Rate Limiting for Beginners: What It Is and How to Build One in Go
Rate limiting is a critical concept in web development and API design. It ensures that users or systems can only make a limited number of requests to a server within a specific time frame. In this blog post, we’ll explore what rate limiting is, why it’s essential, and how to implement a simple rate limiter in Go.
What Is Rate Limiting?
Imagine a theme park with a roller coaster ride that can only accommodate 10 people every 10 minutes. If more than 10 people try to get on within that timeframe, they’ll have to wait. This analogy mirrors the principle of rate limiting in software systems.
In technical terms, rate limiting restricts the number of requests a client (e.g., a user, device, or IP address) can send to a server within a predefined period. It helps:
- Prevent abuse and ensure fair usage of resources.
- Protect servers from being overwhelmed by excessive traffic.
- Avoid costly overuse of third-party APIs or services.
For example, an API might allow 100 requests per minute per user. If a user exceeds this limit, the server denies further requests until the limit resets.
How Does Rate Limiting Work?
One common way to implement rate limiting is through the token bucket algorithm. Here’s how it works:
- A bucket starts with a fixed number of tokens (e.g., 10).
- Each request removes one token from the bucket.
- If the bucket has no tokens left, the request is denied.
- Tokens are replenished at a steady rate (e.g., 1 token every second) until the bucket is full.
Building a Simple Rate Limiter in Go
Let’s dive into building a rate limiter in Go that limits each client to 3 requests per minute.
Step 1: Define the Rate Limiter Structure
We’ll use the sync.Mutex to ensure thread safety and store information like the number of tokens, the maximum capacity, and the refill rate.
package main import ( "sync" "time" ) type RateLimiter struct { tokens float64 // Current number of tokens maxTokens float64 // Maximum tokens allowed refillRate float64 // Tokens added per second lastRefillTime time.Time // Last time tokens were refilled mutex sync.Mutex } func NewRateLimiter(maxTokens, refillRate float64) *RateLimiter { return &RateLimiter{ tokens: maxTokens, maxTokens: maxTokens, refillRate: refillRate, lastRefillTime: time.Now(), } }
Step 2: Implement Token Refill Logic
Tokens should be replenished periodically based on the elapsed time since the last refill.
func (r *RateLimiter) refillTokens() { now := time.Now() duration := now.Sub(r.lastRefillTime).Seconds() tokensToAdd := duration * r.refillRate r.tokens += tokensToAdd if r.tokens > r.maxTokens { r.tokens = r.maxTokens } r.lastRefillTime = now }
Step 3: Check If a Request Is Allowed
The Allow method will determine if a request can proceed based on the available tokens.
func (r *RateLimiter) Allow() bool { r.mutex.Lock() defer r.mutex.Unlock() r.refillTokens() if r.tokens >= 1 { r.tokens-- return true } return false }
Step 4: Apply Rate Limiting Per IP
To limit requests per client, we’ll create a map of IP addresses to their respective rate limiters.
type IPRateLimiter struct { limiters map[string]*RateLimiter mutex sync.Mutex } func NewIPRateLimiter() *IPRateLimiter { return &IPRateLimiter{ limiters: make(map[string]*RateLimiter), } } func (i *IPRateLimiter) GetLimiter(ip string) *RateLimiter { i.mutex.Lock() defer i.mutex.Unlock() limiter, exists := i.limiters[ip] if !exists { // Allow 3 requests per minute limiter = NewRateLimiter(3, 0.05) i.limiters[ip] = limiter } return limiter }
Step 5: Create Middleware for Rate Limiting
Finally, we’ll create an HTTP middleware that enforces the rate limit for each client.
package main import ( "sync" "time" ) type RateLimiter struct { tokens float64 // Current number of tokens maxTokens float64 // Maximum tokens allowed refillRate float64 // Tokens added per second lastRefillTime time.Time // Last time tokens were refilled mutex sync.Mutex } func NewRateLimiter(maxTokens, refillRate float64) *RateLimiter { return &RateLimiter{ tokens: maxTokens, maxTokens: maxTokens, refillRate: refillRate, lastRefillTime: time.Now(), } }
Step 6: Set Up the Server
Here’s how to hook it all together and test the rate limiter.
func (r *RateLimiter) refillTokens() { now := time.Now() duration := now.Sub(r.lastRefillTime).Seconds() tokensToAdd := duration * r.refillRate r.tokens += tokensToAdd if r.tokens > r.maxTokens { r.tokens = r.maxTokens } r.lastRefillTime = now }
Testing the Rate Limiter
Start the server and test it using curl or your browser:
func (r *RateLimiter) Allow() bool { r.mutex.Lock() defer r.mutex.Unlock() r.refillTokens() if r.tokens >= 1 { r.tokens-- return true } return false }
- Send 3 requests quickly: All should succeed.
- Send a 4th request within the same minute: You should see Rate Limit Exceeded message.
- Wait for 20 seconds and try again: The bucket refills, and requests should succeed.
Source Code
GitHub Repo
The above is the detailed content of Rate Limiting for Beginners: What It Is and How to Build One in Go. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











Go language performs well in building efficient and scalable systems. Its advantages include: 1. High performance: compiled into machine code, fast running speed; 2. Concurrent programming: simplify multitasking through goroutines and channels; 3. Simplicity: concise syntax, reducing learning and maintenance costs; 4. Cross-platform: supports cross-platform compilation, easy deployment.

Golang is better than Python in terms of performance and scalability. 1) Golang's compilation-type characteristics and efficient concurrency model make it perform well in high concurrency scenarios. 2) Python, as an interpreted language, executes slowly, but can optimize performance through tools such as Cython.

Golang is better than C in concurrency, while C is better than Golang in raw speed. 1) Golang achieves efficient concurrency through goroutine and channel, which is suitable for handling a large number of concurrent tasks. 2)C Through compiler optimization and standard library, it provides high performance close to hardware, suitable for applications that require extreme optimization.

Goimpactsdevelopmentpositivelythroughspeed,efficiency,andsimplicity.1)Speed:Gocompilesquicklyandrunsefficiently,idealforlargeprojects.2)Efficiency:Itscomprehensivestandardlibraryreducesexternaldependencies,enhancingdevelopmentefficiency.3)Simplicity:

Golang and Python each have their own advantages: Golang is suitable for high performance and concurrent programming, while Python is suitable for data science and web development. Golang is known for its concurrency model and efficient performance, while Python is known for its concise syntax and rich library ecosystem.

Golang is suitable for rapid development and concurrent scenarios, and C is suitable for scenarios where extreme performance and low-level control are required. 1) Golang improves performance through garbage collection and concurrency mechanisms, and is suitable for high-concurrency Web service development. 2) C achieves the ultimate performance through manual memory management and compiler optimization, and is suitable for embedded system development.

The performance differences between Golang and C are mainly reflected in memory management, compilation optimization and runtime efficiency. 1) Golang's garbage collection mechanism is convenient but may affect performance, 2) C's manual memory management and compiler optimization are more efficient in recursive computing.

C is more suitable for scenarios where direct control of hardware resources and high performance optimization is required, while Golang is more suitable for scenarios where rapid development and high concurrency processing are required. 1.C's advantage lies in its close to hardware characteristics and high optimization capabilities, which are suitable for high-performance needs such as game development. 2.Golang's advantage lies in its concise syntax and natural concurrency support, which is suitable for high concurrency service development.
