Rate Limiter

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Read the updated version of this page for Symfony 7.2 (the current stable version).

5.2

The RateLimiter component was introduced in Symfony 5.2.

A "rate limiter" controls how frequently some event (e.g. an HTTP request or a login attempt) is allowed to happen. Rate limiting is commonly used as a defensive measure to protect services from excessive use (intended or not) and maintain their availability. It's also useful to control your internal or outbound processes (e.g. limit the number of simultaneously processed messages).

Symfony uses these rate limiters in built-in features like login throttling, which limits how many failed login attempts a user can make in a given period of time, but you can use them for your own features too.

Danger

By definition, the Symfony rate limiters require Symfony to be booted in a PHP process. This makes them not useful to protect against DoS attacks. Such protections must consume the least resources possible. Consider using Apache mod_ratelimit, NGINX rate limiting or proxies (like AWS or Cloudflare) to prevent your server from being overwhelmed.

Rate Limiting Policies

Symfony's rate limiter implements some of the most common policies to enforce rate limits: fixed window, sliding window, token bucket.

Fixed Window Rate Limiter

This is the simplest technique and it's based on setting a limit for a given interval of time (e.g. 5,000 requests per hour or 3 login attempts every 15 minutes).

In the diagram below, the limit is set to "5 tokens per hour". Each window starts at the first hit (i.e. 10:15, 11:30 and 12:30). As soon as there are 5 hits (the blue squares) in a window, all others will be rejected (red squares).

Its main drawback is that resource usage is not evenly distributed in time and it can overload the server at the window edges. In this example, there were 6 accepted requests between 11:00 and 12:00.

This is more significant with bigger limits. For instance, with 5,000 requests per hour, a user could make 4,999 requests in the last minute of some hour and another 5,000 requests during the first minute of the next hour, making 9,999 requests in total in two minutes and possibly overloading the server. These periods of excessive usage are called "bursts".

Sliding Window Rate Limiter

The sliding window algorithm is an alternative to the fixed window algorithm designed to reduce bursts. This is the same example as above, but then using a 1 hour window that slides over the timeline:

As you can see, this removes the edges of the window and would prevent the 6th request at 11:45.

To achieve this, the rate limit is approximated based on the current window and the previous window.

For example: the limit is 5,000 requests per hour; a user made 4,000 requests the previous hour and 500 requests this hour. 15 minutes in to the current hour (25% of the window) the hit count would be calculated as: 75% * 4,000 + 500 = 3,500. At this point in time the user can only do 1,500 more requests.

The math shows that the closer the last window is, the more the hit count of the last window will affect the current limit. This will make sure that a user can do 5,000 requests per hour but only if they are evenly spread out.

Token Bucket Rate Limiter

This technique implements the token bucket algorithm, which defines continuously updating the budget of resource usage. It roughly works like this:

  1. A bucket is created with an initial set of tokens;
  2. A new token is added to the bucket with a predefined frequency (e.g. every second);
  3. Allowing an event consumes one or more tokens;
  4. If the bucket still contains tokens, the event is allowed; otherwise, it's denied;
  5. If the bucket is at full capacity, new tokens are discarded.

The below diagram shows a token bucket of size 4 that is filled with a rate of 1 token per 15 minutes:

This algorithm handles more complex back-off burst management. For instance, it can allow a user to try a password 5 times and then only allow 1 every 15 minutes (unless the user waits 75 minutes and they will be allowed 5 tries again).

Installation

Before using a rate limiter for the first time, run the following command to install the associated Symfony Component in your application:

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$ composer require symfony/rate-limiter

Configuration

The following example creates two different rate limiters for an API service, to enforce different levels of service (free or paid):

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# config/packages/rate_limiter.yaml
framework:
    rate_limiter:
        anonymous_api:
            # use 'sliding_window' if you prefer that policy
            policy: 'fixed_window'
            limit: 100
            interval: '60 minutes'
        authenticated_api:
            policy: 'token_bucket'
            limit: 5000
            rate: { interval: '15 minutes', amount: 500 }

Note

The value of the interval option must be a number followed by any of the units accepted by the PHP date relative formats (e.g. 3 seconds, 10 hours, 1 day, etc.)

In the anonymous_api limiter, after making the first HTTP request, you can make up to 100 requests in the next 60 minutes. After that time, the counter resets and you have another 100 requests for the following 60 minutes.

In the authenticated_api limiter, after making the first HTTP request you are allowed to make up to 5,000 HTTP requests in total, and this number grows at a rate of another 500 requests every 15 minutes. If you don't make that number of requests, the unused ones don't accumulate (the limit option prevents that number from being higher than 5,000).

Rate Limiting in Action

After having installed and configured the rate limiter, inject it in any service or controller and call the consume() method to try to consume a given number of tokens. For example, this controller uses the previous rate limiter to control the number of requests to the API:

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// src/Controller/ApiController.php
namespace App\Controller;

use Symfony\Bundle\FrameworkBundle\Controller\AbstractController;
use Symfony\Component\HttpFoundation\Request;
use Symfony\Component\HttpKernel\Exception\TooManyRequestsHttpException;
use Symfony\Component\RateLimiter\RateLimiterFactory;

class ApiController extends AbstractController
{
    // if you're using service autowiring, the variable name must be:
    // "rate limiter name" (in camelCase) + "Limiter" suffix
    public function index(Request $request, RateLimiterFactory $anonymousApiLimiter)
    {
        // create a limiter based on a unique identifier of the client
        // (e.g. the client's IP address, a username/email, an API key, etc.)
        $limiter = $anonymousApiLimiter->create($request->getClientIp());

        // the argument of consume() is the number of tokens to consume
        // and returns an object of type Limit
        if (false === $limiter->consume(1)->isAccepted()) {
            throw new TooManyRequestsHttpException();
        }

        // you can also use the ensureAccepted() method - which throws a
        // RateLimitExceededException if the limit has been reached
        // $limiter->consume(1)->ensureAccepted();

        // to reset the counter
        // $limiter->reset();

        // ...
    }
}

Note

In a real application, instead of checking the rate limiter in all the API controller methods, create an event listener or subscriber for the kernel.request event and check the rate limiter once for all requests.

Wait until a Token is Available

Instead of dropping a request or process when the limit has been reached, you might want to wait until a new token is available. This can be achieved using the reserve() method:

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// src/Controller/ApiController.php
namespace App\Controller;

use Symfony\Bundle\FrameworkBundle\Controller\AbstractController;
use Symfony\Component\HttpFoundation\Request;
use Symfony\Component\RateLimiter\RateLimiterFactory;

class ApiController extends AbstractController
{
    public function registerUser(Request $request, RateLimiterFactory $authenticatedApiLimiter)
    {
        $apiKey = $request->headers->get('apikey');
        $limiter = $authenticatedApiLimiter->create($apiKey);

        // this blocks the application until the given number of tokens can be consumed
        $limiter->reserve(1)->wait();

        // optional, pass a maximum wait time (in seconds), a MaxWaitDurationExceededException
        // is thrown if the process has to wait longer. E.g. to wait at most 20 seconds:
        //$limiter->reserve(1, 20)->wait();

        // ...
    }

    // ...
}

The reserve() method is able to reserve a token in the future. Only use this method if you're planning to wait, otherwise you will block other processes by reserving unused tokens.

Note

Not all strategies allow reserving tokens in the future. These strategies may throw a ReserveNotSupportedException when calling reserve().

In these cases, you can use consume() together with wait(), but there is no guarantee that a token is available after the wait:

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// ...
do {
    $limit = $limiter->consume(1);
    $limit->wait();
} while (!$limit->isAccepted());

Exposing the Rate Limiter Status

When using a rate limiter in APIs, it's common to include some standard HTTP headers in the response to expose the limit status (e.g. remaining tokens, when new tokens will be available, etc.)

Use the RateLimit object returned by the consume() method (also available via the getRateLimit() method of the Reservation object returned by the reserve() method) to get the value of those HTTP headers:

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// src/Controller/ApiController.php
namespace App\Controller;

use Symfony\Bundle\FrameworkBundle\Controller\AbstractController;
use Symfony\Component\HttpFoundation\Request;
use Symfony\Component\HttpFoundation\Response;
use Symfony\Component\RateLimiter\RateLimiterFactory;

class ApiController extends AbstractController
{
    public function index(Request $request, RateLimiterFactory $anonymousApiLimiter)
    {
        $limiter = $anonymousApiLimiter->create($request->getClientIp());
        $limit = $limiter->consume();
        $headers = [
            'X-RateLimit-Remaining' => $limit->getRemainingTokens(),
            'X-RateLimit-Retry-After' => $limit->getRetryAfter()->getTimestamp() - time(),
            'X-RateLimit-Limit' => $limit->getLimit(),
        ];

        if (false === $limit->isAccepted()) {
            return new Response(null, Response::HTTP_TOO_MANY_REQUESTS, $headers);
        }

        // ...

        $response = new Response('...');
        $response->headers->add($headers);

        return $response;
    }
}

Storing Rate Limiter State

All rate limiter policies require to store their state (e.g. how many hits were already made in the current time window). By default, all limiters use the cache.rate_limiter cache pool created with the Cache component. This means that every time you clear the cache, the rate limiter will be reset.

You can use the cache_pool option to override the cache used by a specific limiter (or even create a new cache pool for it):

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# config/packages/rate_limiter.yaml
framework:
    rate_limiter:
        anonymous_api:
            # ...

            # use the "cache.anonymous_rate_limiter" cache pool
            cache_pool: 'cache.anonymous_rate_limiter'

Note

Instead of using the Cache component, you can also implement a custom storage. Create a PHP class that implements the StorageInterface and use the storage_service setting of each limiter to the service ID of this class.

Using Locks to Prevent Race Conditions

Race conditions can happen when the same rate limiter is used by multiple simultaneous requests (e.g. three servers of a company hitting your API at the same time). Rate limiters use locks to protect their operations against these race conditions.

By default, Symfony uses the global lock configured by framework.lock, but you can use a specific named lock via the lock_factory option (or none at all):

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# config/packages/rate_limiter.yaml
framework:
    rate_limiter:
        anonymous_api:
            # ...

            # use the "lock.rate_limiter.factory" for this limiter
            lock_factory: 'lock.rate_limiter.factory'

            # or don't use any lock mechanism
            lock_factory: null

5.3

The login throttling doesn't use any lock since Symfony 5.3 to avoid extra load.

This work, including the code samples, is licensed under a Creative Commons BY-SA 3.0 license.
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