Cloudflare Workers & Edge Computing

Build serverless functions at the edge with sub-50ms cold starts, KV storage, and D1 SQLite databases.

CloudflareIntermediate

Why

Cloudflare Workers run in 300+ locations worldwide, executing code 50ms from users. No cold starts (V8 isolates, not containers), pay-per-request with 100k free requests/day.

Ideal for edge APIs, A/B testing, and auth middleware.

When

Choose Workers for edge APIs, auth/redirect middleware, personal projects (free tier), and latency-sensitive global apps. Avoid for long-running tasks (50ms CPU limit) or heavy compute.

How

1. Install Wrangler CLI — npm i -g wrangler 2. Scaffold — wrangler init my-worker (choose "Hello World" template) 3. Write handler — export default { async fetch(request, env, ctx) { ... } } 4. KV namespace — wrangler kv:namespace create KV, bind in wrangler.toml 5. D1 database — wrangler d1 create mydb, use in handler via env.DB 6. Test locally — wrangler dev (simulates edge runtime) 7. Deploy — wrangler deploy (live in <30s across 300+ locations) 8. Custom domain — add in dashboard or via wrangler with routes

Example

// wrangler.toml name = "my-api" main = "src/index.ts" compatibility_date = "2024-12-01" [[kv_namespaces]] binding = "KV" id = "abc123..." [[d1_databases]] binding = "DB" database_name = "mydb" database_id = "xyz789..." // src/index.ts — edge API with KV + D1 export interface Env { KV: KVNamespace; DB: D1Database; } export default { async fetch(request: Request, env: Env): Promise<Response> { const url = new URL(request.url); // Edge-cached response if (url.pathname === "/api/views") { const cached = await env.KV.get("views"); const views = parseInt(cached || "0") + 1; await env.KV.put("views", String(views)); return Response.json({ views }); } // D1 query at the edge if (url.pathname === "/api/users") { const { results } = await env.DB.prepare("SELECT * FROM users LIMIT 10").all(); return Response.json(results); } return new Response("Not found", { status: 404 }); }, };

Common Problems

⚠50ms CPU limit exceeded — crypto or JSON parsing on large payloads hits the wall
⚠KV eventual consistency — writes take up to 60s to propagate globally, stale reads
⚠D1 5MB query limit — large SELECT results get truncated, use pagination
⚠wrangler dev != production — Node.js APIs available locally but not at edge

Best Practices

✓Use Cache API instead of KV for cacheable data — free, faster, respects Cache-Control
✓Keep handlers under 1MB — Workers bundle limit, use dynamic imports for large deps
✓Use D1 read replicas for global reads — primary is single-region, replicas are edge
✓Set compatibility_date in wrangler.toml — pins runtime behavior, prevents surprise breaks

FAQ

What is Cloudflare Workers & Edge Computing and what problem does it solve?

Build serverless functions at the edge with sub-50ms cold starts, KV storage, and D1 SQLite databases. It lets developers deploy, store, and scale without self-managing infrastructure — a core reference for cloud service selection.

How do I get started with Cloudflare Workers & Edge Computing in 5 minutes?

Two steps to run it: (1) Install Wrangler CLI — npm i -g wrangler; (2) Scaffold — wrangler init my-worker (choose "Hello World" template). Validate on the free tier first, then wire into production.

What is the #1 pitfall with Cloudflare Workers & Edge Computing?

The most frequent issue is: 50ms CPU limit exceeded — crypto or JSON parsing on large payloads hits the wall. Run a pre-launch checklist item by item, and add policy/config scanning in CI.

What are the best practices for Cloudflare Workers & Edge Computing?

Best practices for Cloudflare Workers & Edge Computing include: Use Cache API instead of KV for cacheable data — free, faster, respects Cache-Control; Keep handlers under 1MB — Workers bundle limit, use dynamic imports for large deps; Use D1 read replicas for global reads — primary is single-region, replicas are edge. The first one — "Use Cache API instead of KV for cacheable data — free, faster, respects Cache-Control" — should be a team default baked into your IaC templates.

How do I control cost and avoid bill surprises with Cloudflare Workers & Edge Computing?

Three ways to prevent overspend: (1) tag every resource with env/team and enable billing alarms; (2) set budget thresholds to trigger Slack/email alerts; (3) review idle resources in Cost Explorer regularly and clean them up. Most Cloudflare Workers & Edge Computing options offer a free tier — validate within free quota before scaling.