Model-view-docs: taming large-scale documentation projects using structured data
summary
Argues that data-driven documentation makes large, changing docs maintainable by separating structured sources (JSON/YAML) from templates and automating builds. Uses static site generators like Hugo, fetches releases via the GitHub API, and pulls CLI JSON at build time; one downloads page generates about ~250 URLs automatically. Shows Jaeger CLI JSON generation and a Spire downloads site that work in production, and cites Stripe-style OpenAPI YAML as a scalable pattern.
AI-written summary · about
chapters (4)
related talks
01h 02mZero to Document Hero
58mDeveloping Web Applications with Haskell
48mBuilding secure GraphQL APIs without the Boilerplate
14mTalk With Your Documents Via Docs2KG
19mUnlock API and Data – The Power of Data Model and Governance
35mGit: the stupid NOSQL database
31mWhen the data levee breaks: Managing cognitive load in data-intensive projects
40mRapid Data Modeling Using ActiveRecord and the JSON Data Type