Skip to content

Conversation

talkstream
Copy link
Owner

Summary

This PR implements a comprehensive tier-based optimization system for Cloudflare Workers, enabling automatic resource management and optimization based on the worker's tier (free, paid, or enterprise).

Features Implemented

1. Tier Optimization Service

  • Resource tracking (CPU, memory, subrequests, KV/D1 operations)
  • Automatic tier detection based on environment
  • Resource limit enforcement per tier
  • Optimization recommendation system

2. Built-in Optimization Strategies

  • Cache Optimization: More aggressive caching for free tier
  • Request Batching: Batch operations to reduce overhead
  • Query Simplification: Simplify complex queries for free tier
  • Response Compression: Reduce bandwidth usage
  • Early Termination: Prevent CPU limit violations
  • Memory Optimization: Manage memory usage with GC hints
  • KV Optimization: Batch and cache KV operations
  • Adaptive Timeouts: Adjust based on remaining resources
  • Graceful Degradation: Reduce functionality when near limits
  • Subrequest Pooling: Pool connections to reduce overhead

3. Tier Optimizer Middleware

  • Automatic tier detection
  • Resource usage tracking per request
  • Optimization strategy application
  • Debug headers for monitoring
  • Helper functions for tier-aware responses

4. Utility Functions

  • optimizedCache(): Tier-aware caching
  • optimizedBatch(): Dynamic batch sizing
  • createTieredResponse(): Limit data for free tier

Resource Limits by Tier

Resource Free Paid Enterprise
CPU Time 10ms 30s 30s
Memory 128MB 128MB 512MB
Subrequests 50 1000 5000
KV Reads 1000 100k 100k
KV Writes 1000 10k 10k

Test Coverage

  • 25 tests covering all aspects of tier optimization
  • 100% passing test suite
  • Tests for resource tracking, optimization strategies, and recommendations

Documentation

  • Comprehensive documentation in docs/TIER_OPTIMIZATION.md
  • Example implementation in examples/tier-optimization-example.ts
  • Full TypeScript support with detailed interfaces

Breaking Changes

None - this is a new feature that doesn't affect existing functionality.

Usage Example

import { createTierOptimizer } from '@/middleware/tier-optimizer';

export default {
  fetch: new Hono()
    .use('*', createTierOptimizer({
      debug: true,
      config: {
        enabled: true,
        aggressive: false,
      }
    }))
    .get('/api/data', async (c) => {
      // Automatic tier-based optimization
      return createTieredResponse(c, data, {
        summaryFields: ['id', 'name'],
        fullDataTiers: ['paid', 'enterprise']
      });
    })
    .fetch,
};

Integration with Kogotochki Experience

This implementation is based on real-world performance optimizations deployed in the Kogotochki bot, where tier-based resource management significantly improved performance and reduced costs on Cloudflare's free tier.

- Added contribution review checklist for maintainers
- Created successful contributions gallery with examples
- Enhanced contribute.ts with PR conflict detection
- Added GitHub Action for automated PR validation
- Created auto-labeling configuration for PRs
- Updated CONTRIBUTING.md with links to new resources

This improves the contribution workflow by:
1. Providing clear review criteria
2. Showcasing successful contributions
3. Preventing PR conflicts early
4. Automating validation checks
5. Auto-labeling PRs for better organization

Based on experience processing contributions from the community.
- Add comprehensive tier optimization service with resource tracking
- Implement 10 built-in optimization strategies (cache, batching, compression, etc.)
- Create tier optimizer middleware for automatic optimization
- Support free, paid, and enterprise tiers with appropriate limits
- Include tier detection, resource monitoring, and recommendations
- Add helper functions for tier-aware responses and batch processing
- Full test coverage with 25 passing tests
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

None yet

Projects

None yet

Development

Successfully merging this pull request may close these issues.

1 participant