Architecture & Design Patterns - Cloudflare Experiments

All experiments follow consistent architectural patterns and design principles. This guide explains the shared architecture, tech stack, and best practices used throughout the repository.

Tech Stack

Every experiment uses a consistent, modern tech stack optimized for edge computing:

Core Technologies

TypeScript

Strictly typed codebase with full type safety.All experiments use TypeScript with:

Strict mode enabled
No any types
Full type coverage
tsconfig.json per experiment

Environment bindings are typed in src/types/env.d.ts.

Hono

Fast, lightweight web framework for Cloudflare Workers.Benefits:

Ultra-small bundle size (~12KB)
Type-safe routing
Middleware support
Web standard APIs
Built for edge runtime

Used for routing in all experiments.

Cloudflare Workers

Serverless runtime at the edge.Features:

V8 isolate-based execution
Standard Web APIs
Sub-millisecond cold starts
Global deployment
Zero configuration scaling

Wrangler

CLI tool for Workers development and deployment.Used for:

Local development (wrangler dev)
Deployment (wrangler deploy)
Resource management (D1, KV, R2)
Secret management

Project Structure

Every experiment follows an identical directory structure for consistency:

experiments/<name>/
├── src/
│   ├── index.ts          # Entry point - Hono app, route mounting, error handler
│   ├── routes/           # Route handlers (one file per route or logical group)
│   ├── lib/              # Business logic (fetch, parsing, validation)
│   ├── utils/            # Shared utilities (response helpers, formatters)
│   ├── constants/        # Configuration and constants
│   └── types/            # TypeScript types and interfaces
│       └── env.d.ts      # Worker environment bindings
├── migrations/           # Database migrations (D1 experiments only)
├── package.json          # Dependencies and scripts
├── wrangler.json         # Worker configuration and bindings
├── tsconfig.json         # TypeScript configuration
└── README.md             # Experiment documentation

Key Principles

Single Responsibility: One experiment demonstrates one Cloudflare feature
No Shared Code: Each experiment is completely independent
Consistent Structure: Same directory layout across all experiments
Type Safety: Full TypeScript coverage with strict mode

Common Patterns

Experiments implement several recurring architectural patterns:

1. Fetch + Parse Pattern

Fetch external content and extract structured data. Used in: Dependency Analyzer, Website Metadata Extractor, Website DevTools Inspector

// src/routes/analyze.ts
import { Hono } from "hono";
import { validateUrl } from "../lib/url";
import { fetchHtml } from "../lib/fetch";
import { parseDependencies } from "../lib/parse";
import { jsonError, jsonSuccess } from "../utils/response";

const app = new Hono<{ Bindings: Env }>();

app.get("/analyze", async (c) => {
  // 1. Validate input
  const url = validateUrl(c.req.query("url"));
  if (!url) return jsonError(c, "Missing or invalid url", "INVALID_URL");

  try {
    // 2. Fetch content
    const html = await fetchHtml(url);
    
    // 3. Parse and extract
    const data = parseDependencies(html, url);
    
    // 4. Return structured response
    return jsonSuccess(c, data);
  } catch (e) {
    const message = e instanceof Error ? e.message : "Failed to fetch";
    return jsonError(c, message, "FETCH_ERROR", 502);
  }
});

Pattern Flow:

Validate user input (URL)
Fetch external content
Parse/extract data with regex or HTMLRewriter
Return JSON response
Handle errors consistently

2. AI Integration Pattern

Fetch content, extract text, and process with Workers AI. Used in: AI Website Summary, GitHub Repo Explainer

// src/routes/summary.ts
import { Hono } from "hono";
import { validateUrl } from "../lib/url";
import { fetchHtml } from "../lib/fetch";
import { getTitle, getBodyText } from "../lib/html";
import { summarizeWithAi } from "../lib/ai";
import { jsonSuccess, jsonError } from "../utils/response";

const app = new Hono<{ Bindings: Env }>();

app.get("/summary", async (c) => {
  const url = validateUrl(c.req.query("url"));
  if (!url) return jsonError(c, "Missing or invalid url", "INVALID_URL");

  try {
    // 1. Fetch HTML
    const html = await fetchHtml(url);
    
    // 2. Extract text content
    const title = getTitle(html);
    const bodyText = getBodyText(html, 6000);
    
    if (!bodyText.trim()) {
      return jsonSuccess(c, { title, summary: "No content." });
    }
    
    // 3. Summarize with AI
    const summary = await summarizeWithAi(c.env, bodyText, title);
    
    // 4. Return result
    return jsonSuccess(c, { title, summary });
  } catch (e) {
    const message = e instanceof Error ? e.message : "Failed";
    return jsonError(c, message, "FETCH_OR_AI_ERROR", 502);
  }
});

AI Helper Example:

// src/lib/ai.ts
import type { Env } from "../types/env";

export async function summarizeWithAi(
  env: Env,
  text: string,
  title: string | null
): Promise<string> {
  const prompt = `Summarize the following webpage content.\n\nTitle: ${title || "N/A"}\n\nContent:\n${text}`;
  
  const response = await env.AI.run("@cf/meta/llama-3-8b-instruct", {
    messages: [
      { role: "system", content: "You are a helpful assistant." },
      { role: "user", content: prompt },
    ],
  });
  
  return response.response || "Unable to generate summary.";
}

Pattern Flow:

Fetch external content
Extract relevant text (limit to model context)
Send to Workers AI with structured prompt
Return AI response

3. Browser Automation Pattern

Use headless browser to interact with pages. Used in: Screenshot API

// src/routes/screenshot.ts
import { Hono } from "hono";
import puppeteer from "@cloudflare/puppeteer";
import { validateUrl } from "../lib/url";
import { jsonError } from "../utils/response";
import { DEFAULT_VIEWPORT, NAVIGATION_TIMEOUT_MS } from "../constants/defaults";

const app = new Hono<{ Bindings: Env }>();

app.get("/screenshot", async (c) => {
  const url = validateUrl(c.req.query("url"));
  if (!url) return jsonError(c, "Missing or invalid url", "INVALID_URL");

  let browser = null;
  try {
    // 1. Launch browser
    browser = await puppeteer.launch(c.env.BROWSER);
    
    // 2. Create page and configure
    const page = await browser.newPage();
    await page.setViewport(DEFAULT_VIEWPORT);
    
    // 3. Navigate and wait
    await page.goto(url, {
      waitUntil: "networkidle0",
      timeout: NAVIGATION_TIMEOUT_MS,
    });
    
    // 4. Capture screenshot
    const png = await page.screenshot({ type: "png" });
    
    // 5. Clean up
    await browser.close();
    browser = null;

    // 6. Return image
    return new Response(png, {
      headers: {
        "Content-Type": "image/png",
        "Cache-Control": "public, max-age=60",
      },
    });
  } catch (e) {
    if (browser) try { await browser.close(); } catch { /* ignore */ }
    const message = e instanceof Error ? e.message : "Screenshot failed";
    return jsonError(c, message, "SCREENSHOT_ERROR", 502);
  }
});

Pattern Flow:

Launch browser session
Configure viewport and navigation options
Navigate to URL and wait for load
Perform action (screenshot, scraping, etc.)
Always close browser (cleanup)
Return binary or JSON response

4. Storage Pattern (D1 + KV)

Combine D1 (primary) with KV (cache) for optimal performance. Used in: Link Shortener

// src/routes/redirect.ts
import { Hono } from "hono";
import type { Env } from "../types/env";
import { jsonError } from "../utils/response";

const app = new Hono<{ Bindings: Env }>();

app.get("/:code", async (c) => {
  const code = c.req.param("code");

  // 1. Try KV cache first (fast read)
  let url = await c.env.LINKS_CACHE.get(code);
  
  if (!url) {
    // 2. Cache miss - read from D1 (source of truth)
    const row = await c.env.DB.prepare(
      "SELECT url FROM links WHERE code = ?"
    ).bind(code).first<{ url: string }>();
    
    if (!row) {
      return jsonError(c, "Link not found", "NOT_FOUND", 404);
    }
    
    url = row.url;
    
    // 3. Populate cache for future requests
    await c.env.LINKS_CACHE.put(code, url);
  }

  // 4. Redirect
  return c.redirect(url, 302);
});

Storage Strategy:

D1: Source of truth, handles writes and cache misses
KV: Read-through cache, optimized for redirects
Pattern: Read from KV → Miss → Read D1 → Cache in KV → Return

5. Object Storage Pattern

Public and private R2 buckets with direct access. Used in: R2 Storage

// src/routes/object.ts
import { Hono } from "hono";
import type { Env } from "../types/env";

const app = new Hono<{ Bindings: Env }>();

app.put("/object", async (c) => {
  const key = c.req.query("key");
  const isPublic = c.req.query("public") === "true";
  
  if (!key) return c.json({ error: "Missing key" }, 400);

  // Choose bucket based on public flag
  const bucket = isPublic ? c.env.PUBLIC_BUCKET : c.env.BUCKET;
  
  // Upload object
  await bucket.put(key, c.req.raw.body, {
    httpMetadata: {
      contentType: c.req.header("Content-Type") || "application/octet-stream",
    },
  });
  
  // Generate public URL if applicable
  const response: any = { key, uploaded: true };
  if (isPublic && c.env.PUBLIC_BUCKET_URL) {
    response.url = `${c.env.PUBLIC_BUCKET_URL}/${key}`;
  }
  
  return c.json(response);
});

Storage Strategy:

Private bucket: Objects only accessible via Worker
Public bucket: Direct URLs for CDN delivery
Pattern: Choose bucket → Upload → Return URL (public) or key (private)

Error Handling

Consistent error handling across all experiments:

Response Utilities

// src/utils/response.ts
import type { Context } from "hono";

export function jsonSuccess<T>(c: Context, data: T) {
  return c.json(data);
}

export function jsonError(
  c: Context,
  message: string,
  code: string,
  status: number = 400
) {
  return c.json({ error: message, code }, status);
}

Global Error Handler

Every experiment registers a global error handler:

// src/index.ts
import { Hono } from "hono";
import type { Env } from "./types/env";
import routes from "./routes/...";

const app = new Hono<{ Bindings: Env }>();

app.route("/", routes);

app.get("/", (c) => {
  return c.json({
    name: "experiment-name",
    description: "What this experiment does",
    usage: "GET /endpoint?param=value",
  });
});

// Global error handler for uncaught errors
app.onError((err, c) => {
  return c.json({ error: err.message, code: "INTERNAL_ERROR" }, 500);
});

export default { fetch: app.fetch };

Error Codes

Standardized error codes used across experiments:

Code	Status	Description
`INVALID_URL`	400	Missing or malformed URL parameter
`INVALID_INPUT`	400	Invalid request body or parameters
`NOT_FOUND`	404	Resource not found (links, objects)
`FETCH_ERROR`	502	Failed to fetch external resource
`PARSE_ERROR`	502	Failed to parse HTML or response
`AI_ERROR`	502	Workers AI inference failed
`SCREENSHOT_ERROR`	502	Browser Rendering failed
`DATABASE_ERROR`	500	D1 query failed
`STORAGE_ERROR`	500	KV or R2 operation failed
`INTERNAL_ERROR`	500	Uncaught/unexpected error

Validation

Input validation is critical for security and reliability:

URL Validation

// src/lib/url.ts
export function validateUrl(input: string | undefined): string | null {
  if (!input) return null;
  
  try {
    const url = new URL(input);
    // Only allow HTTP and HTTPS
    if (url.protocol !== "http:" && url.protocol !== "https:") {
      return null;
    }
    return url.toString();
  } catch {
    return null;
  }
}

export function resolveUrl(base: string, href: string): string {
  try {
    return new URL(href, base).toString();
  } catch {
    return href;
  }
}

Request Body Validation

// src/routes/shorten.ts
app.post("/shorten", async (c) => {
  let body: any;
  
  try {
    body = await c.req.json();
  } catch {
    return jsonError(c, "Invalid JSON", "INVALID_INPUT");
  }
  
  const url = validateUrl(body?.url);
  if (!url) {
    return jsonError(c, "Missing or invalid url in body", "INVALID_URL");
  }
  
  // Proceed with validated input
});

HTML Parsing

Experiments use regex-based parsing for lightweight HTML extraction:

// src/lib/parse.ts
function extractScripts(html: string): string[] {
  const urls: string[] = [];
  const re = /<script[^>]+src=["']([^"']+)["']/gi;
  let m: RegExpExecArray | null;
  while ((m = re.exec(html)) !== null) {
    urls.push(m[1].trim());
  }
  return urls;
}

function getTitle(html: string): string | null {
  const m = html.match(/<title[^>]*>([\s\S]*?)<\/title>/i);
  return m ? m[1].replace(/<[^>]+>/g, "").trim() || null : null;
}

function getMeta(html: string, name: string): string | null {
  const re = new RegExp(
    `<meta[^>]+name=["']${name}["'][^>]+content=["']([^"']*)["']`,
    "i"
  );
  const m = html.match(re);
  return m ? m[1].trim() || null : null;
}

Why Regex Instead of DOM Parser?

Lower memory overhead
Faster for simple extraction
No need for full DOM representation
Works well at the edge with streaming

Configuration

Configuration is managed via wrangler.json and environment variables:

wrangler.json Structure

{
  "name": "experiment-name",
  "main": "src/index.ts",
  "compatibility_date": "2024-01-01",
  "node_compat": true,
  
  "vars": {
    "PUBLIC_URL": "https://example.com"
  },
  
  "ai": {
    "binding": "AI"
  },
  
  "browser": {
    "binding": "BROWSER"
  },
  
  "d1_databases": [
    {
      "binding": "DB",
      "database_name": "my-database",
      "database_id": "00000000-0000-0000-0000-000000000000"
    }
  ],
  
  "kv_namespaces": [
    {
      "binding": "CACHE",
      "id": "00000000000000000000000000000000"
    }
  ],
  
  "r2_buckets": [
    {
      "binding": "BUCKET",
      "bucket_name": "my-bucket"
    }
  ]
}

Environment Bindings

Type bindings in src/types/env.d.ts:

export interface Env {
  // AI binding
  AI?: Ai;
  
  // Browser binding
  BROWSER?: Fetcher;
  
  // D1 database
  DB?: D1Database;
  
  // KV namespace
  CACHE?: KVNamespace;
  
  // R2 bucket
  BUCKET?: R2Bucket;
  PUBLIC_BUCKET?: R2Bucket;
  
  // Environment variables
  PUBLIC_BUCKET_URL?: string;
}

Performance Optimization

Experiments follow edge-optimized performance patterns:

1. Minimize Latency

Use edge-native APIs (fetch, KV)
Stream responses when possible
Avoid buffering large payloads

2. Optimize Cold Starts

Keep bundle size small (Hono ~12KB)
Minimal dependencies
Tree-shaking via esbuild

3. Cache Effectively

Use KV for read-heavy data
Set appropriate Cache-Control headers
Leverage Cloudflare’s CDN

4. Handle Timeouts

Set reasonable fetch timeouts
Browser navigation timeouts
Graceful degradation

Security Best Practices

Input Validation

Always validate user input:

URL format and protocol
JSON structure
Parameter types and ranges

Error Messages

Never expose internal details:

Generic error messages for users
Specific errors logged internally
No stack traces in responses

Rate Limiting

Protect against abuse:

Cloudflare Rate Limiting rules
Per-IP limits
Per-endpoint limits

Secret Management

Store secrets securely:

Use Wrangler secrets (encrypted)
Never commit secrets to git
Rotate keys regularly

Testing Strategy

Test experiments locally before deployment:

# Type checking
npm run build
# or: tsc --noEmit

# Local development
npm run dev

# Remote testing (for AI, Browser, R2)
npm run dev -- --remote

# Manual endpoint testing
curl http://localhost:8787/endpoint?param=value

Next Steps

Cloudflare Features

Learn about platform features used in experiments

Deployment Guide

Deploy experiments to production

Contributing

Add your own experiment to the repository

Resources

​Tech Stack

​Core Technologies

TypeScript

Hono

Cloudflare Workers

Wrangler

​Project Structure

​Key Principles

​Common Patterns

​1. Fetch + Parse Pattern

​2. AI Integration Pattern

​3. Browser Automation Pattern

​4. Storage Pattern (D1 + KV)

​5. Object Storage Pattern

​Error Handling

​Response Utilities

​Global Error Handler

​Error Codes

​Validation

​URL Validation

​Request Body Validation

​HTML Parsing

​Configuration

​wrangler.json Structure

​Environment Bindings

​Performance Optimization

​1. Minimize Latency

​2. Optimize Cold Starts

​3. Cache Effectively

​4. Handle Timeouts

​Security Best Practices

Input Validation

Error Messages

Rate Limiting

Secret Management

​Testing Strategy

​Next Steps

Cloudflare Features

Deployment Guide

Contributing

Tech Stack

Core Technologies

Project Structure

Key Principles

Common Patterns

1. Fetch + Parse Pattern

2. AI Integration Pattern

3. Browser Automation Pattern

4. Storage Pattern (D1 + KV)

5. Object Storage Pattern

Error Handling

Response Utilities

Global Error Handler

Error Codes

Validation

URL Validation

Request Body Validation

HTML Parsing

Configuration

wrangler.json Structure

Environment Bindings

Performance Optimization

1. Minimize Latency

2. Optimize Cold Starts

3. Cache Effectively

4. Handle Timeouts

Security Best Practices

Testing Strategy

Next Steps