apiclarity VS rust

We'll install APIClarity into a Kubernetes cluster to test our API documentation. We're using a Kind cluster for demonstration purposes. Of course, if you have another Kubernetes cluster up and running elsewhere, all steps also work there.

If you go to APIClarity, the first thing you’ll see is the source code (Figure 1), followed by some documentation at the bottom.

This feature is available in the open-source tool APIClarity, as part of the OpenClarity initiative.

Hi, I would also like to add another tool I'm contributing to at work (cisco) called APIClarity [1]. It aims at reconstructing swagger specifications of REST microservices running in K8S, but can also be run locally.

This is a challenging task and we don't support OpenAPI v3 specs yet (we are working on it).

Feel free to have a look, and get ideas from it :)

We'll also be presenting it at next Kubecon 2022.

[1]: https://github.com/openclarity/apiclarity

For example, APIClarity is a tool that observes all of the API traffic within your Kubernetes environment. Based on traffic observation, APIClarity infers an OpenAPI description for those APIs. This is especially helpful if the API creator never defined or provided such a description. It also surfaces potential problems with existing APIs, such as requests made to undocumented, shadow APIs or continued use of deprecated, zombie APIs. If you’re getting started on the path toward OAS compliance, then tools like APIClarity can be a great source of insight and observability.

The fundamental first step to solving this problem is to create an API spec and use it to audit and document the APIs your apps use. Ideally, we would create an API spec simply by observing API traffic in real-world applications. In the past, there was no simple, scalable, and open-source tooling capable of doing this. Now, we have APIClarity—an open-source API traffic visibility tool for Kubernetes (K8s) clusters. It’s purpose-built to address the gap and enable API reconstruction through observation.

If you haven't dipped your touch-typing fingers into Rust yet, you really owe it to yourself. Rust is a modern programming language with features that make it suitable not only for systems programming -- its original purpose, but just about any other environment, too; there are frameworks that let your build web services, web applications including user interfaces, software for embedded devices, machine learning solutions, and of course, command-line tools. Since a custom GitHub Action is essentially a command-line tool that interacts with the system through files and environment variables, Rust is perfectly suited for that as well.

Here's an example of someone citing a disagreement between CRT and shell32:

https://github.com/rust-lang/rust/issues/44650

This in addition to the Rust CVE mentioned elsewhere in the thread which was rooted in this issue:

https://blog.rust-lang.org/2024/04/09/cve-2024-24576.html

Here are some quick programs to test contrasting approaches. I don't have examples of inputs where they parse differently on hand right now, but I know they exist. This was also a problem that was frequently discussed internally when I worked at MSFT.

    #include 

> instead of choosing a certain numbered version of the random library (if I remember correctly) I let cargo download the latest version which had a completely different API.

Yeah, they didn't follow the instructions and got burned. I still think that multiple things went wrong simultaneously for that experience. I wonder if more prevalent uses of `#[doc(alias = "name")]` being leveraged by https://github.com/rust-lang/rust/pull/120730 (which now that I check only accounts for methods and not functions, I should get on that!) so that when changing APIs around people at least get a slightly better experience.

Almost fixed the compiler: https://github.com/rust-lang/rust/pull/123325

Rust: A secure, efficient, and modern programming language (omitting ten thousand words). You can simply follow the installation instructions provided on the official website.

Recently did something similar in Rust but for generating SVGs. We've adopted it for snapshot testing of cargo and rustc's output. Don't have a good PR handy for showing Github's rendering of changes in the SVG (text, side-by-side, swiping) but https://github.com/rust-lang/rust/pull/121877/files has newly added SVGs.

To see what is supported, see the screenshot in the docs: https://docs.rs/anstyle-svg/latest/anstyle_svg/

We strongly believe in Rust as a powerful language for building production-grade software, especially for systems like ours that run alongside Kubernetes.

The above Assert<{N % 2 == 1}> requires #![feature(generic_const_exprs)] and the nightly toolchain. See https://github.com/rust-lang/rust/issues/76560 for more info.