Vercel rate limits
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'Handle Vercel API rate limits, implement retry logic, and configure WAF rate limiting.
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SKILL.md
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Vercel Rate Limits
Overview
Handle Vercel REST API rate limits with proper retry logic, and configure Vercel's WAF rate limiting SDK to protect your deployed API endpoints from abuse. Covers both consuming the Vercel API (outbound) and protecting your own functions (inbound).
Prerequisites
- Vercel CLI installed and authenticated
- Understanding of HTTP 429 status codes
- For WAF rate limiting: Vercel Pro or Enterprise plan
Instructions
Step 1: Vercel REST API Rate Limits
The Vercel REST API enforces rate limits per endpoint. When exceeded, the API returns HTTP 429 with rate limit headers:
HTTP/1.1 429 Too Many Requests
X-RateLimit-Limit: 100
X-RateLimit-Remaining: 0
X-RateLimit-Reset: 1711152000
Retry-After: 60
Known API limits:
| Endpoint Category | Rate Limit |
|---|---|
| Deployments (create) | 100/hour per project |
| Deployments (list/get) | 500/min |
| Projects (CRUD) | 200/min |
| Environment variables | 200/min |
| Domains | 200/min |
| Teams | 200/min |
| DNS records | 200/min |
| General API | 120 requests/min (default) |
Step 2: Implement Retry with Backoff for Vercel API
// lib/rate-limit-handler.ts
interface RateLimitInfo {
limit: number;
remaining: number;
reset: number; // Unix timestamp
}
function parseRateLimitHeaders(headers: Headers): RateLimitInfo {
return {
limit: Number(headers.get('X-RateLimit-Limit') ?? 100),
remaining: Number(headers.get('X-RateLimit-Remaining') ?? 100),
reset: Number(headers.get('X-RateLimit-Reset') ?? 0),
};
}
async function vercelFetchWithRetry(
url: string,
options: RequestInit,
maxRetries = 3
): Promise<Response> {
for (let attempt = 0; attempt <= maxRetries; attempt++) {
const res = await fetch(url, options);
if (res.status !== 429) return res;
if (attempt === maxRetries) {
throw new Error(`Rate limited after ${maxRetries} retries: ${url}`);
}
// Use Retry-After header if present, otherwise exponential backoff
const retryAfter = res.headers.get('Retry-After');
const waitMs = retryAfter
? Number(retryAfter) * 1000
: Math.min(1000 * Math.pow(2, attempt) + Math.random() * 1000, 30000);
console.warn(`Rate limited (attempt ${attempt + 1}/${maxRetries}). Waiting ${Math.round(waitMs)}ms...`);
await new Promise(r => setTimeout(r, waitMs));
}
throw new Error('Unreachable');
}
Step 3: Proactive Rate Limit Avoidance
// lib/rate-limiter.ts
// Track remaining quota and slow down before hitting the wall
class VercelRateLimiter {
private remaining = 100;
private resetAt = 0;
async throttle(): Promise<void> {
// If near the limit, wait until reset
if (this.remaining < 5) {
const waitMs = Math.max(0, this.resetAt * 1000 - Date.now()) + 1000;
console.warn(`Near rate limit (${this.remaining} remaining). Waiting ${waitMs}ms...`);
await new Promise(r => setTimeout(r, waitMs));
}
}
update(headers: Headers): void {
this.remaining = Number(headers.get('X-RateLimit-Remaining') ?? this.remaining);
this.resetAt = Number(headers.get('X-RateLimit-Reset') ?? this.resetAt);
}
}
Step 4: Protect Your Own Endpoints — Vercel WAF Rate Limiting
Vercel's WAF provides built-in rate limiting for your deployed functions:
// middleware.ts — WAF rate limiting via Vercel Firewall SDK
import { ipAddress } from '@vercel/functions';
import { checkRateLimit } from '@vercel/firewall';
export async function middleware(request: Request) {
const ip = ipAddress(request) ?? '127.0.0.1';
// Rate limit: 100 requests per 60 seconds per IP
const { rateLimited } = await checkRateLimit('api-limit', {
key: ip,
limit: 100,
window: '60s',
});
if (rateLimited) {
return new Response(
JSON.stringify({ error: 'Too many requests. Please try again later.' }),
{ status: 429, headers: { 'Content-Type': 'application/json', 'Retry-After': '60' } }
);
}
}
export const config = {
matcher: '/api/:path*',
};
Install: npm install @vercel/firewall @vercel/functions
Step 5: Custom Rate Limiting with Edge Config
// api/rate-limited-endpoint.ts
import { get } from '@vercel/edge-config';
export const config = { runtime: 'edge' };
// Simple in-memory sliding window (per-isolate, not global)
const windowMs = 60_000;
const maxRequests = 50;
const requests = new Map<string, number[]>();
function isRateLimited(key: string): boolean {
const now = Date.now();
const timestamps = (requests.get(key) ?? []).filter(t => now - t < windowMs);
timestamps.push(now);
requests.set(key, timestamps);
return timestamps.length > maxRequests;
}
export default async function handler(request: Request): Promise<Response> {
const ip = request.headers.get('x-forwarded-for') ?? 'unknown';
if (isRateLimited(ip)) {
return Response.json({ error: 'Rate limit exceeded' }, { status: 429 });
}
return Response.json({ data: 'ok' });
}
Platform Concurrency Limits
| Plan | Concurrent Executions | Builds/Hour |
|---|---|---|
| Hobby | 10 | 32 |
| Pro | 1,000 | 6,000/day |
| Enterprise | 100,000 | Custom |
Output
- Vercel API calls wrapped with automatic retry and backoff
- Rate limit headers parsed and monitored proactively
- WAF rate limiting protecting deployed API endpoints
- Custom per-IP rate limiting for fine-grained control
Error Handling
| Error | Cause | Solution |
|---|---|---|
429 Too Many Requests | API rate limit exceeded | Use vercelFetchWithRetry() wrapper |
FUNCTION_THROTTLED | Concurrent execution limit hit | Reduce parallelism or upgrade plan |
| Rate limit not applied | Middleware not matching routes | Check config.matcher pattern |
| In-memory rate limit resets | Edge function isolate recycled | Use Redis or Vercel KV for persistent state |
Resources
Next Steps
For security best practices, see vercel-security-basics.