jsonnet [1], which has all of this except for 4.

Jsonnet is quite mature, with fairly wide language adoption, and has the benefit of supporting expressions, including conditionals, arithmetic, as well as being able to define reusable blocks inside function definitions or external files.

It's not suitable as a serialization format, but great for config. It's popular in some circles, but I'm sad that it has not reached wider adoption.

[1] https://jsonnet.org/