Vercel Functions

Vercel Functions

You are an expert in Vercel Functions — the compute layer of the Vercel platform.

Function Types

Serverless Functions (Node.js)

• Full Node.js runtime, all npm packages available
• Default for Next.js API routes, Server Actions, Server Components
• Cold starts: 800ms–2.5s (with DB connections)
• Max duration: 10s (Hobby), 300s (Pro default), 800s (Fluid Compute Pro/Enterprise)

// app/api/hello/route.ts
export async function GET() {
  return Response.json({ message: 'Hello from Node.js' })
}

Edge Functions (V8 Isolates)

• Lightweight V8 runtime, Web Standard APIs only
• Ultra-low cold starts (<1ms globally)
• Limited API surface (no full Node.js)
• Best for: auth checks, redirects, A/B testing, simple transformations

// app/api/hello/route.ts
export const runtime = 'edge'

export async function GET() {
  return new Response('Hello from the Edge')
}

Bun Runtime (Public Beta)

Add "bunVersion": "1.x" to vercel.json to run Node.js functions on Bun instead. ~28% lower latency for CPU-bound workloads. Supports Next.js, Express, Hono, Nitro.

Rust Runtime (Public Beta)

Rust functions run on Fluid Compute with HTTP streaming and Active CPU pricing. Built on the community Rust runtime. Supports environment variables up to 64 KB.

Node.js 24 LTS

Node.js 24 LTS is now GA on Vercel for both builds and functions. Features V8 13.6, global URLPattern, Undici v7 for faster fetch(), and npm v11.

Choosing Runtime

Need	Runtime	Why
Full Node.js APIs, npm packages	nodejs	Full compatibility
Lower latency, CPU-bound work	nodejs + Bun	~28% latency reduction
Ultra-low latency, simple logic	edge	<1ms cold start, global
Database connections, heavy deps	nodejs	Edge lacks full Node.js
Auth/redirect at the edge	edge	Fastest response
AI streaming	Either	Both support streaming
Systems-level performance	rust (beta)	Native speed, Fluid Compute

Fluid Compute

Fluid Compute is the unified execution model for all Vercel Functions (both Node.js and Edge).

Key benefits:

• Optimized concurrency: Multiple invocations on a single instance — up to 85% cost reduction for high-concurrency workloads
• Extended durations: Default 300s for all plans; up to 800s on Pro/Enterprise
• Active CPU pricing: Charges only while CPU is actively working, not during idle/await time. Enabled by default for all plans. Memory-only periods billed at a significantly lower rate.
• Background processing: waitUntil / after for post-response tasks
• Dynamic scaling: Automatic during traffic spikes
• Bytecode caching: Reduces cold starts via Rust-based runtime with pre-compiled function code
• Multi-region failover: Default for Enterprise when Fluid is activated

Instance Sizes

Size	CPU	Memory
Standard (default)	1 vCPU	2 GB
Performance	2 vCPU	4 GB

Hobby projects use Standard CPU. The Basic CPU instance has been removed.

Background Processing with waitUntil

// Continue work after sending response
import { waitUntil } from '@vercel/functions'

export async function POST(req: Request) {
  const data = await req.json()

  // Send response immediately
  const response = Response.json({ received: true })

  // Continue processing in background
  waitUntil(async () => {
    await processAnalytics(data)
    await sendNotification(data)
  })

  return response
}

Next.js after (equivalent)

import { after } from 'next/server'

export async function POST(req: Request) {
  const data = await req.json()

  after(async () => {
    await logToAnalytics(data)
  })

  return Response.json({ ok: true })
}

Streaming

Zero-config streaming on both runtimes, including Server-Sent Events (SSE). Essential for AI applications.

You do NOT need runtime = 'edge' for streaming or SSE. Streaming responses (ReadableStream, text/event-stream) work on the default Node.js runtime — this is a common misconception. Stay on Node.js (Fluid Compute) so you keep full Node.js APIs, npm packages, and longer durations; Edge offers no streaming advantage here.

export async function POST(req: Request) {
  const encoder = new TextEncoder()
  const stream = new ReadableStream({
    async start(controller) {
      for (const chunk of data) {
        controller.enqueue(encoder.encode(chunk))
        await new Promise(r => setTimeout(r, 100))
      }
      controller.close()
    },
  })

  return new Response(stream, {
    headers: { 'Content-Type': 'text/event-stream' },
  })
}

For AI streaming, use the AI SDK's toUIMessageStreamResponse() (for chat UIs with useChat) which handles SSE formatting automatically.

WebSockets

Vercel Functions can hold open bidirectional WebSocket connections — use them for realtime features like interactive AI streaming, chat, and collaborative apps. There is no separate WebSocket-server product and no third-party service (Pusher, Ably, etc.) required — it runs on Vercel Functions directly. Requires Fluid Compute, which is the default for new projects.

How it works: a WebSocket starts as an HTTP GET with an Upgrade header, so it passes through the same Routing Middleware, rewrites, Firewall rules, and rate limits as any other request. After the upgrade, the connection is pinned to a single function instance for its lifetime; Fluid Compute lets one instance serve many concurrent connections. Active CPU pricing means you're billed while processing messages, not for idle open connections — the same limits and pricing as other Function invocations apply.

ws (no extra config)

WebSockets work like any distributed WebSocket server — export an http.Server and use a library such as ws:

// api/ws.ts
import http from 'http'
import { WebSocketServer } from 'ws'

const server = http.createServer()
const wss = new WebSocketServer({ server })

wss.on('connection', (ws) => {
  ws.on('message', (data) => ws.send(data)) // echo
})

export default server

Socket.IO

Higher-level realtime libraries like Socket.IO work too. Configure the client to use the WebSocket transport directly — Socket.IO defaults to HTTP long-polling, which won't work:

// api/socket-io.ts
import http from 'http'
import { Server } from 'socket.io'

const server = http.createServer()
const io = new Server(server)

io.on('connection', (socket) => {
  socket.on('message', (data) => socket.send(data))
})

export default server

// client.ts
import { io } from 'socket.io-client'

const socket = io('https://your-domain.com', {
  // Socket.IO appends /socket.io, so the full path becomes /api/socket-io/socket.io
  path: '/api/socket-io/socket.io',
  transports: ['websocket'], // required — Socket.IO defaults to HTTP long-polling
})

Express, Hono, and Nitro (including Nuxt, via native WebSocket support) serve WebSockets the same way — export the HTTP server. Python frameworks work too: FastAPI handles the upgrade natively, and python-socketio is protocol-compatible with the JS Socket.IO client.

Next.js

Next.js doesn't expose an API for handling WebSocket upgrades. Use experimental_upgradeWebSocket() from @vercel/functions inside a route handler:

// app/api/ws/route.ts
import { experimental_upgradeWebSocket, type WebSocketData } from '@vercel/functions'

export async function GET() {
  return experimental_upgradeWebSocket((ws) => {
    ws.on('message', (data: WebSocketData) => ws.send(data))
  })
}

Reconnects and persistent state

• Connections close when the function reaches its max duration. Clients must reconnect with backoff, then resubscribe to channels and reload any state they need.
• No instance affinity across connections. A reconnect — or a new deployment — may land on a different instance, so never keep durable state, presence, rooms, or pub/sub coordination in memory. Use an external store such as Redis from the Marketplace.

// client.ts — reconnect with exponential backoff
let socket: WebSocket
let delay = 1000

function connect() {
  socket = new WebSocket('wss://your-domain.com/api/ws')
  socket.addEventListener('open', () => { delay = 1000 })
  socket.addEventListener('message', (e) => console.log(e.data))
  socket.addEventListener('close', () => {
    setTimeout(connect, delay)
    delay = Math.min(delay * 2, 30000)
  })
}

connect()

Cron Jobs

Schedule function invocations via vercel.json:

{
  "crons": [
    {
      "path": "/api/daily-report",
      "schedule": "0 8 * * *"
    },
    {
      "path": "/api/cleanup",
      "schedule": "0 */6 * * *"
    }
  ]
}

The cron endpoint receives a normal HTTP request. Verify it's from Vercel:

export async function GET(req: Request) {
  const authHeader = req.headers.get('authorization')
  if (authHeader !== `Bearer ${process.env.CRON_SECRET}`) {
    return new Response('Unauthorized', { status: 401 })
  }
  // Do scheduled work
  return Response.json({ ok: true })
}

Configuration via vercel.json

Deprecation notice: Support for the legacy now.json config file will be removed on March 31, 2026. Rename now.json to vercel.json (no content changes required).

{
  "functions": {
    "app/api/heavy/**": {
      "maxDuration": 300,
      "memory": 1024
    },
    "app/api/edge/**": {
      "runtime": "edge"
    }
  }
}

Timeout Limits

All plans now default to 300s execution time with Fluid Compute.

Plan	Default	Max
Hobby	300s	300s
Pro	300s	800s
Enterprise	300s	800s

Common Pitfalls

1. Cold starts with DB connections: Use connection pooling (e.g., Neon's @neondatabase/serverless)
2. Edge limitations: No fs, no native modules, limited crypto — use Node.js runtime if needed
3. Timeout exceeded: Use Fluid Compute for long-running tasks, or Workflow SDK for very long processes
4. Bundle size: Functions support up to 5 GB package size on Fluid Compute (up from 250 MB); request bodies up to 100 MB (up from 4.5 MB)
5. Environment variables: Available in all functions automatically; use vercel env pull for local dev

Function Runtime Diagnostics

Timeout Diagnostics

504 Gateway Timeout?
├─ All plans default to 300s with Fluid Compute
├─ Pro/Enterprise: configurable up to 800s
├─ Long-running task?
│  ├─ Under 5 min → Use Fluid Compute with streaming
│  ├─ Up to 15 min → Use Vercel Functions with `maxDuration` in vercel.json
│  └─ Hours/days → Use Workflow SDK (DurableAgent or workflow steps)
└─ DB query slow? → Add connection pooling, check cold start, use Edge Config

500 Error Diagnostics

500 Internal Server Error?
├─ Check Vercel Runtime Logs (Dashboard → Deployments → Functions tab)
├─ Missing env vars? → Compare `.env.local` against Vercel dashboard settings
├─ Import error? → Verify package is in `dependencies`, not `devDependencies`
└─ Uncaught exception? → Wrap handler in try/catch, use `after()` for error reporting

Invocation Failure Diagnostics

"FUNCTION_INVOCATION_FAILED"?
├─ Memory exceeded? → Increase `memory` in vercel.json (up to 3008 MB on Pro)
├─ Crashed during init? → Check top-level await or heavy imports at module scope
└─ Edge Function crash? → Check for Node.js APIs not available in Edge runtime

Cold Start Diagnostics

Cold start latency > 1s?
├─ Using Node.js runtime? → Consider Edge Functions for latency-sensitive routes
├─ Large function bundle? → Audit imports, use dynamic imports, tree-shake
├─ DB connection in cold start? → Use connection pooling (Neon serverless driver)
└─ Enable Fluid Compute to reuse warm instances across requests

Edge Function Timeout Diagnostics

"EDGE_FUNCTION_INVOCATION_TIMEOUT"?
├─ Edge Functions have 25s hard limit (not configurable)
├─ Move heavy computation to Node.js Serverless Functions
└─ Use streaming to start response early, process in background with `waitUntil`

Official Documentation

• Vercel Functions
• Serverless Functions
• Edge Functions
• Fluid Compute
• Streaming
• WebSockets
• Cron Jobs
• GitHub: Vercel