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Implement API Rate Limiting and Throttling #39

@Drago-03

Description

@Drago-03

Issue: Implement API Rate Limiting and Throttling

Description

Our API currently lacks protection against excessive usage, making it vulnerable to abuse, DoS attacks, and resource exhaustion. We need to implement a robust rate limiting and throttling system to ensure fair usage, protect server resources, and maintain service availability for all users.

Current Implementation Issues

  • No limits on API request frequency from individual clients
  • Vulnerable to denial-of-service attacks through excessive requests
  • High-volume automated scrapers can consume disproportionate resources
  • No differentiation between essential and non-essential API endpoints
  • Lack of usage tiers for different user types
  • Missing retry-after headers and proper status code responses
  • No monitoring of API usage patterns
  • Difficulty identifying abusive clients
  • Risk of unexpected bill increases from cloud service providers due to traffic spikes

Proposed Solution

Implement a comprehensive API rate limiting and throttling system that:

  • Limits request frequency based on client identity
  • Provides graduated response to excessive requests
  • Differentiates limits based on endpoint criticality
  • Supports different rate limits for various user tiers
  • Returns appropriate status codes and headers
  • Logs and monitors usage patterns
  • Identifies potential abuse
  • Protects against resource exhaustion and cost spikes

Implementation Requirements

  • Design and implement token bucket or leaky bucket algorithm for rate limiting
  • Create configuration for different rate limits by endpoint and user tier
  • Implement client identification mechanism (API keys, IP, user ID)
  • Return proper 429 Too Many Requests responses with Retry-After headers
  • Add request throttling for expensive operations
  • Set up monitoring and alerting for rate limit events
  • Create admin dashboard for viewing API usage patterns
  • Implement automatic temporary bans for repeated abuse
  • Document rate limits in API documentation
  • Develop graceful degradation of service under heavy load

Acceptance Criteria

  • Rate limits are enforced consistently across all API endpoints
  • Different user tiers receive appropriate request allocations
  • System properly identifies clients for rate limiting purposes
  • 429 responses include clear Retry-After headers
  • Rate limit events are logged and monitorable
  • Admins can view usage patterns and rate limit events
  • Documentation clearly explains rate limits to API consumers
  • System can handle bursts of traffic without failing
  • Abuse attempts are automatically detected and mitigated
  • Rate limiting configuration can be updated without service restart

Additional Notes

Consider implementing a Redis-based rate limiting solution for distributed environments. Rate limits should balance security needs with legitimate user experience. We should provide a clear upgrade path for users who regularly hit rate limits. The system should be flexible enough to adjust limits during special events or promotions.

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