hcl VS jsonnet

Terraform HCL (HashiCorp Configuration Language) is an essential language for cloud engineers in 2024, particularly for those involved in infrastructure as code (IaC) practices. HCL is the configuration language used by Terraform, a widely adopted tool that enables engineers to define, provision, and manage cloud infrastructure using a declarative configuration approach. Learning Terraform HCL allows cloud engineers to automate the deployment and lifecycle management of cloud resources across various service providers, ensuring consistency, repeatability, and scalability of cloud environments.

Reminds me of [HCL](https://github.com/hashicorp/hcl), but without all the providers to deploy the config?

HCL: A Go implementation structured configuration language. The native syntax of HCL is inspired by libucl and nginx configurations. It is used to create a structured configuration language that is friendly to humans and machines, mainly for DevOps tools, server configurations, and resource configurations as a Terraform language.

HCL has a JSON representation [1], internally, objects behave that way. so it should be possible to write a Jsonnet wrapper around it. Terraform can currently parse json pipelines too.

[1]: https://github.com/hashicorp/hcl/blob/main/json/spec.md

>https://noyaml.com/

I'm not sure this is the criticism you think it is. Wow, so you basically have to add quotes to get strings in some ambiguous situations?

Yeah sure you could probably improve YAML by getting rid of these weird pitfalls, but that is a minor improvement. The alternative isn't something like TOML, because YAML is optimized for hierarchical configuration. It's every vendor implementing a different syntax such as Hashicorp with their HCL [0].

[0] https://github.com/hashicorp/hcl

The Hashicorp corporation has made a huge impact in providing valuable tools and platforms in the cloud ecosystem. The advantage of using the tools they provide, such as Terraform, Vault, and Packer, is that they all have the same language, Hashicorp Configuration Language (HCL). This means you can easily pick up any of these tools by learning HCL, which is similar to JSON. This approach can be useful when choosing tools to learn or use for a project.

Format is HCL language feature: https://github.com/hashicorp/hcl/blob/main/hclwrite/public.go

Hi, from what I read from HCL Github "HCL is a syntax and API specifically designed for building structured configuration formats.".

When the desired state is relatively simple to define and the mechanism to reach that state is not that important, writing up a declaration of what is needed and letting something/someone else deal with it is the most logical abstraction. This would be like drafting up the architectural draft for your new restaurant and paying a contracting company to actually build it, or writing HTML and letting a web browser render it, or writing a Terraform HCL file and letting the Terraform CLI tool apply it. This is called declarative programming in the software world, and has many advantages (and a few disadvantages!) for cloud infrastructure management.

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/