How to choose serverless without hitting invisible limits
Pick an execution model first (edge vs region), then validate cold starts, ceilings, and cost cliffs under production-like load.
Top Rated Serverless Platforms
AWS Lambda
Regional serverless baseline for AWS-first teams building event-driven systems with deep AWS triggers and integrations....
Cloudflare Workers
Edge-first runtime for low-latency request-path compute (middleware, routing, personalization) close to global users....
Vercel Functions
Web-platform serverless functions optimized for framework DX (especially Next.js) and fast iteration for product teams....
Netlify Functions
Platform-integrated serverless functions for web properties and lightweight backends with an emphasis on deployment simplicity....
Azure Functions
Regional serverless compute for Azure-first organizations, typically chosen for ecosystem alignment and enterprise governance patterns....
Google Cloud Functions
GCP’s managed serverless functions for event-driven workloads, typically chosen by teams building on Google Cloud services and triggers....
Supabase Edge Functions
Edge functions integrated into Supabase, used to extend Supabase apps with auth-aware logic and lightweight APIs near product data flows....
Fastly Compute
Edge compute runtime for performance-sensitive request handling and programmable networking patterns close to users....
Pricing and availability may change. Verify details on the official website.
How to Choose the Right Serverless Platforms Platform
Edge vs region (latency model)
Edge runtimes reduce latency for global users and middleware-style workloads. Regional runtimes offer deeper managed triggers and a familiar cloud model, but add latency and can expose cold-start penalties for synchronous endpoints.
Questions to ask:
- Is your compute on the request path (UX) or in the background (events)?
- Do you need global distribution as a default, or specific regions?
- Will data locality and state patterns work with your execution model?
Cold starts, limits, and scaling behavior
Most serverless pain is constraint-driven: timeouts, memory/CPU coupling, throttling, and tail latency. A platform that looks great in dev can degrade under bursts or long-tail traffic.
Questions to ask:
- What are your timeout, memory, and concurrency needs under peak load?
- How will you mitigate cold starts (architecture, capacity controls, edge execution)?
- Can you observe tail latency, throttling, retries, and partial failures?
Cost physics (requests, duration, egress)
Serverless is often marketed as pay-per-use, but cost cliffs appear with sustained traffic, chatty APIs, and egress-heavy workloads. You need workload math, not pricing pages.
Questions to ask:
- Is your traffic spiky or steady-state?
- Will egress and cross-service networking dominate costs?
- Do platform limits or pricing mechanics force an early migration?
How We Rank Serverless Platforms
Source-Led Facts
We prioritize official pricing pages and vendor documentation over third-party review noise.
Intent Over Pricing
A $0 plan is only a "deal" if it actually solves your problem. We rank based on use-case fitness.
Durable Ranges
Vendor prices change daily. We highlight stable pricing bands to help you plan your long-term budget.