vercel-cost-tuning

Optimize Vercel costs through plan selection, function efficiency, and usage monitoring. Use when analyzing Vercel billing, reducing function execution costs, or implementing spend management and budget alerts. Trigger with phrases like "vercel cost", "vercel billing", "reduce vercel costs", "vercel pricing", "vercel expensive", "vercel budget".

claude-codecodexopenclaw
6 Tools
vercel-pack Plugin
saas packs Category

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ReadWriteEditBash(vercel:*)Bash(curl:*)Grep

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vercel-pack

Claude Code skill pack for Vercel (30 skills)

saas packs v1.0.0
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Installation

This skill is included in the vercel-pack plugin:

/plugin install vercel-pack@claude-code-plugins-plus

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Instructions

Vercel Cost Tuning

Overview

Optimize Vercel costs by understanding the Fluid Compute pricing model, reducing function execution time, leveraging edge caching to avoid function invocations, and configuring spend management. Covers plan comparison, cost drivers, and monitoring.

Prerequisites

  • Access to Vercel billing dashboard
  • Understanding of current deployment architecture
  • Access to Vercel Analytics for usage patterns

Instructions

Step 1: Understand the Pricing Model

Vercel uses Fluid Compute pricing (for new projects):

Resource Hobby (Free) Pro ($20/member/mo) Enterprise
Bandwidth 100 GB 1 TB included Custom
Serverless Execution 100 GB-hrs 1000 GB-hrs included Custom
Edge Function invocations 500K 1M included Custom
Edge Middleware invocations 1M 1M included Custom
Image Optimizations 1000 5000 included Custom
Builds per day 6000 6000 Custom
Concurrent builds 1 1 (more available) Custom

Fluid Compute billing breakdown:

  • Active CPU time: charged per ms of actual CPU usage
  • Provisioned memory: charged per GB-second of allocated memory
  • Benefit: you pay for actual work, not idle waiting (e.g., waiting for a database response)

Step 2: Identify Cost Drivers


# Check usage via API
curl -s -H "Authorization: Bearer $VERCEL_TOKEN" \
  "https://api.vercel.com/v2/usage" | jq .

# Top cost drivers on Vercel:
# 1. Serverless function execution time (CPU + memory)
# 2. Bandwidth (large responses, unoptimized images)
# 3. Edge Middleware invocations (runs on EVERY request)
# 4. Image optimizations (each unique transform costs)
# 5. Build minutes (frequent deploys or slow builds)

Step 3: Reduce Function Execution Costs


// 1. Right-size function memory — don't over-allocate
// vercel.json
{
  "functions": {
    "api/lightweight.ts": { "memory": 128 },    // Simple JSON responses
    "api/standard.ts": { "memory": 512 },       // Database queries
    "api/heavy.ts": { "memory": 1024 }          // Image processing
  }
}

// 2. Move read-only endpoints to Edge Functions (cheaper, no cold starts)
// api/config.ts
export const config = { runtime: 'edge' };
export default function handler() {
  return Response.json({ features: ['a', 'b'] });
}

// 3. Cache function responses at the edge
// Eliminates function invocations entirely for cached routes
export default function handler(req, res) {
  res.setHeader('Cache-Control', 's-maxage=3600, stale-while-revalidate=86400');
  res.json(data);
}

Step 4: Reduce Bandwidth Costs


// vercel.json — compress and cache aggressively
{
  "headers": [
    {
      "source": "/static/(.*)",
      "headers": [
        { "key": "Cache-Control", "value": "public, max-age=31536000, immutable" }
      ]
    }
  ],
  "images": {
    "sizes": [640, 750, 1080],
    "formats": ["image/avif", "image/webp"],
    "minimumCacheTTL": 86400
  }
}

Key bandwidth reducers:

  • Use Vercel's image optimization (auto WebP/AVIF conversion)
  • Set aggressive cache headers on static assets
  • Use ISR to serve static HTML instead of SSR
  • Compress API responses (Vercel auto-compresses with Brotli)

Step 5: Optimize Middleware Costs

Middleware runs on every matched request. Minimize its scope:


// middleware.ts — scope to specific paths only
export const config = {
  matcher: [
    // Only run middleware on API routes and protected pages
    '/api/:path*',
    '/dashboard/:path*',
    // Skip static files, images, and public assets
    '/((?!_next/static|_next/image|favicon.ico|public).*)',
  ],
};

export function middleware(request) {
  // Keep logic minimal — this runs on every matched request
  // Avoid: database queries, external API calls, heavy computation
  // Good: cookie checks, header modifications, redirects
}

Step 6: Configure Spend Management

In the Vercel dashboard under Settings > Billing > Spend Management:


Default budget: $200/month on-demand usage
Options:
- Set custom budget limit
- Enable hard limit (pauses all projects when reached)
- Configure email alerts at 50%, 75%, 90%, 100%

# Check current usage against budget via API
curl -s -H "Authorization: Bearer $VERCEL_TOKEN" \
  "https://api.vercel.com/v2/usage?teamId=team_xxx" \
  | jq '{period: .period, bandwidth: .bandwidth, execution: .serverlessFunctionExecution}'

Cost Optimization Checklist

Action Impact Effort
Add s-maxage cache headers High — eliminates function invocations Low
Use Edge Functions for simple endpoints Medium — cheaper than serverless Low
Right-size function memory Medium — reduces GB-hr cost Low
Scope middleware matcher Medium — reduces edge invocations Low
Enable image optimization Medium — reduces bandwidth Low
Use ISR instead of SSR High — serves cached HTML Medium
Optimize build speed Low — reduces build minutes Medium
Set spend management alerts Safety — prevents surprise bills Low

Output

  • Function memory right-sized per endpoint
  • Edge caching reducing function invocations
  • Middleware scoped to minimize invocations
  • Spend management configured with budget alerts
  • Usage monitoring via API

Error Handling

Error Cause Solution
Unexpected bill spike Uncached high-traffic endpoint Add s-maxage to the response
Projects paused Hard spending limit reached Increase limit or optimize usage
Image optimization quota exceeded Too many unique image transforms Reduce sizes array, increase cache TTL
Build minutes exceeded Slow builds or too many deploys Use ignoreCommand to skip non-code changes

Resources

Next Steps

For reference architecture, see vercel-reference-architecture.

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