Rate limiting and throttling are essential traffic control mechanisms in distributed systems and APIs that regulate the rate at which clients can make requests within a specified timeframe. These patterns protect backend infrastructure from overload, prevent abuse, enforce usage quotas for tiered pricing models, and ensure fair resource allocation across all users. The key distinction is that rate limiting blocks requests once a threshold is exceeded (returning HTTP 429), while throttling slows down or queues excess requests to smooth traffic flow—though in practice, many practitioners use the terms interchangeably. Understanding the algorithmic foundations (token bucket, leaky bucket, sliding window) and architectural considerations (distributed state management, Redis-backed counters, monitoring) is critical for building resilient, scalable APIs that can withstand traffic spikes, DDoS attempts, and noisy neighbors without degrading service quality for legitimate users.