Edge Computing
SkillDatabases & dataEdge computing with Cloudflare Workers, Deno Deploy, Bun, Vercel Edge Functions, AWS Lambda@Edge, and edge databases (Turso, D1, DynamoDB Global Tables). Use when building low-latency edge applications, edge-side rendering, or globally distributed compute.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Edge Computing skill
What this skill tells your AI
The instructions your AI receives, as published by travisjneuman/.claude in skills/edge-computing/SKILL.md and read by ahel’s review.
Platforms
| Platform | Runtime | Cold Start | Limits |
|---|---|---|---|
| Cloudflare Workers | V8 isolates | ~0ms | 128MB, 30s CPU |
| Deno Deploy | V8 isolates | ~0ms | 512MB, 50ms CPU |
| Vercel Edge Functions | V8 isolates | ~0ms | 128MB, 25s |
| AWS Lambda@Edge | Node.js | ~100ms | 128MB, 5s (viewer) |
| Bun | JavaScriptCore | N/A (server) | No hard limits |
Cloudflare Workers
export default {
async fetch(request: Request, env: Env): Promise<Response> {
const url = new URL(request.url);
// KV storage
const cached = await env.KV.get(url.pathname);
if (cached) return new Response(cached, { headers: { 'Cache-Control': 'max-age=60' } });
// D1 database
const { results } = await env.DB.prepare('SELECT * FROM users WHERE id = ?')
.bind(url.searchParams.get('id'))
.all();
// Durable Objects for state
const id = env.COUNTER.idFromName('global');
const obj = env.COUNTER.get(id);
const count = await obj.fetch(request);
return new Response(JSON.stringify(results));
}
};
Edge Databases
| Database | Type | Best For |
|---|---|---|
| Cloudflare D1 | SQLite | Workers-native, SQL at edge |
| Turso | libSQL (SQLite) | Multi-region replicas, embedded |
| Cloudflare KV | Key-value | Simple caching, config |
| Durable Objects | Stateful | Real-time, coordination, counters |
| Upstash Redis | Redis | Rate limiting, sessions at edge |
Deno Deploy
Deno.serve(async (req: Request) => {
const kv = await Deno.openKv();
const url = new URL(req.url);
if (req.method === "POST") {
const body = await req.json();
await kv.set(["items", crypto.randomUUID()], body);
return new Response("Created", { status: 201 });
}
const entries = kv.list({ prefix: ["items"] });
const items = [];
for await (const entry of entries) items.push(entry.value);
return Response.json(items);
});
Patterns
- Edge-side rendering: SSR at the edge for <50ms TTFB globally
- Smart routing: Geo-aware request routing based on
request.cf.country - Edge caching: Cache API for fine-grained control, stale-while-revalidate
- Rate limiting: Sliding window counters with Durable Objects or Upstash
- A/B testing: Edge-side feature flags without origin round-trips
- Image optimization: On-the-fly transforms at edge (Cloudflare Images, Imgproxy)
Constraints & Gotchas
- No Node.js APIs (fs, net, etc.) in V8 isolate runtimes
- No native modules or binaries (use WASM for compute-heavy work)
- Limited CPU time per request — offload heavy work to queues
- Cold starts are near-zero for isolates but real for Lambda@Edge
- Database connections: use HTTP-based clients, not TCP connection pools
Signals
- GitHub stars
- 97
- Forks
- 22
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
edge-computing- Source
- github.com/travisjneuman/.claude