the_information_nexus/tech_docs/CUE_your_new_friend.md

The Complete Technical Guide to CUE (Configure-Unify-Execute)

A structured, practical, and comprehensive introduction to CUE—covering core concepts, real-world applications, and best practices.

---

1. Introduction to CUE

What is CUE?

CUE (Configure-Unify-Execute) is an open-source data constraint language developed at Google. It is designed for:

• Configuration management (Kubernetes, Terraform, CI/CD)
• Data validation (API schemas, input sanitization)
• Code generation (Dockerfiles, Kubernetes manifests, SQL schemas)
• Policy enforcement (security rules, compliance checks)

Unlike YAML/JSON, CUE merges types, values, and constraints into a single model, enabling deterministic, reproducible configurations.

Why CUE Over Alternatives?

Tool	Strengths	Weaknesses vs. CUE
YAML	Human-readable, widely used	No validation, no logic, fragile
Jsonnet	Templating, code reuse	Slower, no built-in validation
HCL	Terraform integration	Less flexible for non-TF use
Pulumi	Full programming model	Complex, runtime-dependent
CUE	Validation + unification	Steeper initial learning curve

---

2. Core Concepts

The CUE Lattice

CUE’s power comes from its lattice structure, where:

• _ (Top): Accepts any value (e.g., string, int, {}).
• _|_ (Bottom): An invalid/conflicting value (error state).
• Unification (&) combines constraints (like logical AND).
• Disjunction (|) allows alternatives (like logical OR).

Example:

#Schema: {
    name:  string & =~"^[A-Z][a-z]+$"  // Must start with uppercase
    age:   int & >0 & <120             // Age between 0 and 120
    role?: "admin" | "user"            // Optional role
}

valid: #Schema & { name: "Alice", age: 30 }  // ✅ Valid
invalid: #Schema & { name: "alice", age: 150 }  // ❌ Fails (name, age)

---

3. Getting Started

Installation

# Install CUE
brew install cue-lang/tap/cue  # macOS
sudo apt-get install cue       # Debian/Ubuntu
go install cuelang.org/go/cmd/cue@latest  # Go users

# Verify
cue version

Basic Workflow

1. Define schemas (.cue files).
2. Validate data (cue vet).
3. Export to JSON/YAML (cue export).

Example:

// schema.cue
#Person: {
    name: string
    age:  int & >=18
}

// data.json
{ "name": "Bob", "age": 25 }

# Validate
cue vet schema.cue data.json  # ✅ Passes

---

4. Real-World Use Cases

Case 1: Kubernetes Configuration

Problem: YAML files are brittle and hard to validate.
Solution: Define a reusable schema.

// k8s.cue
#Deployment: {
    apiVersion: "apps/v1"
    kind:       "Deployment"
    metadata: name: string
    spec: {
        replicas: int & >=1
        template: spec: containers: [{
            name:  string
            image: string & =~".+:.+"
        }]
    }
}

myapp: #Deployment & {
    metadata: name: "webapp"
    spec: replicas: 3
    spec: template: spec: containers: [{ name: "app", image: "nginx:latest" }]
}

# Export to YAML
cue export k8s.cue -e myapp --out yaml > deploy.yaml

Case 2: Terraform Guardrails

Problem: Prevent invalid cloud configurations.
Solution: Enforce AWS/GCP policies.

#AWS: {
    region: "us-east-1" | "us-west-2"
    instanceType: "t2.micro" | "t3.medium"
}

my_vm: #AWS & {
    region: "us-east-1"
    instanceType: "t2.micro"  # ✅ Valid
}

invalid_vm: #AWS & {
    region: "eu-west-1"  # ❌ Fails (invalid region)
}

Case 3: CI/CD Pipeline-as-Code

Problem: YAML-based pipelines are hard to maintain.
Solution: Define pipelines in CUE.

#Pipeline: {
    steps: [...{
        name: string
        cmd:  string
    }]
}

my_pipeline: #Pipeline & {
    steps: [
        { name: "build", cmd: "go build" },
        { name: "test",  cmd: "go test" },
    ]
}

# Generate GitHub Actions YAML
cue export pipeline.cue --out yaml > .github/workflows/ci.yml

---

5. Debugging & Best Practices

Debugging Unification Errors

• Use cue eval -v to trace unification steps.
• Check for _|_ (bottom) in output—indicates conflicts.

Best Practices

1. Modularize: Split schemas into files (schemas/, configs/).
2. Reuse: Leverage CUE’s import system (import "acme.com/schemas").
3. Validate Early: Run cue vet in CI/CD.

---

6. Advanced Topics

Go + CUE Integration

Embed CUE in Go programs for dynamic validation:

package main

import (
	"cuelang.org/go/cue/cuecontext"
	"fmt"
)

func main() {
	ctx := cuecontext.New()
	schema := ctx.CompileString(`
		#Person: {
			name: string
			age:  int & >=18
		}`)
	data := ctx.CompileString(`{ name: "Alice", age: 30 }`)

	unified := schema.Unify(data)
	if err := unified.Validate(); err != nil {
		fmt.Println("Validation failed:", err)
	} else {
		fmt.Println("Valid!")
	}
}

Generating Code

Convert CUE to:

• OpenAPI: cue export --out openapi
• Go Structs: cue get go
• SQL: Use templates (text/template).

---

7. Learning Resources

• Official Docs: cuelang.org
• Playground: cuelang.org/play
• Community: CUE Slack

---

Conclusion

CUE replaces ad-hoc YAML/JSON with structured, validated, and reusable configurations. By mastering:

1. Lattice logic (unification, constraints),
2. Real-world workflows (K8s, Terraform, CI/CD),
3. Tooling integration (Go, OpenAPI),

You can eliminate configuration errors and enforce policies declaratively.

Next Step: Try the CUE Tutorial or experiment in the playground! 🚀