A leaky bucket rate limiter and corresponding middleware with route-level granularity compatible with Laravel.

1.1.0 2024-03-14 14:52 UTC

This package is auto-updated.

Last update: 2024-05-14 15:21:17 UTC


A leaky bucket rate limiter and corresponding middleware with route-level granularity compatible with Laravel.

Table of Contents


The package installs into a PHP application like any other PHP package:

composer require artisansdk/ratelimiter

Once installed, you will need to bind your choice of Bucket implementations for the rate Limiter class. Choose either the Leaky or the Leaky Evented bucket if you need additional event dispatching. Add the following lines to your App\Providers\AppServiceProvider:

use ArtisanSdk\RateLimiter\Buckets\Leaky;
use ArtisanSdk\RateLimiter\Contracts\Bucket;

public function register()
    $this->app->bind(Bucket::class, Leaky::class);

If you do plan on using the Evented leaky bucket then you'll also want to change to the following binding to your register() method. The event dispatcher is injected automatically by Laravel:

use ArtisanSdk\RateLimiter\Buckets\Evented;
use ArtisanSdk\RateLimiter\Contracts\Bucket;

public function register()
    $this->app->bind(Bucket::class, Evented::class);

The package includes middleware for the rate limiter which is compatible with Laravel's built in Illuminate\Routing\Middleware\ThrottleRequests. Simply update the App\Http\Kernel::$routeMiddleware array so that the throttle key points to ArtisanSdk\RateLimiter\Middleware like so:

protected $routeMiddleware = [
    // ...
    'throttle' => \ArtisanSdk\RateLimiter\Middleware::class,

Now requests will go through the leaky bucket rate limiter. The requests are throttled according to the algorithm which leaks at rate of 1 request per second (r\s) with a maximum capacity of 60 requests with a 1 minute timeout when the limit is exceeded. This is based on the default Laravel signature of throttle:60,1 which is found in App\Http\Kernel::$middlewareGroups under the api group:

protected $middlewareGroups = [
    // ...
    'api' => [

Change the rates or add throttle:60,1 to the web group as well to rate limit even regular page requests. See the Usage Guide for more options including using the rate limiter and bucket without the middleware.

Usage Guide

Overview of the Laravel Rate Limiter

Laravel shipped without rate limiting for years and so it is a welcomed addition. To be fair, some rate limiting is better than none at all. From a security perspective though, at best Laravel's rate limiter only slows down a hacker, typically trips up legitimate usage, and presents a false sense of security.

Laravel's Implementation

Laravel has a fixed decay rate limiter. With default settings of throttle:60,1 this means that a client could make 60 requests with 1 minute of decay before hitting a 1 minute forced decay timeout. The client could make 60 requests in 1 second or distributed over 60 seconds at a rate of 1 request per second (1 r/s). If the requests are evenly spaced at about 1 r/s then the client will not be rate limited. This means that throttle:120,2 is effectively the same as 1 r/s but tracked for 2 minutes and allowing a larger burst limit up to 120 requests. Meanwhile throttle:120,1 would be an effective rate of 2 r/s with the same burst limit.

Problem 1: Bursting Exploit

Generally you want both of these numbers to be large because that provides more tracking of abuse while allowing for sufficient legitimate requests. For example if the goal is to get 1 r/s average over 24 hours up to 100K requests that would translate to throttle:100000,1440. Every day a client could dump 100K requests in 1 second! So much for 1 r/s load balancing. Furthermore, there's no penalty for abuse – just wait the 1440 minutes and you can do it again as if you made 1 r/s non stop for ever. So you lower it to throttle:3600,60 so bursting is limited to 3600 requests but the rates are reset every hour. There might be a sweet spot but it is hard to get just right.

Problem 2: No Granularity

Also the signature for the client is determined by the domain and IP address of the requester. While most hackers will randomize their IP and almost all rate limiters suffer from this (and the shared IP address issue common on public networks), all requests made by a user dump into the same cache of hits for that client. So you set your throttler differently for different routes like throttle:10,10 for a user login screen vs. throttle:60,1 for other routes because you hear you are suppose to rate limit resources according to their typical usage. Instead of working you find your users hit rate limits because they made a lot of requested against one route that tripped the rate limiter on another. So you raise the limits because that sounds like the simple fix but it turns out you just increased your attack surface area.

Problem 3: Not Extensible

If the user is logged in, Laravel does use the unique identifier for the user as the key which is better than the IP address. Even better, different rates for different users using a string based key like throttle:60|rate_limit which translates to 60 requests by guests and whatever Auth::user()->rate_limit returns for users (or if you use the Laravel suggested throttle:rate_limit value, it will actually be the same as throttle:0 for guests). That's all fine but you want to rate limit the resources the user accesses differently. The only answer to that problem is to hack the Illuminate\Routing\Middleware\ThrottleRequests middleware and overload the resolveRequestSignature() method to return your custom key. Oh, and let's not forget that the same decay rate is used for both guests and authenticated users so you have to grok your way through that inadvertent security coupling.

Understanding the Leaky Bucket Algorithm

The answer to Laravel's rate limiter is a better algorithm that includes a couple of additional configuration settings.

Leaky Bucket Implementation

The Leaky Bucket Algorithm is the rate limiter this package implements. As its name suggests, there is a bucket (a cache) that you fill with drips (a request) up to the maximum capacity (the limit) at which point if you continue filling it will overflow (rate limiting). This bucket also leaks at a constant rate of drips per second (requests per second). This means that if you fill the bucket with drips at the same rate in which it leaks then you can continue hitting it forever without overflowing. You can also burst up to the maximum capacity which has no effect on the leak rate. So effectively the Leaky Bucket Algorithm enforces a constant drip rate determined not by the number of drips added to the bucket but by the leak rate in constant time. Since the algorithm tracks leaks and buckets and not just drips, buckets can be persisted for a longer time to track malicious activity longer and rate limit a more balanced request load.

Solution 1: Bursting Limit

As already, explained bursting is an exploit that a hacker can use against the Laravel rate limiter and to monitor (increase the limits) the exploit makes the attack surface area even bigger. The bursting limit in a Leaky Bucket implementation is a separate limit that does not expire in a binary, all or nothing, way but expires one drip at a time as the bucket leaks. With this implementation you set the bursting limit and that limit drains slowly over time at the constant leak rate. This means that so long as the client does not exceed the limits and enters a timeout, the client can burst up to this limit then wait as little as the leak rate to make one more request. They can trickle in requests constantly so long as they don't overflow the bucket's maximum capacity.

For example if the settings were throttle:60,1 then the user can burst up in the first second to 60 requests, and only has to wait 1 second to make a subsequent request but if they make 2 requests then they'll overflow which introduces the timeout penalty. The more time the client rests the more requests per second they can make. The two configurations in the settings translate to the 60 maximum requests allowed when bursting and effectively an average request per second rate of 1 r/s (technically it's 1 leak per second or 1 l/s). Now setting higher limits represents increased performance, and since they are independent of each other, configuration is clear with respect to its effect.

Solution 2: Route-Level Granularity

As mentioned, Laravel's built in key resolver for determining what a unique client is simply based on the guest's IP address or the authenticated user's identifier. There's no more granularity than this and any attempt to introduce granularity feels like a hack or is riddled with complexity. Instead, this rate limiter ships with a couple of different resolvers including ArtisanSdk\RateLimiter\Resolver\Route class which attempts to match the client against rates specific to the URI they are requesting. This is done firstly by the route's name, falling back to the route's controller method, before finally just using the URI. If none of these fallbacks can be resolved, it'll just revert back to default behavior of resolving to the guest's IP address or authenticated user's identifier. To use this resolver, you simply set it in the route binding like so throttle:ArtisanSdk\RateLimiter\Resolver\Route,60,1.

The rate limiter implements a Leaky Bucket and as such granularity for one bucket needs to apply to the greater limits applied to the user's more global limits. This implementation uses a multi-bucket solution. The bucket's rates cascade from outside in from more global to more specific. You can imagine the more granular route-level rates as being a subset of the more user-level rate limits so a hit against the route-level rates counts as a hit against the user-level rates. If either one of them is tripped then that bucket's limits are in effect. Different routes share the same parent user-level buckets but have separate bucket limits themselves so tripping only a route-level bucket will prevent further requests to that route, while other routes may be still active. This use case is good for when you need to limit a specific resource to a lower threshold of requests while simultaneously limiting the user to daily maximum requests.

Solution 3: Extensible Key Resolvers

Both Laravel's rate limiter and this Leaky Bucket rate limiter use cache keys to save the hits against the rate limiter by a given client. The default resolver for this key is the same in both rate limiters. The way in which these resolvers are defined is different: this package makes use of a separate resolver class that you can customize and mixin when configuring the routes themselves. The package ships with three built-in resolvers and you can create your own very easily:

  • Limit by IP/User (default): ArtisanSdk\RateLimiter\Resolvers\User
  • Limit by Route: ArtisanSdk\RateLimiter\Resolvers\Route
  • Limit by Tag: ArtisanSdk\RateLimiter\Resolvers\Tag

Because the User resolver is the default, you do not have to specify the resolver at all which makes throttle and throttle:\ArtisanSdk\RateLimiter\Resolvers\User equivalent. The normal bindings of throttle:60,1 still apply and are just added on the end like so throttle:\ArtisanSdk\RateLimiter\Resolvers\User,60,1. To use a different resolver (which all default back to the User resolver) just make it the first parameter like so throttle:\ArtisanSdk\RateLimiter\Resolvers\Route,60,1.

You can define your own resolvers and call them the same way like throttle:\App\Http\FooBarResolver and just implement the ArtisanSdk\RateLimiter\Contracts\Resolver interface on your custom resolver. Extensibility built right in. Resolvers can therefore also be used to share and reuse typical throttling settings so no more magic numbers in your route bindings. For example throttle:\App\Http\UserResourceLimits, throttle:\App\Http\HighLimits, or throttle:\App\Http\SlowLimits.

Bonus: Overflow Penalties

This package's implementation also puts a customizable penalty on the filler (the client) if they overflow (exceed the bursting limits). This is done in the form of a third configuration setting such as throttle:60,1,60. The default value is 60 minute which is close to the default behavior of Laravel's rate limiter. This value however is independent of all the others whereas Laravel's is coupled to the decay time. This third configuration sets a penalty in seconds the client must rest before making another request. This is enforced even if the bursting rates would normally reset according to the leak rate. For example, a throttle:60,1,600 would enact a 600 second (10 minute) timeout for exceeding the 60 requests burst limit. This would slow down a hacker 10x more than with Laravel's built in rate limiter.

Furthermore the timeout is customizable differently for guests vs. authenticated users by using the split configuration such as throttle:60|100,1|10,86400|3600. This would translate to a guest being able to make up to 60 requests at once or at a constant rate of 1 r/s and if they violate these rules then they will have exceeded their daily limit and be rate limited for 24 hours (86400 seconds). Meanwhile, an authenticated user can make up to 100 requests at once or at a constant rate of 10 r/s all day long (846K requests per day) and if they violate the rules then they go into only a 60 minute (3600 second) timeout. Using the route-based rate limiter for a login route you could do something like throttle:Resolvers\Route::class,3,0.1,600 which would limit the login to 1 request every 10 seconds (1r/10s --> 0.1 r/s) and up to 3 in 10 seconds with any violators being banned for 10 minutes (600 minutes).

Different Rates for Guests vs. Authenticated Users

Chances are you don't trust your guests as much as you do your authenticated users. In reality you should trust no one but this packages makes it easier to segment rates that should apply to guests and the rates that apply to authenticated users. Laravel uses the pipe (|) separate convention to accomplish this with the configuration settings so this package extends that behavior. The guest's value will be on the left of the pipe while the user's value will be on the right of the pipe. An example would be throttle:60|120 which would apply a limit of 60 requests for guests and 120 requests for users. You can alternatively provide a string on the user side of the pipe to dynamically set the rate from the authenticated user such as throttle:60,rate_limit or just throttle:rate_limit if you're OK with 0 being inferred for the guest side.

All of the configuration settings for max, rate, and duration are configurable this way (something Laravel's rate limiter doesn't do) so you can pass pipe-separated limits for guests and users for any of these settings. The signature format is of the form throttle:max|rate|duration. For example you could do: throttle:60|120,1|2,300|60 to set the following limits:

Burst Limit Leak Rate Timeout Duration
Guest 60 requests 1 r/s 300 seconds
User 120 requests 2 r/s 60 seconds

Additionally all the user limits accept a string which may be used to fetch the value dynamically from the authenticated user. Even if you do not support a database driven value, you could create an attribute getter on the App\User model to get the value as a constant or based on some value.

Different Rates for Different Users

Chances are you have a combination of tiered SaaS plans, admin and regular users, a mobile app that makes heavier use of your API than your web app does, or just that one user who seems to thinks they need to hammer that page. You'll want to have different rates for different users in other words. You can of course segment guests from users but that is a broad stroke. You want more fine grain control and this package makes that easier. You can define a custom rate per user for every rate setting including the max, rate, and duration. Simply provide a string instead of a number for the configuration value such as throttle:max_limit,rate_limit,duration_limit which map to a call such as Auth::user()->max_limit, Auth::user()->rate_limit, etc. Now Bob and Suzy can have different rates pulled back from their user profile.

Anything more sophisticated than that and you'll want to use a custom resolver. For example if you use this with the Tag or Route resolver then you'll likely be wanting to set different user rates for different resources or routes. For that you'll implement a rates table to setup the fine grain controls per user. You'll have to implement a custom resolver to fetch the limits in that case. You can checkout the ArtisanSdk\RateLimiter\Resolvers\User::parse() method for some inspiration on how to query the authenticated user for the limits.

Handling the Rate Limit Exceptions

Whenever a client is rate limited there is an exception thrown. The exception is the ArtisanSdk\RateLimiter\Exception which roughly maps to the Illuminate\Caching\Exceptions\TooManyAttempts exception which likewise extends a Symfony HTTP exception with appropriate 429 Too Many Requests code and message. The built in Laravel exception handler (App\Exceptions\Handler) catches these and renders the appropriate response. Simply custom the Handler::report() and Handler::render() methods to handle the exception differently. For example, you could report the rate limiting as an audit log event on the user's profile for further investigating or reporting of suspicious user activity. Using these logs as a feedback loop you could even increase subsequent penalty rates for that user so that they have to ease back in or suffer increasingly severe backoff penalties to the point of blocking their user permanently.

Setting a Custom Cache for the Rate Limiter

While Laravel is smart enough to resolve your default cache driver, you may specifically want to use specialized Redis or Memcached cache for the hits and timers for the Leaky Buckets. In that case you'll need to register that configuration in your App\Providers\AppServiceProvider class. Just add to your register() method the following (or better, abstract it to its own method):

use ArtisanSdk\RateLimiter\Contracts\Limiter;
use Illuminate\Contracts\Cache\Repository;
use Illuminate\Support\Facades\Cache;

        return Cache::driver('redis');

This binding ensures that when the Limiter is injected into the middleware that it is resolved out of the container using the redis driver instead of the default file driver for the cache Repository needed by the Limiter. You could do something similar if you needed to use a completely different Limiter or set a different default resolver within the middleware.

How Request Signature Resolvers Work

The key resolvers are technically only used by the ArtisanSdk\RateLimiter\Middleware class and their values passed off as request limits to the rate limiter. You can use the resolvers to get the request key and rate limits for other things other than requests, but generally you would only be using them with request throttling via the middleware. A resolver is any class that implements the ArtisandSdk\RateLimiter\Contracts\Resolver interface. The returned values could be anything statically returned or dynamically resolved from the request and other services available to the class. The only resolved value that cannot be overwritten is the key which is used as the signature that identifies the unique request. This signature is the key used to cache the Leaky Bucket. No two users would have the same bucket and no two routes would likewise use the same bucket because the keys would resolve to something different.

How Multiple Buckets Work

The keys are hashed but in raw form they look like| for guests or johndoe[at] for authenticated users. More granular keys such as|127.0.01:/api/foo/bar as used by the Tag and Route resolvers nest using the colon (:) separator. Both sides of the separator are hashed separately such that you could think of the sides as client:bucket where hits against the bucket key count as a hit against the client key as well. Timeout durations resolve from outside in so if the client key is in a timeout, all bucket keys are rate limited as well. Conversely if a bucket key is in a timeout, other buckets may still be available and the parent client key may also still be available. Since multiple buckets for the same client share the same client key, the sum of bucket hits will overflow the client limits resulting in a client timeout and not just a bucket timeout.

Because of the timeouts, clients should attempt to remain at all times within their limits. While every request returns the X-RateLimit headers, the application developer may wish to expose an API endpoint such as /api/rates or deploy some other automated way of informing the client about all the available resources and their respective limits. Included in this response would be the remaining drips available by both the client and the specific resources including the appropriate retry timestamp and back off durations for any resources imposing rate limited timeouts. This would require some sort of global rate store which can be queried and resolved and is outside the scope fo this package. Use could probably reuse the middleware but may need to implement a custom implementation of ArtisandSdk\RateLimiter\Contracts\Limiter.

Using the Built In Resolvers

The package has several built in resolvers with the default being to uniquely identify the user and apply a global rate limit. All other resolvers should fall back to this resolver or create a sub bucket. This ensures that the resolver's more granular rate limits count towards the global rate limit for the user. All of the built in resolvers use the same default settings for the rates including for both guests and authenticated users:

Max Requests Leak Rate Timeout Duration
60 total 1 per second 60 seconds
// Use the current user as the resolver (default)
// The following lines are all the same binding
use ArtisanSdk\RateLimiter\Resolvers\User;

// Add the route to the bucket key to add more granularity
use ArtisanSdk\RateLimiter\Resolvers\Route;

// Add a tag to the bucket key to group related resources
use ArtisanSdk\RateLimiter\Resolvers\Tag;

Creating Custom Resolvers

One of the simplest custom resolvers would be a hard-coded version of the Tag resolver which can be used to create settings objects for throttling related resources. Something like this would do the trick:

use ArtisanSdk\RateLimiter\Resolvers\User as Resolver;
use Symfony\Component\HttpFoundation\Request;

class UserResourceLimits extends Resolver
    protected $max = '50|100'; // 50 drips for guests, 100 drips for users
    protected $rate = '1|10'; // 1 drip per second for guests, 10 drips per second for users
    protected $duration = 3600; // 3600 second (60 minute) timeout
    protected $resource = 'user'; // resource key

    public function __construct(Request $request)
        parent::__construct($request, $this->max, $this->rate, $this->duration);

    public function key(): string
        return parent::key().':'.$this->resource();

    public function resource(): string
        return $this->resource;

Then to use this limiter you would simply bind it on routes like this:

use App\Http\UserResourceLimits;

        $router->get('/', 'UserApi@index');
        $router->get('{id}', 'UserApi@show');

Route::get('/dashboard', 'Dashboard@index');

Each of the /api/user prefixed routes would then log a hit against the user resource bucket while the /dashboard would use the default global limits. A visit to the dashboard would increment the global bucket, while a visit to a user resource endpoint would increment both the user resource bucket and the global bucket. The UserResourceLimits resolver uses the hard-coded values so that there is only one configurable place to customize the settings. This is purposefully closed and if a more extensible solution is needed then the built-in Tag resolver would be a better option.

Setting a Custom Resolver as the Default

Similar to how a custom cache Repository can be injected into the rate Limiter class, a secondary argument allows for the injection of a custom ArtisanSdk\RateLimiter\Contracts\Resolver implementation. The default resolver is ArtisanSdk\RateLimiter\Resolvers\User and to override this, you to bind the custom resolver as default by registering it in your App\Providers\AppServiceProvider class. Just add to your register() method the following (or better, abstract it to it's own method):

use ArtisanSdk\RateLimiter\Middleware;
use App\Http\FooBarResolver;

        return FooBarResolver::class;

This will give the fully-qualified resolver class name to the $resolver variable in the Middleware's constructor which will then be used as the default anytime a more specific route binding is not provided. In this case it is providing the custom App\Http\FooBarResolver as the default.

Using the Rate Limiter by Itself

The Limiter class can be used by itself to persist the leaky Bucket implementation. Essentially the Limiter class is just an abstraction of the Bucket to be more aligned with the concepts of "hits", "limits", and "backoffs" as are often used in rate limiting requests or login attempts. These are not the only things that need be rate limited. You can rate limit the number of reads and writes for models defering to queuing when a certain limit is exceeded. You can rate limit the number of parallel processed jobs. Essentially anything that needs to be limited using the Leaky Bucket Algorithm can use the Limiter class as a standalone rate limiter.

All you need to use the limiter is a persistence layer that implements the Illuminate\Contracts\Cache\Repository interface and an instance of the ArtisanSdk\RateLimiter\Bucket. The Bucket which contains the drips (hits) against the Limiter and is configured with the needed rates and limits, is also instantiated with $key which the Repository service uses to persist the Bucket. For long-running daemons, the Bucket might not even be persisted in which case the Illuminate\Cache\ArrayStore repository may be used.

use ArtisanSdk\RateLimiter\Limiter;
use ArtisanSdk\RateLimiter\Bucket;
use Illuminate\Support\Facades\Cache;

// Configure the limiter to use the default cache driver
// and persist the bucket under the key 'foo' and limit to
// 1 hit per minute or up to the maximum of 10 hits while bursting
$bucket = new Bucket($key = 'foo', $max = 10, $rate = 0.016667);
$limiter = new Limiter(Cache::store(), $bucket);

// Keep popping or queuing jobs until empty or the limit is hit
while(/* some function that gets a job */) {

    // Check that we can proceed with processing
    // This is an abstraction for checking if there's an existing timeout
    // or if the leaky bucket is now overflowing
    if( $limiter->exceeded() ) {

        // Put the bucket in a timeout until it drains
        // or you could use any arbitrary duration (or even allow for overflow)
        $seconds = $bucket->duration();

    // Execute the job and when the work is done, log a hit
    // Unlike the bucket which allows for multiples drips at a time,
    // a rate limiter usually only allows for a single hit at a time.

// Let the caller know when in seconds to try again
return $limiter->backoff();

If you need to use multiple buckets then simply instantiate a bucket with a compound key such as foo:bar. The rate limiter would then apply rates for hits against foo:bar and foo simultaneously. Just change out the lines to be:

$limiter = new Limiter(Cache::store(), new Bucket('foo:bar'));

// or let Laravel handle the cache driver dependencies with
$limiter = app(Limiter::class, ['bucket' => new Bucket('foo:bar')]);

Take a look at ArtisanSdk\RateLimiter\Contracts\Limiter for additional methods you can call or at the concrete implementation ArtisanSdk\RateLimiter\Limiter for non-contract, convenience methods such as reset(), clear(), hasTimeout(), etc. that are unique to the implementation.

Creating a Custom Rate Limiter

If the logic of the rate limiter is not to your liking, you can use the Middleware and the leaky Bucket but implement your own instance of ArtisanSdk\RateLimiter\Contracts\Limiter. Alternatively you could re-implement Laravel's fixed Decay Rate Limiter by modifying the calls that refer to the Leaky Bucket Algorithm with more generic methods on a custom bucket. So long as the Limiter contract is implemented, then the Middleware can be configured to inject your custom Limiter.

Similar to how a custom cache Repository can be injected into the rate Limiter class, the Middleware can receive your custom Limiter as an injected dependency. You bind the custom Limiter by registering it in your App\Providers\AppServiceProvider class. Just add to your register() method the following (or better, abstract it to it's own method):

use App\Http\RateLimiter;
use ArtisanSdk\RateLimiter\Contracts\Limiter;

$this->app->bind(Limiter::class, RateLimiter::class);

Now wherever the type hinted Limiter contract is resolved out of the container, your custom RateLimiter class will be provided instead.

Using the Bucket by Itself

The Bucket class can be used by itself wherever a Leak Bucket Algorithm is needed. All of the algorithm is implemented against an internal in-memory store which can be converted to an array with toArray() or as JSON with toJson(). This allows persistence layers such as a rate Limiter implementation to be just about anything.

For example, the Bucket could be implemented as a new connection pooling and flood controls for a long-running WebSocket server. Whenever a new connection is established, the Bucket is fill() with a drip and when it isFull() then connections could be rejected. Since the Bucket is constantly leaking, new connection can be made at a constant rate, once full. This is especially useful for logic where establishing say up to 100 connections can be done relatively quickly, but once you have that many connections established, adding more involves more coordination and more consideration of resource prioritization for the already established connections. Having a Leaky Bucket lets you control the rate of addition.

The Bucket has a fluent builder interface for configuring itself and as the critical part of the code-base it's worth taking a look under the hood at the raw code. Here's a quick overview of it's public API though:

use ArtisanSdk\RateLimiter\Buckets\Leaky;

$bucket = new Leaky('foo');              // bucket named 'foo' with default capacity and leakage
$bucket = new Leaky('foo', 100, 10);     // bucket holding 100 drips that leaks 10 drips per second
$bucket = new Leaky('foo', 1, 0.016667); // bucket that overflows at more than 1 drip per minute

(new Leaky('foo'))
        'max' => 100,            // 100 drips capacity
        'rate' => 10,            // leaks 10 drips per second
        'drips' => 50,           // already half full
        'timer' => time() - 10,  // created 10 seconds ago
    ->fill(10)                   // add 10 more drips
    ->leak()                     // recalculate the bucket's state
    ->toArray();                 // get array representation for persistence

$bucket = (new Leaky('foo'))     // instantiate the same bucket as above
    ->max(100)                   // $bucket->max() would return 100
    ->rate(10)                    // $bucket->rate() would return 10
    ->drips(50)                  // $bucket->drips() would return 50
    ->timer(time() - 10)         // $bucket->timer() would get the time
    ->fill(10)                   // $bucket->remaining() would return 40
    ->leak();                    // $bucket->drips() would return 30

$bucket->isEmpty();              // false
$bucket->isFull();               // false
$bucket->duration();             // 10 seconds till empty again
$bucket->key();                  // string('foo')
$bucket->reset();                // keeps configuration but reset drips and timer

Using the Evented Bucket

If you consider it, a drip in the bucket represents some sort of event that occurred within the application. At some point you routed your call to log the drip into the bucket. Chances are you could listen for the original event, but if you are dispatching through a command bus, then you might need to log calls to the bucket as events the rest of your application can listen for.

Note: The Evented bucket is an extension of the Leaky bucket that only wraps the parent class with events. All the same builder logic and behavior is the same otherwise.

You can switch from the basic Leaky bucket to the Evented bucket by binding the interface to the concrete the register() method of your App\Providers\AppServiceProvider:

use ArtisanSdk\RateLimiter\Buckets\Evented;
use ArtisanSdk\RateLimiter\Contracts\Bucket;

$this->app->bind(Bucket::class, Evented::class);

And then you can listen for the following events:

  • ArtisanSdk\RateLimiter\Events\Filling
  • ArtisanSdk\RateLimiter\Events\Filled
  • ArtisanSdk\RateLimiter\Events\Leaking
  • ArtisanSdk\RateLimiter\Events\Leaked

If you want to fire events whenever the limiter is exceeded, you'll need to do that in your own code or modify the Limiter itself to also fire events. You could do that by injecting into the constructor the optional implementation of Illuminate\Contracts\Event\Dispatcher and when present the Limiter would fire events for Limiter::hit() and Limiter::timeout() and optionally Limiter::clear() methods.

Logging the Drips in the Bucket

Another way would be to do the decorating of the Bucket at the Limiter level or simply do the eventing directly there. If you notice, the Limiter is the persistence manager for the Bucket anyway and the Bucket simply holds the state while in memory. So with that in mind, you could also modify the Limiter such that a hit() passes an event object to the Bucket which is pushed on to an internal stack of events instead of incrementing an internal counter. Then when the Bucket is persisted instead of simply returning a count of $drips it can return an array of event objects. This opens up the ability to log hits only if they are unique, or to further limit the bucket based on the types of hits received. You could go as far as resolving the right rate bucket to store the hit against based on the event object being passed to hit() method. With a little modification, you could convert the Bucket to an event store.

Running the Tests

The package is unit tested with 100% line coverage and path coverage. You can run the tests by simply cloning the source, installing the dependencies, and then running ./vendor/bin/phpunit. Additionally included in the developer dependencies are some Composer scripts which can assist with Code Styling and coverage reporting:

composer test
composer fix
composer report

See the composer.json for more details on their execution and reporting output.


Copyright (c) 2018-2024 Artisan Made, Co.

This package is released under the MIT license. Please see the LICENSE file distributed with every copy of the code for commercial licensing terms.