TL;DR:

  • Cloudflare Workers runs JavaScript/TypeScript (and WASM) at 300+ edge locations; Fastly Compute runs WebAssembly natively, supporting Rust, Go, and JavaScript at 90+ PoPs
  • Workers has the larger ecosystem, more integrations, and a more generous free tier; Fastly Compute’s WASM-first architecture offers stronger isolation and more predictable performance at scale
  • For most teams starting out, Workers is the practical choice; teams with strict latency SLAs, compliance requirements, or Rust/Go expertise should evaluate Fastly Compute seriously

The fundamental proposition of edge functions is compelling: rather than routing all requests to a centralised origin — incurring 50–200ms of round-trip latency — run logic at a CDN point of presence a few milliseconds from the user. For tasks like auth token validation, A/B testing, request transformation, and personalisation, edge execution makes the user experience measurably better.

Two platforms have emerged as the serious options for production edge function deployment: Cloudflare Workers and Fastly Compute. They share the basic idea but differ significantly in architecture, ecosystem, and trade-offs.

Architecture Differences

Cloudflare Workers uses an Isolates-based model, running V8 JavaScript engine instances in a shared process. Isolates start in under 1ms (no container or VM spin-up), which is why Workers can maintain sub-millisecond cold starts globally. The runtime exposes a Service Worker-style API — you handle fetch events, read the request, and return a response. Workers also supports WebAssembly modules loaded from JavaScript.

Fastly Compute (formerly Compute@Edge) uses WebAssembly as its primary execution model. Your code — written in Rust, Go, JavaScript, Python, or any language that compiles to WASM — is compiled ahead of time and executed in a Wasmtime-based runtime. Each request gets a fresh WASM instance. Isolation between requests and tenants is strong by design. Cold starts are typically 1–3ms.

The practical implication: Workers’ V8 Isolates are proven at enormous scale and are simpler to target with JavaScript; Fastly Compute’s WASM approach provides harder security boundaries and is preferable for multi-tenant environments or when mixing languages is important.

Performance Comparison

Both platforms advertise sub-5ms response times globally on cache hits, and both deliver on this in practice for simple functions.

Network coverage: Workers operates from 300+ cities. Fastly operates from 90+ PoPs but these are strategically placed in high-traffic regions, and Fastly’s network is particularly strong in European and US enterprise markets.

Cold starts: Workers typically <1ms; Fastly Compute typically 1–3ms. Neither is meaningfully slow for user-facing applications.

CPU-intensive tasks: Fastly Compute’s compiled WASM often outperforms Workers’ V8 execution for CPU-bound work (parsing, compression, crypto). For typical edge use cases (request inspection, simple transformations), the difference is negligible.

Memory limits: Workers currently allows up to 128MB per request; Fastly Compute 32MB. Both can be constraining for heavy workloads.

Developer Experience

Cloudflare Workers wins on ecosystem. Workers has:

  • wrangler CLI with an excellent local development experience via wrangler dev
  • KV (key-value store), R2 (object storage), D1 (SQLite), Durable Objects (stateful coordination), Queues — all integrated
  • Workers AI (run inference models at the edge)
  • Extensive documentation, a large community, and abundant third-party tutorials

For a team starting an edge-native project today, Workers’ integrated platform means you can build a complete application — edge functions, database, storage, AI inference — without leaving Cloudflare.

Fastly Compute wins on language flexibility and WASM maturity. The fastly CLI and the Fiddle browser-based editor work well. Fastly’s WASM SDK for Rust is particularly mature. If your team already writes Rust or Go, targeting Fastly feels natural in a way that doesn’t require learning JavaScript idioms.

Fastly’s configuration (including edge logic) is also partially expressible as code via Terraform, which is valuable in infrastructure-as-code workflows.

Pricing

Cloudflare Workers:

  • Free tier: 100,000 requests/day, 10ms CPU time/request
  • Workers Paid: $5/month includes 10M requests/month; $0.30 per additional million
  • CPU time limits are the main scaling cost driver for compute-heavy functions

Fastly Compute:

  • No free tier (though a trial is available)
  • Priced on a combination of requests and compute time; enterprise pricing dominates
  • Generally more expensive at low volume; more competitive at high scale with predictable pricing

For startups and side projects: Workers is the clear choice — the free tier is genuinely usable, and $5/month covers most early-stage traffic.

For enterprise: pricing converges and Fastly’s SLA commitments and support model may be preferable.

Use Case Fit

Choose Workers for:

  • Projects where integrated KV/R2/D1/Durable Objects simplifies architecture
  • JavaScript/TypeScript teams building edge-first applications
  • Progressive migration of API routes from an origin to the edge
  • AI-at-the-edge inference with Workers AI
  • Projects where the free tier matters

Choose Fastly Compute for:

  • Teams writing Rust or Go who want to deploy the same language at the edge
  • Environments requiring strict request-level isolation (multi-tenant SaaS, regulated industries)
  • High-throughput edge logic where compiled WASM performance advantage is measurable
  • Existing Fastly CDN customers who want to add compute without introducing a second vendor

Getting Started

Cloudflare Workers:

npm install -g wrangler
wrangler init my-worker
cd my-worker && wrangler dev

Fastly Compute (Rust):

cargo install fastly-cli
fastly compute init  # select Rust starter kit
fastly compute serve  # local dev server

Both platforms support local development with live reloading, which makes experimentation fast. For most developers, spending an hour with each’s “hello world” to authentication check function is the most direct way to sense which DX feels right for a given team.

The edge function category is solidly mature. Either platform will serve production workloads reliably — the decision comes down to team language preferences, ecosystem integration needs, and whether you’re building a new project or extending an existing CDN relationship.