Rate Limits

Overview

To ensure fair usage and maintain service quality, the Dzaleka Online Services API implements rate limiting based on IP address.

Current rate limit: 60 requests per minute per IP address

Rate Limit Configuration

The rate limiting system is implemented in src/utils/api-utils.ts:12-77 with the following parameters:

const RATE_LIMIT_WINDOW = 60 * 1000; // 1 minute
const MAX_REQUESTS_PER_WINDOW = 60; // 60 requests per minute

How It Works

Each IP address gets a 60-request budget per minute
The window starts with your first request
The counter resets after 60 seconds
Requests beyond the limit receive a 429 Too Many Requests response

Rate limits are tracked in-memory and reset automatically. The system periodically cleans up expired entries.

Rate Limit Headers

When you exceed the rate limit, the API returns these headers:

HTTP/1.1 429 Too Many Requests
X-RateLimit-Limit: 60
X-RateLimit-Remaining: 0
X-RateLimit-Reset: 1709982600000
Retry-After: 45

Header Descriptions

X-RateLimit-Limit

string

Maximum requests allowed per window (60)

X-RateLimit-Remaining

string

Number of requests remaining in current window (0 when limited)

X-RateLimit-Reset

string

Unix timestamp (milliseconds) when the rate limit resets

Retry-After

string

Number of seconds to wait before making another request

Rate Limit Response

When you exceed the rate limit, you’ll receive this response:

{
  "status": "error",
  "message": "Rate limit exceeded. Please try again later.",
  "retryAfter": 45
}

Example Rate Limit Error

curl -i https://dzaleka.com/api/services

Response when rate limited:

HTTP/1.1 429 Too Many Requests
Content-Type: application/json
Access-Control-Allow-Origin: *
X-RateLimit-Limit: 60
X-RateLimit-Remaining: 0
X-RateLimit-Reset: 1709982645000
Retry-After: 45

{
  "status": "error",
  "message": "Rate limit exceeded. Please try again later.",
  "retryAfter": 45
}

IP Address Detection

Rate limits are applied per IP address. The system detects your IP from these headers (in order of priority):

x-forwarded-for (first IP in the list)
x-real-ip
cf-connecting-ip (Cloudflare)
Direct connection IP

From src/utils/api-utils.ts:25-29:

const clientIP =
  request.headers.get('x-forwarded-for')?.split(',')[0] ||
  request.headers.get('x-real-ip') ||
  request.headers.get('cf-connecting-ip') ||
  'unknown';

If multiple users share the same public IP (e.g., corporate network, shared hosting), they share the same rate limit.

Handling Rate Limits

Best Practices

Implement Exponential Backoff

When you receive a 429 response, wait before retrying:

async function fetchWithRetry(url, maxRetries = 3) {
  for (let i = 0; i < maxRetries; i++) {
    const response = await fetch(url);
    
    if (response.status !== 429) {
      return response;
    }
    
    // Get retry-after header (in seconds)
    const retryAfter = parseInt(response.headers.get('Retry-After') || '60');
    
    // Wait with exponential backoff
    const delay = retryAfter * 1000 * Math.pow(2, i);
    console.log(`Rate limited. Retrying in ${delay}ms...`);
    
    await new Promise(resolve => setTimeout(resolve, delay));
  }
  
  throw new Error('Max retries exceeded');
}

Cache API Responses

Reduce API calls by caching responses:

const cache = new Map();
const CACHE_TTL = 5 * 60 * 1000; // 5 minutes

async function fetchWithCache(url) {
  const cached = cache.get(url);
  
  if (cached && Date.now() - cached.timestamp < CACHE_TTL) {
    return cached.data;
  }
  
  const response = await fetch(url);
  const data = await response.json();
  
  cache.set(url, {
    data,
    timestamp: Date.now()
  });
  
  return data;
}

Batch Requests

Use POST requests with filters instead of multiple GET requests:

// Bad: Multiple requests
const services = await fetch('/api/services');
const events = await fetch('/api/events');
const news = await fetch('/api/news');

// Better: Use search endpoint
const results = await fetch(
  '/api/search?q=education&collections=services,events,news'
);

Monitor Usage

Track your API usage to avoid hitting limits:

class RateLimitTracker {
  constructor() {
    this.requests = [];
    this.window = 60 * 1000; // 1 minute
  }
  
  canMakeRequest() {
    const now = Date.now();
    // Remove requests outside current window
    this.requests = this.requests.filter(
      time => now - time < this.window
    );
    
    return this.requests.length < 60;
  }
  
  recordRequest() {
    this.requests.push(Date.now());
  }
  
  getRemainingRequests() {
    const now = Date.now();
    this.requests = this.requests.filter(
      time => now - time < this.window
    );
    return 60 - this.requests.length;
  }
}

Code Examples

JavaScript with Rate Limit Handling

class DzalekaAPIClient {
  constructor(baseURL = 'https://services.dzaleka.com/api') {
    this.baseURL = baseURL;
    this.requestQueue = [];
    this.processing = false;
  }
  
  async fetch(endpoint, options = {}) {
    return new Promise((resolve, reject) => {
      this.requestQueue.push({ endpoint, options, resolve, reject });
      this.processQueue();
    });
  }
  
  async processQueue() {
    if (this.processing || this.requestQueue.length === 0) {
      return;
    }
    
    this.processing = true;
    const { endpoint, options, resolve, reject } = this.requestQueue.shift();
    
    try {
      const response = await fetch(`${this.baseURL}${endpoint}`, options);
      
      if (response.status === 429) {
        const retryAfter = parseInt(
          response.headers.get('Retry-After') || '60'
        );
        
        console.log(`Rate limited. Waiting ${retryAfter}s...`);
        
        // Re-queue the request
        this.requestQueue.unshift({ endpoint, options, resolve, reject });
        
        // Wait before processing next request
        setTimeout(() => {
          this.processing = false;
          this.processQueue();
        }, retryAfter * 1000);
        
        return;
      }
      
      const data = await response.json();
      resolve({ status: response.status, data });
      
    } catch (error) {
      reject(error);
    }
    
    // Small delay between requests to avoid hitting limit
    setTimeout(() => {
      this.processing = false;
      this.processQueue();
    }, 1000); // 1 second between requests
  }
}

// Usage
const api = new DzalekaAPIClient();

const services = await api.fetch('/services');
const events = await api.fetch('/events');
const news = await api.fetch('/news');

console.log('Services:', services.data);

Python with Rate Limit Handling

import time
import requests
from typing import Optional, Dict, Any

class DzalekaAPIClient:
    def __init__(self, base_url: str = 'https://services.dzaleka.com/api'):
        self.base_url = base_url
        self.session = requests.Session()
    
    def fetch(self, endpoint: str, method: str = 'GET', 
              data: Optional[Dict] = None, max_retries: int = 3) -> Dict[Any, Any]:
        url = f"{self.base_url}{endpoint}"
        
        for attempt in range(max_retries):
            try:
                if method == 'GET':
                    response = self.session.get(url)
                else:
                    response = self.session.post(url, json=data)
                
                if response.status_code == 429:
                    retry_after = int(response.headers.get('Retry-After', 60))
                    print(f"Rate limited. Waiting {retry_after}s...")
                    time.sleep(retry_after)
                    continue
                
                response.raise_for_status()
                return response.json()
                
            except requests.exceptions.RequestException as e:
                if attempt == max_retries - 1:
                    raise
                print(f"Request failed: {e}. Retrying...")
                time.sleep(2 ** attempt)  # Exponential backoff
        
        raise Exception("Max retries exceeded")

# Usage
api = DzalekaAPIClient()

try:
    services = api.fetch('/services')
    print(f"Found {services['count']} services")
    
    events = api.fetch('/events')
    print(f"Found {events['count']} events")
    
except Exception as e:
    print(f"Error: {e}")

cURL with Manual Retry

#!/bin/bash

MAX_RETRIES=3
URL="https://services.dzaleka.com/api/services"

for i in $(seq 1 $MAX_RETRIES); do
  echo "Attempt $i..."
  
  RESPONSE=$(curl -s -w "\n%{http_code}" "$URL")
  HTTP_CODE=$(echo "$RESPONSE" | tail -n1)
  BODY=$(echo "$RESPONSE" | sed '$d')
  
  if [ "$HTTP_CODE" = "200" ]; then
    echo "Success!"
    echo "$BODY" | jq .
    exit 0
  elif [ "$HTTP_CODE" = "429" ]; then
    RETRY_AFTER=$(echo "$BODY" | jq -r '.retryAfter // 60')
    echo "Rate limited. Waiting ${RETRY_AFTER}s..."
    sleep "$RETRY_AFTER"
  else
    echo "Error: HTTP $HTTP_CODE"
    echo "$BODY" | jq .
    exit 1
  fi
done

echo "Max retries exceeded"
exit 1

Rate Limit Strategies

Strategy Comparison

Strategy	Pros	Cons	Best For
Request Queue	Prevents rate limit errors	Slower overall	Background jobs
Exponential Backoff	Automatic recovery	Adds complexity	Production apps
Client-side Caching	Reduces API calls	Stale data possible	Read-heavy apps
Request Throttling	Smooth traffic	May not use full quota	High-volume apps

Recommended Approach

Combine multiple strategies:

Cache responses (5-10 minute TTL)
Throttle requests (max 1 per second)
Implement retry logic with exponential backoff
Monitor usage and adjust throttling

Troubleshooting

Getting 429 Errors Immediately

Possible causes:

Multiple users sharing the same IP
Previous requests still counting toward limit
Aggressive polling or loops

Solution: Implement rate tracking and delay between requests

Shared IP Rate Limiting

If your users share a public IP:

Consider server-side API calls instead of client-side
Implement request queuing on your server
Cache aggressively to reduce API calls

Rate Limit Not Resetting

Rate limits reset after 60 seconds from the start of the window:

Check X-RateLimit-Reset header for exact reset time
Ensure you’re waiting for the full Retry-After duration

Future Enhancements

The following features are under consideration for future releases:

Higher rate limits for authenticated users
Per-user rate limiting (instead of IP-based)
Rate limit headers on all responses (not just 429s)
Burst allowance for occasional spikes

Next Steps

API Overview

Learn about available endpoints and response formats

Authentication

Understand CORS configuration and headers

Getting Started

Endpoints

Data Models

Overview

Rate Limit Configuration

How It Works

Rate Limit Headers

Header Descriptions

Rate Limit Response

Example Rate Limit Error

IP Address Detection

Handling Rate Limits

Best Practices

Code Examples

JavaScript with Rate Limit Handling

Python with Rate Limit Handling

cURL with Manual Retry

Rate Limit Strategies

Strategy Comparison

Recommended Approach

Troubleshooting

Future Enhancements

Next Steps

API Overview

Authentication

Getting Started

Endpoints

Data Models

​Overview

​Rate Limit Configuration

​How It Works

​Rate Limit Headers

​Header Descriptions

​Rate Limit Response

​Example Rate Limit Error

​IP Address Detection

​Handling Rate Limits

​Best Practices

​Code Examples

​JavaScript with Rate Limit Handling

​Python with Rate Limit Handling

​cURL with Manual Retry

​Rate Limit Strategies

​Strategy Comparison

​Recommended Approach

​Troubleshooting

​Future Enhancements

​Next Steps

API Overview

Authentication

Overview

Rate Limit Configuration

How It Works

Rate Limit Headers

Header Descriptions

Rate Limit Response

Example Rate Limit Error

IP Address Detection

Handling Rate Limits

Best Practices

Code Examples

JavaScript with Rate Limit Handling

Python with Rate Limit Handling

cURL with Manual Retry

Rate Limit Strategies

Strategy Comparison

Recommended Approach

Troubleshooting

Future Enhancements

Next Steps