**CUE (Configure-Unify-Execute)** is an **open-source data constraint language** developed at Google, designed for **configuration management, validation, and templating**. It stands for **Configure, Unify, Execute**. ### Purpose CUE simplifies tasks involving **defining, validating, and using data** in complex systems like Kubernetes. It combines **schemas, constraints, and values** into a unified framework, ensuring configurations adhere to predefined rules. ### Key Features - **Validation First**: Unlike traditional languages, CUE prioritizes validation, ensuring data meets strict criteria. - **JSON Superset**: It builds upon JSON, adding logic like conditionals and loops. - **Constraint-Based**: Uses constraints instead of inheritance, avoiding complexity from order-dependent merging. - **Order Independence**: Merging configurations is **associative, commutative, and idempotent**, ensuring consistency regardless of merge order. - **Tooling**: Offers CLI tools (`cue` command), APIs for automation, and integrations with YAML/JSON. ### Use Cases - **Kubernetes**: Validate and generate YAML configurations. - **Data Validation**: Define schemas for APIs or infrastructure. - **Code Generation**: Extract schemas from source code or generate code from CUE definitions. - **CI/CD Pipelines**: Ensure deployment consistency. ### Example In CUE, you might define a schema for a Kubernetes deployment, enforce constraints (e.g., resource limits), and generate validated YAML—all in one workflow. ### Summary CUE is a **robust, constraint-driven language** that unifies configuration, validation, and execution, particularly valuable for managing complex, policy-driven systems like cloud infrastructure. --- Here are **six starter ideas** that feel more like “mini-projects” than “hello-world” exercises. Each one is scoped to be finished in an evening or weekend and leaves you with something useful you can actually commit to a repo or show a teammate. ------------------------------------------------ 1. “Pet-Picture” API Contract • Goal: Design the request/response contract for a tiny REST service that lets users POST pictures of their pets. • CUE angle – Write a `#PetPhoto` schema with required fields (`id`, `petName`, `imageURL`), plus constraints (URL must start with `https://`, file size ≤ 5 MB, allowed MIME types). – Export the same CUE to JSON Schema so front-end folks can use it in Swagger / OpenAPI. • Quick win: `curl` a sample payload through `cue vet` in CI and watch it reject the 6 MB GIF someone tried to sneak in . 2. Terraform Variable Guardrails • Goal: Stop teammates from fat-fingering Azure VM sizes or AWS regions in your Terraform repo. • CUE angle – Describe all valid regions, SKUs, and tag patterns in CUE. – Make a `variables.cue` that unifies with every `.tfvars` file in the repo; fail the plan if anything is wrong . • Quick win: open a PR that deliberately violates the policy and see GitHub Actions reject it in <30 s. 3. Team Dotfiles Distribution • Goal: Ship a single YAML/JSON file per engineer that declares their preferred shell, VS Code extensions, and git aliases. • CUE angle – Provide a `#Workstation` schema with defaults (shell = `"zsh"`, extensions = `[ "GitLens", "k9s" ]`). – Write a 20-line Go program that ingests the unified CUE value and spits out the right Ansible or Home-Brew bundle per person . 4. Kubernetes “Golden Path” Templates • Goal: Give devs a one-command way to generate a Deployment + Service + HPA that already meets security and resource standards. • CUE angle – Create a `#Microservice` definition that enforces labels, resource limits, and security contexts. – Provide optional overlays (staging vs prod) that inject different image registries or replica counts . • Quick win: `cue cmd gen prod my-app` writes `prod-my-app.yaml` with zero copy-paste. 5. Resume-as-Data • Goal: Host your résumé as YAML but still be able to export to PDF, JSON, and HTML. • CUE angle – Model sections (`experience`, `education`, `skills`) with strict types and regex rules (company names must match LinkedIn URLs). – Use `cue export` to feed a Go template that renders LaTeX or Markdown. • Quick win: change one bullet in YAML, rerun `make` and see every output format refresh. 6. Advent-of-Code Input Validator • Goal: Stop wasting time on malformed puzzle inputs. • CUE angle – For any AoC day, capture the input grammar in CUE (grids, ints, regex groups). – Add constraints (board size 100×100, numbers 0-9 only). • Quick win: paste your downloaded input into `input.txt`; `cue vet` tells you immediately if the site changed the format overnight. ------------------------------------------------ How to pick one • If you live in Terraform → start with #2. • If you just want to “see CUE do magic” → #1 or #5 finishes in <30 min. • If you’re already on K8s → #4 will save you real toil next sprint. Each repo can literally be a folder with a `schema.cue`, a `data.*` file, and a two-line GitHub Action that runs `cue vet`. Ship it, tag a friend for review, and you’ve officially gone from “reading about CUE” to “running CUE in production.” --- Below is a **step-by-step brainstorm** that keeps the promise: “Everything is an object” → expressed in **CUE** → rendered into **one or more Docker containers** → **deployed on stock Debian**. We iterate *together*—after each numbered idea you can simply reply **“next”** or **“deep-dive ”** and I’ll expand only the one you like. ------------------------------------------------ 1. Object–Music Player (OM-Player) • **Object model**: every track, playlist, device, volume-level, EQ preset is a CUE object. • **CUE → Docker trick**: `cue export om.cue | cue cmd gen docker-compose.yml` yields *three* containers (MPD server, web-UI, icecast stream). • **Deploy**: `./deploy.sh` on a Debian box auto-pulls images, mounts `/music`, and exposes port 8000. • *Hook*: you can change “cross-fade = 2.0s” in the CUE file, run `cue vet`, and the compose file re-renders without touching YAML by hand. 2. Object–Photo Darkroom (OM-Darkroom) • **Object model**: raw image, transform pipeline (crop 1:1 → denoise → LUT), export profiles. • **CUE → Docker trick**: single multi-stage Dockerfile generated from CUE; includes conditional GPU layer if `gpu: true`. • **Deploy**: on Debian with or without NVIDIA Docker runtime . • *Hook*: `cue eval darkroom.cue` shows you the exact ImageMagick CLI that will run inside the container before you ever build. 3. Object–Home-Lab Router (OM-Router) • **Object model**: interface objects, VLAN objects, nftables rule objects, WireGuard peer objects. • **CUE → Docker trick**: produces a *privileged* container that maps `/etc/wireguard`, `/etc/nftables`; plus a dry-run sidecar container that just prints the rules it *would* apply. • **Deploy**: systemd service on Debian host starts the container at boot. • *Hook*: `cue vet` guarantees that no two VLANs share the same ID, no overlapping subnets, etc. 4. Object–FaaS Edge (OM-Edge) • **Object model**: every function is an object (`fn`, `runtime`, `env`, `memory`, `cpu`). • **CUE → Docker trick**: CUE spawns one container per function plus an nginx reverse-proxy container. • **Deploy**: Debian box becomes a mini Lambda—`curl /fn/hello` triggers the container of the moment. • *Hook*: horizontal scale is just changing `replicas: 3` in CUE and re-exporting. 5. Object–Minecraft World (OM-Mine) • **Object model**: world seed, player objects, permission objects, mod objects. • **CUE → Docker trick**: Server container + optional RCON web UI container. • **Deploy**: on Debian; mods are baked into the image hash calculated from the CUE file. • *Hook*: roll back to yesterday’s world by reverting one Git commit to the CUE file and redeploying. 6. Object–CI Matrix (OM-Matrix) • **Object model**: every job, step, runner label, secret ref is an object. • **CUE → Docker trick**: generates a lightweight Drone-CI server + runner containers. • **Deploy**: single `docker compose up` on Debian; self-hosted CI in < 2 min. • *Hook*: matrix expansion (`go: [1.21, 1.22]`) happens in CUE, not in YAML anchors. ------------------------------------------------ Your turn Reply with the **number** you want to pursue (or say “new batch”) and I’ll give: 1. Minimal CUE schema 2. Exact `docker-compose.yml` generator snippet 3. One-liner to run it on a fresh Debian install