Edge computing has revolutionized how we deploy web applications. By running code closer to users, we achieve faster response times and better user experiences. In 2026, the major platforms have converged on V8-based runtimes while differentiating on features and integrations.
Edge computing runs your code at data centers closest to your users
What is Edge Computing?
Edge computing moves computation from centralized servers to locations closer to end users:
Traditional Architecture:
User (Tokyo) → Server (US-East) → Response
Latency: ~200ms
Edge Architecture:
User (Tokyo) → Edge (Tokyo) → Response
Latency: ~20msWhy Edge Matters
| Metric | Traditional | Edge | Improvement |
|---|---|---|---|
| Latency | 100-300ms | 10-50ms | 5-10x |
| Cold Start | 100ms-1s | <5ms | 20x+ |
| Global Performance | Variable | Consistent | N/A |
Platform Comparison
Cloudflare Workers
Best For: Maximum performance, global scale, complex edge logic
Cloudflare Workers use V8 isolates for near-instant cold starts:
// Cloudflare Worker
export default {
async fetch(request, env, ctx) {
const url = new URL(request.url);
// Edge logic - runs in under 5ms cold start
if (url.pathname === '/api/hello') {
return new Response(JSON.stringify({
message: 'Hello from the edge!',
location: request.cf?.city || 'unknown',
country: request.cf?.country || 'unknown',
}), {
headers: { 'Content-Type': 'application/json' },
});
}
return fetch(request);
},
};Key Stats:
- 300+ locations worldwide
- Sub-5ms cold starts
- 95% of world's population within ~50ms
- Unlimited bandwidth (no overage charges)
Cloudflare's global network spans 300+ cities
Vercel Edge Functions
Best For: Next.js applications, developer experience, seamless deployment
// pages/api/geo.ts (Vercel Edge Function)
import { NextRequest } from 'next/server';
export const config = {
runtime: 'edge',
};
export default function handler(req: NextRequest) {
return new Response(JSON.stringify({
city: req.geo?.city,
country: req.geo?.country,
region: req.geo?.region,
}), {
headers: { 'Content-Type': 'application/json' },
});
}Key Stats:
- Deep Next.js integration
- Edge Middleware for request interception
- Edge Config for dynamic configuration
- Generous free tier (100GB bandwidth)
Netlify Edge Functions
Best For: Deno ecosystem, simple edge transformations
// netlify/edge-functions/hello.ts
import type { Context } from "@netlify/edge-functions";
export default async (request: Request, context: Context) => {
const geo = context.geo;
return new Response(`Hello from ${geo.city}, ${geo.country}!`, {
headers: { "content-type": "text/plain" },
});
};
export const config = { path: "/hello" };Key Stats:
- Powered by Deno (modern runtime)
- TypeScript native (no compilation)
- Integrated with Netlify CMS
Performance Benchmarks
Cold Start Comparison
Cold Start Times (P50):
├── Cloudflare Workers: <1ms
├── Vercel Edge Functions: ~5ms
├── Netlify Edge: ~10ms
├── AWS Lambda@Edge: ~100ms
└── Traditional Lambda: ~200-500msGlobal Latency
| Platform | Near Region | Global (P50) | Global (P99) |
|---|---|---|---|
| Cloudflare | 10-30ms | 20-50ms | 100ms |
| Vercel (Pro) | 10-30ms | 30-80ms | 150ms |
| Vercel (Free) | 10-30ms | 50-150ms | 250ms |
| Netlify | 15-40ms | 40-100ms | 200ms |
Use Cases and Patterns
1. Personalization at the Edge
// Personalize content based on user location
export default {
async fetch(request) {
const country = request.cf?.country || 'US';
// Fetch region-specific content
const content = await fetch(
`https://api.example.com/content?region=${country}`
);
// Transform response
const html = await content.text();
const personalizedHtml = html.replace(
'{{GREETING}}',
getGreeting(country)
);
return new Response(personalizedHtml, {
headers: { 'Content-Type': 'text/html' },
});
},
};
function getGreeting(country) {
const greetings = {
'US': 'Hello!',
'JP': 'こんにちは!',
'DE': 'Guten Tag!',
'IN': 'नमस्ते!',
};
return greetings[country] || 'Hello!';
}2. A/B Testing
// Vercel Edge Middleware for A/B testing
import { NextResponse } from 'next/server';
import type { NextRequest } from 'next/server';
export function middleware(request: NextRequest) {
// Check for existing bucket
let bucket = request.cookies.get('ab-bucket')?.value;
if (!bucket) {
// Randomly assign to bucket
bucket = Math.random() < 0.5 ? 'control' : 'variant';
}
// Rewrite to appropriate version
const url = request.nextUrl.clone();
url.pathname = bucket === 'variant'
? `/variant${url.pathname}`
: url.pathname;
const response = NextResponse.rewrite(url);
response.cookies.set('ab-bucket', bucket, { maxAge: 60 * 60 * 24 * 30 });
return response;
}3. Authentication at the Edge
// JWT validation at the edge
import jwt from '@tsndr/cloudflare-worker-jwt';
export default {
async fetch(request, env) {
const authHeader = request.headers.get('Authorization');
if (!authHeader?.startsWith('Bearer ')) {
return new Response('Unauthorized', { status: 401 });
}
const token = authHeader.substring(7);
try {
const isValid = await jwt.verify(token, env.JWT_SECRET);
if (!isValid) {
return new Response('Invalid token', { status: 401 });
}
// Token is valid, proceed to origin
return fetch(request);
} catch (error) {
return new Response('Token verification failed', { status: 401 });
}
},
};4. Image Optimization
// Dynamic image optimization at the edge
export default {
async fetch(request, env) {
const url = new URL(request.url);
if (!url.pathname.startsWith('/images/')) {
return fetch(request);
}
// Get image from origin
const imageUrl = `https://origin.example.com${url.pathname}`;
// Use Cloudflare Image Resizing
return fetch(imageUrl, {
cf: {
image: {
width: parseInt(url.searchParams.get('w') || '800'),
quality: parseInt(url.searchParams.get('q') || '80'),
format: 'auto', // WebP or AVIF if supported
},
},
});
},
};
Edge computing enables real-time image optimization closest to users
Edge Ecosystem Services
Cloudflare
Cloudflare Edge Ecosystem:
├── Workers - Compute
├── KV - Key-value storage
├── D1 - SQLite database
├── R2 - Object storage (S3-compatible)
├── Durable Objects - Stateful coordination
├── Queues - Message queues
├── AI - Machine learning inference
└── Vectorize - Vector databaseVercel
Vercel Edge Ecosystem:
├── Edge Functions - Compute
├── Edge Config - Dynamic configuration
├── KV - Key-value storage
├── Postgres - Database
├── Blob - Object storage
└── AI SDK - LLM integrationCost Comparison
Cloudflare Workers
Pricing (2026):
├── Free tier: 100,000 requests/day
├── Paid: $5/month base
│ ├── 10M requests included
│ └── $0.50 per additional 1M requests
└── Bandwidth: Unlimited (no overage!)Vercel
Pricing (2026):
├── Free tier:
│ ├── 100GB bandwidth
│ └── 100K function invocations
├── Pro: $20/user/month
│ ├── 1TB bandwidth
│ └── 1M invocations
└── Enterprise: CustomCost Example
| Scenario | Cloudflare | Vercel Pro | Netlify Pro |
|---|---|---|---|
| 1M requests | $5 | $20 | $19 |
| 10M requests | $5 | $20 | $25 |
| 100M requests | $50 | Custom | Custom |
Best Practices
1. Keep Edge Functions Lean
// Good: Simple, fast edge logic
export default {
async fetch(request) {
// Quick decision-making
const path = new URL(request.url).pathname;
if (path === '/api/health') {
return new Response('OK');
}
return fetch(request);
},
};
// Avoid: Heavy computation at edge
export default {
async fetch(request) {
// Don't do this at the edge
const result = heavyComputation(data);
return new Response(result);
},
};2. Use Appropriate Storage
// Use KV for read-heavy data
const value = await env.MY_KV.get('key');
// Use Durable Objects for coordination
const id = env.COUNTER.idFromName('global');
const counter = env.COUNTER.get(id);
// Use R2/Blob for large files
const object = await env.BUCKET.get('large-file.pdf');3. Cache Strategically
// Cloudflare caching
export default {
async fetch(request, env, ctx) {
const cacheKey = new Request(request.url, request);
const cache = caches.default;
// Check cache
let response = await cache.match(cacheKey);
if (!response) {
response = await fetch(request);
// Clone and cache
ctx.waitUntil(cache.put(cacheKey, response.clone()));
}
return response;
},
};When to Use Each Platform
Choose Cloudflare When:
- Maximum performance is critical
- High-traffic applications
- Complex edge logic required
- Cost optimization at scale
- Using other Cloudflare services
Choose Vercel When:
- Building with Next.js
- Developer experience is priority
- Need tight framework integration
- Preview deployments are important
- Team collaboration features needed
Choose Netlify When:
- Using Deno/TypeScript native
- Simpler deployment needs
- JAMstack architecture
- Content-focused sites
The Future: Convergence
By 2026, major platforms are converging on V8-like edge runtimes. The differentiators are:
- Ecosystem integration - Storage, databases, AI
- Developer experience - Tooling, debugging, deployment
- Pricing models - Free tiers, scaling costs
- Geographic coverage - Number and location of edges
Resources
- Cloudflare Workers Docs
- Vercel Edge Functions
- Netlify Edge Functions
- DEV: Edge Performance Truth 2026
Need help architecting an edge-first application? Contact CODERCOPS for expert guidance.
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