Rate Limiting and Quota Management for AI Applications

Without limits, AI costs spiral out of control. Rate limiting and quota management protect your infrastructure and budget while ensuring fair access. This guide covers strategies for controlling AI usage effectively.

Why Rate Limit?

Rate Limiting Strategies

Quota Tiers

Overage Handling

Implementation

async function checkRateLimit(userId) {
  const key = `rate:${userId}`;
  const count = await redis.get(key);
  
  if (count >= USER_LIMITS[user.tier]) {
    throw new Error('Rate limit exceeded');
  }
  
  await redis.incr(key);
  await redis.expire(key, 60); // Reset after 60s
}

Conclusion

Rate limiting and quota management are essential for sustainable AI applications. Implement fair limits, provide clear feedback, and make upgrading easy to balance user experience with cost control.