kubernetes-json-schema VS mermaid

Hey, so I thought I remembered your username. This isn’t the first interaction we’ve had, or I’ve seen you have, that follows this similar pattern. In fact it’s the third example from you under this post!

It’s not a particularly pleasant experience to discuss anything with you, as after you make a particularly vapid and usually ice-cold take that is rebuffed, you seem to just try to make snarky replies rather than engage.

Understand that if you post your takes here they may be discussed and challenged, and if you don’t want this then I would refrain from initially commenting.

In response to your comment: They do. All Kubernetes resources are typed with JSON-schema definitions. Because of course they are, how else would kubernetes validate anything. https://kubernetesjsonschema.dev/

Anyone who’s used k8s at all knows this, if only from the error messages. From this you get autocompletion and a wide ecosystem of gui configuration tools. I like lens (https://k8slens.dev/).

To avoid spending unreasonable amount of time trying to find that one wrong indent, I recommend you use schema validation and let your IDE do all the work. You can use validation schemas from https://schemastore.org/json or custom schemas such as these for Kubernetes to validate your files. These will work both with JetBrains products (e.g. Pycharm, IntelliJ) as well as VSCode (see this guide)

Seems like they haven't generated v1.20+ schema. It might work if you generate the schema yourself and feed it to KUBEVAL_SCHEMA_LOCATION

Kubeval - instrumenta/kubernetes-json-schema (last commit: 133f848 on April 29, 2020)

My "Documentation as Code" series took an unexpected turn. While I initially was a Plantuml advocate, I found myself gravitating more and more towards Mermaid charts (also after having to write some ADRs where, of course, I've added some diagrams). Its seamless integration with GitHub - automatic rendering in Markdown documents 😎 - proved to be a killer feature.

Good architecture prioritizes transparency and understanding. Tools such as vFunction or Dash0 can bring your architecture out of the shadows and into the light. Both of these offer architectural observability capabilities that help visualize your codebase, revealing service boundaries, interdependencies, and areas of inefficiency. With vFunction, teams can document complex microservices in real time, making it easier to spot bugs and bringing architecture-as-code to life with support for tools like Mermaid for sequence diagrams and automatically validating the actual architecture against manually created C4 diagrams for system modeling.

With the rise of AI-powered tools, creating these diagrams has never been easier. In this post, I evaluate some of the most popular AI-enabled diagramming tools, including Miro, Excalidraw, Figma's FigJam, ChatGPT (with Mermaid). My goal is to see how they perform when tasked with real-world developer scenarios like sequence diagrams or database ERDs.

Notion serves as a knowledge base and documentation hub for our whole company, and as QA we use it to document our practices and store some test data references. In particular, I love the ability to reference pages in other pages, creating a web of knowledge across all our documents - and with the native integration of Mermaid.js, creating flowcharts is fun and easy.

mindmap-to-mermaid: last agent transform the mind-map representation in a mermaid syntax ready for the visualization

Today, tools like Mermaid and PlantUML have taken center stage, thanks to their ability to generate diagrams with text-based commands. Even better, AI-powered assistants like Claude, ChatGPT, and GitHub Copilot have made generating diagrams even easier. These tools work directly within a developer's environment, creating diagrams that are version-controlled and integrated seamlessly into workflows.

The secret is that Q will not draw a diagram (like we would do on a piece of paper), I will ask Q to generate diagram as code with mermaid. So, my diagram will be a text that I can modify in a code editor and that I can reuse as a source for multiple tools. In this case I will use it later to rebuild my project.

Some nits:

The "Example" buttons don't jump out at me; I found them but it took a while. Also consider labeling them with their point, e.g. "Example 3: Color"

If you change the input text to something well-formed, the graph seems to update immediately. But if you change it to something ill-formed, the graph doesn't update immediately — and then if you click "Generate" manually, it blanks the input box. Either this is a bug, or the "Generate" button doesn't do what I think it does (i.e. generate output). Again, adding a noun to the verb might help. Or just adding some usage information somewhere on the page.

For those like me who've never heard of "Mermaid," apparently it's like GraphViz's dot language but different. https://github.com/mermaid-js/mermaid

* Drawn by mermaid.

The Markdown format is a blessing for documentation. While many are aware it can create headings, tables, text styles, and lists, not many know about extensions available to the basic Markup language. Today, we'll learn about Mermaid.js. This powerful yet simple diagramming tool speaks to the aspirations of Markdown format.