vercel-cost-tuning

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