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cloudflare-limits.md

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Cloudflare Worker Limits and Quotas

This document outlines the limits and quotas that apply to FoxCloud when running on Cloudflare Workers.

Free Tier Limits

Execution Limits

  • CPU Time: 10 ms per request (can be limiting for complex operations)
  • Memory: 128 MB
  • Execution Timeout: 30 seconds per request
  • Concurrent Subrequests: 6 per request
  • Total Subrequests: 1,000 per day

Data Transfer Limits

  • Outbound Data Transfer: 100,000 requests per day
  • Inbound Data Transfer: No specific limit
  • KV Storage: 1 GB (if using Workers KV)

Request Limits

  • Requests: 100,000 per day
  • Request Size: 128 KB maximum
  • Response Size: 128 KB maximum

Paid Tier Limits (Bundled)

Execution Limits

  • CPU Time: 30 ms per request
  • Memory: 128 MB
  • Execution Timeout: 30 seconds per request
  • Concurrent Subrequests: 6 per request
  • Total Subrequests: 10,000 per day

Data Transfer Limits

  • Outbound Data Transfer: 10 million requests per month
  • Inbound Data Transfer: No specific limit
  • KV Storage: 1 GB (if using Workers KV)

Paid Tier Limits (Unbound)

Execution Limits

  • CPU Time: 30 ms per request
  • Memory: 128 MB
  • Execution Timeout: 30 seconds per request
  • Concurrent Subrequests: 6 per request
  • Total Subrequests: 100,000 per day

Data Transfer Limits

  • Outbound Data Transfer: 100 million requests per month
  • Inbound Data Transfer: No specific limit
  • KV Storage: 1 GB (if using Workers KV)

Implications for FoxCloud

WebSocket Connections

  • Each WebSocket connection consumes CPU time and memory
  • Long-lived connections may hit execution timeout limits
  • Consider connection duration when designing proxy behavior

Proxy Requests

  • Each proxy request counts as a subrequest
  • High-volume proxy usage may hit subrequest limits
  • Consider caching strategies to reduce subrequests

Data Transfer

  • Large data transfers may be limited by request/response size limits
  • WebSocket data transfer is subject to these limits
  • Consider data compression for large transfers

Optimization Strategies

CPU Usage Optimization

  1. Minimize Processing: Reduce unnecessary computations
  2. Efficient Algorithms: Use optimized algorithms for proxy operations
  3. Caching: Cache frequently accessed data
  4. Lazy Loading: Load resources only when needed

Memory Optimization

  1. Object Reuse: Reuse objects instead of creating new ones
  2. Memory Cleanup: Clean up unused variables and objects
  3. Stream Processing: Process data in streams rather than loading all at once
  4. Efficient Data Structures: Use appropriate data structures for the task

Request Optimization

  1. Batching: Batch multiple operations when possible
  2. Caching: Cache responses to reduce repeated requests
  3. Compression: Use compression for large data transfers
  4. Connection Reuse: Reuse connections when possible

Monitoring Usage

Built-in Monitoring

  • Cloudflare Dashboard provides usage statistics
  • Monitor requests, CPU time, and errors
  • Set up alerts for quota limits

Custom Monitoring

  • Implement custom logging for detailed metrics
  • Track proxy usage by UUID
  • Monitor connection durations
  • Log errors and exceptions

Scaling Considerations

Traffic Spikes

  • Free tier may not handle traffic spikes well
  • Consider upgrading to paid tiers for production use
  • Implement rate limiting to prevent abuse
  • Use multiple proxy servers for load distribution

User Growth

  • Plan for increased usage as user base grows
  • Monitor quota usage regularly
  • Upgrade tiers as needed
  • Consider architectural changes for high scale

Best Practices for Staying Within Limits

Efficient Proxy Implementation

  1. Minimize Handshake Overhead: Optimize WebSocket connection establishment
  2. Efficient Data Forwarding: Use streaming for data transfer
  3. Connection Pooling: Reuse connections when possible
  4. Error Handling: Handle errors efficiently to avoid resource waste

Resource Management

  1. Memory Management: Clean up resources promptly
  2. CPU Usage: Optimize critical paths
  3. Subrequest Management: Minimize unnecessary subrequests
  4. Caching Strategy: Implement effective caching

Monitoring and Alerting

  1. Usage Tracking: Monitor quota usage regularly
  2. Performance Metrics: Track response times and error rates
  3. Alerting: Set up alerts for approaching limits
  4. Logging: Implement comprehensive logging

Troubleshooting Limit Issues

Identifying Limit Issues

  • Check Cloudflare Dashboard for quota usage
  • Monitor Worker logs for timeout errors
  • Look for "CPU exceeded" or "memory limit" errors
  • Monitor response times for degradation

Resolving Limit Issues

  1. Optimize Code: Reduce CPU and memory usage
  2. Upgrade Tier: Move to a higher tier if needed
  3. Implement Caching: Reduce repeated operations
  4. Load Distribution: Distribute load across multiple Workers

Additional Considerations

Regional Differences

  • Limits may vary by region
  • Check Cloudflare documentation for region-specific limits
  • Consider deploying to multiple regions for better performance

Future Changes

  • Cloudflare may change limits over time
  • Stay updated with Cloudflare announcements
  • Plan for potential limit changes

Special Use Cases

  • High-frequency trading applications
  • Real-time gaming applications
  • Video streaming applications
  • These may require special consideration for limits

By understanding and working within these limits, you can ensure a stable and performant FoxCloud deployment on Cloudflare Workers.