# **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:**  
```cue
#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**  
```bash
# 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:**  
```cue
// 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.  

```cue
// 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.  

```cue
#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.  

```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:  
```go
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](https://cuelang.org/)  
- **Playground**: [cuelang.org/play](https://cuelang.org/play)  
- **Community**: [CUE Slack](https://cuelang.slack.com/)  

---

## **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](https://cuelang.org/docs/tutorials/) or experiment in the **playground**! 🚀


Here’s a **Mermaid.js diagram** that visually explains the CUE lattice (Top, Bottom, Unification, and Disjunction) in a way that’s both accurate and appealing for visual learners. You can embed this directly in your Gitea Markdown files (if Mermaid rendering is enabled):

```mermaid
%% CUE Lattice Diagram
graph TD
    A["⊤ (Top)"] --> B["Concrete Values"]
    A --> C["Constraints"]
    B --> D["Unification (&)"]
    C --> D
    D --> E["Valid Output"]
    D --> F["⊥ (Bottom, Invalid)"]
    B --> G["Disjunction (|)"]
    C --> G
    G --> H["Valid Alternative"]

    style A fill:#4CAF50,stroke:#388E3C
    style F fill:#F44336,stroke:#D32F2F
    style E fill:#2196F3,stroke:#1976D2
    style H fill:#FF9800,stroke:#F57C00

    %% Examples
    I["Example:\nname: string & =~'^[A-Z]'"] --> D
    J["Example:\nrole: 'admin' | 'user'"] --> G
```

---

### **How to Use in Gitea**:
1. Ensure Mermaid is enabled in your Gitea instance (check with admins).
2. Paste the above code into a Markdown file (e.g., `README.md`).
3. It will render as an interactive diagram.

---

### **Diagram Explanation**:
1. **`⊤ (Top)`**  
   - The root of all possible values (e.g., `string`, `int`, `{}`).  
   - Branches into **concrete values** (like `"Alice"`) and **constraints** (like `>=18`).

2. **Unification (`&`)**  
   - Merges constraints (like a strict AND gate).  
   - Outputs either a **valid value** (if constraints are met) or **`⊥` (Bottom)** (if conflicts exist).

3. **Disjunction (`|`)**  
   - Represents alternatives (like a flexible OR gate).  
   - Outputs the **first valid alternative** (e.g., `"admin" | "user"`).

4. **`⊥ (Bottom)`**  
   - The "error state" (e.g., `name: 42` when `string` is required).

---

### **Why This Works**:
- **Visualizes the Lattice**: Shows how CUE narrows possibilities from `⊤` to valid outputs.
- **Color-Coded**: Green (Top), Blue (Valid), Red (Error), Orange (Alternatives).
- **Includes Examples**: Embedded real CUE snippets for clarity.

---

### **Alternate Version (Simpler)**:
If you prefer a minimalistic view:
```mermaid
graph LR
    T["⊤ (Any Value)"] -->|Unification (&)| U["Valid"]
    T -->|Conflict| B["⊥ (Invalid)"]
    T -->|Disjunction (|)| D["A | B | C"]
```

Let me know if you'd like to tweak the design (e.g., add more examples, change layouts)!