title: "API Rate Limiting — 5 Patterns That Actually Scale" slug: api-rate-limiting-patterns-that-scale meta_description: "Learn 5 production-proven API rate limiting patterns with code examples. From token buckets to sliding windows — pick the right approach for your traffic profile." target_keyword: "API rate limiting" secondary_keywords:

• "rate limiting patterns"
• "token bucket algorithm"
• "API throttling best practices" word_count: 2847 estimated_read_time: "12 min" category: "Engineering" tags:
• api-design
• rate-limiting
• scalability cta_type: newsletter

API Rate Limiting — 5 Patterns That Actually Scale

Your API handles 10,000 requests per second until it doesn't. One aggressive scraper, one retry storm from a misbehaving client, and your database connection pool is exhausted before your on-call engineer finishes reading the PagerDuty alert. Rate limiting isn't optional infrastructure — it's the difference between a graceful 429 response and a cascading outage.

Token Bucket: The Default Choice for Most APIs

The token bucket algorithm is the most widely deployed rate limiting pattern for a reason: it handles bursts gracefully while enforcing a sustained rate ceiling. Tokens accumulate at a fixed rate (say, 100/second), and each request consumes one token. When the bucket is empty, requests receive a 429 until tokens replenish...

Internal Linking Suggestions

| Anchor Text | Target Page Description | Location in Post | |-------------|------------------------|------------------| | "connection pool exhaustion" | Database connection management guide | Section 1, paragraph 1 | | "retry storms" | Circuit breaker pattern article | Section 3, paragraph 2 |

Social Distribution Copy

Twitter/X (under 280 chars): Most rate limiting tutorials stop at token buckets. Here are 5 patterns we've actually run in production at 10K+ RPS — including the one that saved us during a retry storm. 🧵

LinkedIn (under 700 chars): Rate limiting seems simple until you're debugging a cascading failure at 2 AM. After implementing all five major patterns across different production systems, here's what I've learned about when each one actually works.