What causes Error 429 Rate Limit Exceeded?

Error 429 occurs when you exceed the API request limits set by the service provider. Common causes include too many requests in a short time period, missing rate limiting in your code, or insufficient API quotas.

How to fix 429 Rate Limit error quickly?

Add exponential backoff retry logic, implement request queuing, increase API quotas if available, and add proper delays between requests. Use CLI tools like Gemini CLI for automated fixes.

What is exponential backoff for rate limiting?

Exponential backoff is a retry strategy where the delay between requests increases exponentially with each failed attempt. This helps avoid overwhelming the API while retrying failed requests.

Error 429 Fix | Gemini CLI

Error 429 Rate Limit Exceeded occurs when your application makes too many requests to an API within a specific time window. This comprehensive guide provides immediate solutions using CLI tools, API adjustments, and retry strategies to resolve rate limiting issues in under 60 seconds.

Root Cause

Rate limiting errors typically stem from one or more of these underlying issues:

Burst requests: Sending too many requests in a short time period
Missing rate limiting: No client-side throttling implementation
Insufficient quotas: API plan limits exceeded
Concurrent processes: Multiple instances hitting the same endpoint
Poor retry logic: Aggressive retries without backoff

The most common scenario is applications that don't implement proper request spacing, leading to sudden spikes that trigger API rate limiters.

Fix in CLI

Use Gemini CLI to automatically implement rate limiting fixes in your codebase:

gemini fix "429 rate limit exceeded"

For automatic retry logic implementation:

gemini generate "exponential backoff retry logic for API calls"

The CLI will analyze your code and suggest specific implementations based on your tech stack and API patterns.

API Adjustments

Implement client-side request throttling to prevent rate limit errors:

JavaScript/Node.js

const rateLimiter = {
  queue: [],
  running: false,
  delay: 1000, // 1 second between requests
  
  async add(apiCall) {
    return new Promise((resolve, reject) => {
      this.queue.push({ apiCall, resolve, reject });
      this.process();
    });
  },
  
  async process() {
    if (this.running || this.queue.length === 0) return;
    this.running = true;
    
    while (this.queue.length > 0) {
      const { apiCall, resolve, reject } = this.queue.shift();
      try {
        const result = await apiCall();
        resolve(result);
      } catch (error) {
        reject(error);
      }
      await new Promise(resolve => setTimeout(resolve, this.delay));
    }
    
    this.running = false;
  }
};

Python

import time
import requests
from functools import wraps

def rate_limit(calls_per_second=1):
    min_interval = 1.0 / calls_per_second
    last_called = [0.0]
    
    def decorator(func):
        @wraps(func)
        def wrapper(*args, **kwargs):
            elapsed = time.time() - last_called[0]
            left_to_wait = min_interval - elapsed
            if left_to_wait > 0:
                time.sleep(left_to_wait)
            ret = func(*args, **kwargs)
            last_called[0] = time.time()
            return ret
        return wrapper
    return decorator

@rate_limit(calls_per_second=2)
def api_call():
    return requests.get('https://api.example.com/data')

Retry Logic

Implement exponential backoff to handle temporary rate limits gracefully:

async function retryWithBackoff(apiCall, maxRetries = 3) {
  for (let attempt = 0; attempt <= maxRetries; attempt++) {
    try {
      return await apiCall();
    } catch (error) {
      if (error.status === 429 && attempt < maxRetries) {
        const delay = Math.pow(2, attempt) * 1000; // Exponential backoff
        console.log(`Rate limit hit, retrying in ${delay}ms`);
        await new Promise(resolve => setTimeout(resolve, delay));
        continue;
      }
      throw error;
    }
  }
}

// Usage
const result = await retryWithBackoff(() => 
  fetch('https://api.example.com/data')
    .then(response => {
      if (response.status === 429) {
        throw { status: 429, message: 'Rate limited' };
      }
      return response.json();
    })
);

This implementation waits progressively longer between retries: 1s, 2s, 4s, preventing further rate limit violations while allowing temporary limits to reset.

Common Pitfalls

Avoid these mistakes that can worsen rate limiting issues:

Immediate retries: Retrying failed requests instantly without delay compounds the problem and may trigger longer rate limit windows
Ignoring Retry-After headers: Many APIs provide specific wait times in response headers - always check and respect these values
Fixed retry intervals: Using the same delay for all retries doesn't adapt to varying server load conditions
No jitter in backoff: Multiple clients using identical backoff timing can create synchronized retry storms
Excessive retry attempts: More than 3-5 retries usually indicates a deeper issue that won't resolve with more attempts
Missing request deduplication: Duplicate requests waste quota and increase the likelihood of hitting rate limits
Poor error handling: Not distinguishing between 429 (retriable) and 4xx errors (permanent failures) leads to wasted retry attempts

Error 429 · Rate Limit Exceeded