What is Rate Limiting?

Have you ever tried to use an online service and suddenly got a message saying, "Too many requests. Try again later"? That’s rate limiting in action!

Rate limiting is a technique used by websites, apps, and online services to control how many times a user or system can request data within a specific timeframe. This helps prevent excessive load on servers, ensuring smooth performance for everyone.

Why is Rate Limiting Important?

Without rate limiting, a service could be overwhelmed by too many requests at once. This could be caused by:

Malicious attacks (such as DDoS attacks where bots flood a server with requests to make it crash)
Excessive usage (when too many people use a service at the same time)
Unintentional overuse (users making too many requests too quickly)

By limiting the number of requests a user or system can make in a short period, rate limiting helps keep services running smoothly and fairly for everyone.

A Real-Life Example: ChatGPT’s Ghibli Image Generation Issue

Let’s take a real-world example: OpenAI’s ChatGPT offers various services, including AI-generated images. When they introduced Ghibli-style image generation, many users rushed to try it out, making a massive number of requests at once.

The demand was so high that OpenAI had to implement rate limiting to prevent their servers from getting overloaded. Users who exceeded the allowed request limit had to wait before generating more images. (Do let everyone know in the comment section how much limits are currently there on ChatGPT for image generation). This ensured that the service remained available to everyone instead of crashing due to excessive demand.

How Does Rate Limiting Work?

Rate limiting can be enforced in different ways:

Fixed Window: Users can make a set number of requests in a fixed time (e.g., 100 requests per hour).
Sliding Window: Requests are tracked over a rolling period instead of resetting at a fixed time.
Token Bucket: Users get a limited number of "tokens" that allow them to make requests; tokens refill over time.
Leaky Bucket: Similar to token bucket, but requests are processed at a fixed rate, preventing sudden bursts.

Key Takeaway

Rate limiting is essential for maintaining the stability and fairness of online services. It prevents overload, ensures security, and keeps things running smoothly for all users.

Rate Limiting: Why It Matters and How It Works