cloudflare-workers:optimize

Workers Optimize Command

Comprehensive performance analysis and optimization for Cloudflare Workers.

Execution Workflow

Phase 1: Analysis Scope Determination

If --target argument provided:

• Focus analysis on specified area (bundle, memory, or cache)
• Skip other analyses for faster results

If no --target argument:

• Run complete performance audit
• Analyze all optimization areas

Phase 2: Bundle Size Analysis

Analyze Worker bundle size and identify bloat:

1. Build Worker and check output size:

bunx wrangler deploy --dry-run --outdir=.wrangler-output
du -h .wrangler-output/

1. Parse bundle size:

   • Extract total bundle size in KB
   • Compare against limits:
     • Free tier: 1MB limit
     • Paid tier: 10MB limit
   • Flag if >50% of limit used

2. Identify large dependencies:

# Analyze package.json dependencies
grep -A 100 '"dependencies"' package.json

Common bloat sources:

• moment.js (large, use date-fns instead)
• lodash (use lodash-es for tree-shaking)
• axios (use native fetch)
• Large UI libraries in backend code

1. Check for unnecessary imports:
   • Grep for wildcard imports: import * as
   • Check for unused imports in main worker file
   • Look for dev dependencies in production bundle

Findings:

### Bundle Size Analysis

**Current Size**: X KB / Y MB limit (Z% used)

**Large Dependencies**:
1. [package-name]: X KB
2. [package-name]: X KB

**Recommendations**:
- Remove [package] (unused in production)
- Replace [package] with [lighter alternative]
- Use dynamic imports for [feature]

Phase 3: Caching Analysis

Analyze Cache API usage and opportunities:

1. Check for Cache API usage:

grep -r "caches.open" src/
grep -r "cache.match" src/
grep -r "cache.put" src/

1. Identify cacheable endpoints:

   • Look for GET routes
   • Check for static responses
   • Find repeated external API calls

2. Check cache headers:

grep -r "Cache-Control" src/
grep -r "max-age" src/