workers-performance

# Cloudflare Workers Performance Optimization

Techniques for maximizing Worker performance and minimizing latency.

## Quick Wins

```typescript
// 1. Avoid unnecessary cloning
// ❌ Bad: Clones entire request
const body = await request.clone().json();

// ✅ Good: Parse directly when not re-using body
const body = await request.json();

// 2. Use streaming instead of buffering
// ❌ Bad: Buffers entire response
const text = await response.text();
return new Response(transform(text));

// ✅ Good: Stream transformation
return new Response(response.body.pipeThrough(new TransformStream({
  transform(chunk, controller) {
    controller.enqueue(process(chunk));
  }
})));

// 3. Cache expensive operations
const cache = caches.default;
const cached = await cache.match(request);
if (cached) return cached;
```

## Critical Rules

1. **Stay under CPU limits** - 10ms (free), 30ms (paid), 50ms (unbound)
2. **Minimize cold starts** - Keep bundles < 1MB, avoid dynamic imports
3. **Use Cache API** - Cache responses at the edge
4. **Stream large payloads** - Don't buffer entire responses
5. **Batch operations** - Combine multiple KV/D1 calls

## Top 10 Performance Errors

| Error | Symptom | Fix |
|-------|---------|-----|
| CPU limit exceeded | Worker terminated | Optimize hot paths, use streaming |
| Cold start latency | First request slow | Reduce bundle size, avoid top-level await |
| Memory pressure | Slow GC, timeouts | Stream data, avoid large arrays |
| KV latency | Slow reads | Use Cache API, batch reads |
| D1 slow queries | High latency | Add indexes, optimize SQL |
| Large bundles | Slow cold starts | Tree-shake, code split |
| Blocking operations | Request timeouts | Use Promise.all, streaming |
| Unnecessary cloning | Memory spike | Only clone when needed |
| Missing cache | Repeated computation | Implement caching layer |
| Sync operations | CPU spikes | Use async alternatives |

## CPU Optimization

### Profile Hot Paths

```typescript
async function profiledHandler(r