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Provides a low-level time-based throttle. Is mainly meant for situations where using something like Rack::Attack is not very useful since you need access to more variables. Under the hood, this uses a Lua script that implements the Leaky Bucket algorithm in a single threaded and race condition safe way.

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Add this line to your application's Gemfile:

gem 'prorate'

And then execute:

bundle install

Or install it yourself as:

gem install prorate


The simplest mode of operation is throttling an endpoint, using the throttler before the action happens.

Within your Rails controller:

t =
    logger: Rails.logger,
    name: "throttle-login-email",
    limit: 20,
    period: 5.seconds
# Add all the parameters that function as a discriminator.
t << request.ip << params.require(:email)
# ...and call the throttle! method
t.throttle! # Will raise a Prorate::Throttled exception if the limit has been reached
# Your regular action happens after this point

To capture that exception, in the controller

rescue_from Prorate::Throttled do |e|
  response.set_header('Retry-After', e.retry_in_seconds.to_s)
  render nothing: true, status: 429

Throttling and checking status

More exquisite control can be achieved by combining throttling (see previous step) and - in subsequent calls - checking the status of the throttle before invoking the throttle. When you call throttle!, you add tokens to the leaky bucket.

Let's say you have an endpoint that not only needs throttling, but you want to ban credential stuffers outright. This is a multi-step process:

  1. Respond with a 429 if the discriminators of the request would land in an already blocking 'credential-stuffing'-throttle
  2. Run your regular throttling
  3. Perform your sign in action
  4. If the sign in was unsuccessful, add the discriminators to the 'credential-stuffing'-throttle

In your controller that would look like this:

t =
    logger: Rails.logger,
    name: "credential-stuffing",
    limit: 20,
    period: 20.minutes
# Add all the parameters that function as a discriminator.
t << request.ip
# And before anything else, check whether it is throttled
if t.status.throttled?
  response.set_header('Retry-After', t.status.remaining_throttle_seconds.to_s)
  render(nothing: true, status: 429) and return

# run your regular throttles for the endpoint!)
# Perform your sign in logic..

user = YourSignInLogic.valid?(
  email: params[:email],
  password: params[:password]

# Add the request to the credential stuffing throttle if we didn't succeed
t.throttle! unless user

# the rest of your action

To capture that exception, in the controller

rescue_from Prorate::Throttled do |e|
  response.set_header('Retry-After', e.retry_in_seconds.to_s)
  render nothing: true, status: 429

Using just the leaky bucket

There is also an object for using the heart of Prorate (the leaky bucket) without blocking or exceptions. This is useful if you want to implement a more generic rate limiting solution and customise it in a fancier way. The leaky bucket on it's own provides the following conveniences only:

  • Track the number of tokens added and the number of tokens that have leaked
  • Tracks whether a specific token fillup has overflown the bucket. This is only tracked momentarily if the bucket is limited

Level and leak rate are computed and provided as Floats instead of Integers (in the Throttle class). To use it, employ the LeakyBucket object:

# The leak_rate is in tokens per second
leaky_bucket =, redis_key_prefix: "user123", leak_rate: 0.8, bucket_capacity: 2)
leaky_bucket.state.level #=> will return 0.0
leaky_bucket.state.full? #=> will return "false"
state_after_add = leaky_bucket.fillup(2) #=> returns a State object_
state_after_add.full? #=> will return "true"
state_after_add.level #=> will return 2.0

Why Lua?

Prorate is implementing throttling using the "Leaky Bucket" algorithm and is extensively described here. The implementation is using a Lua script, because is the only language available which runs inside Redis. Thanks to the speed benefits of Lua the script runs fast enough to apply it on every throttle call.

Using a Lua script in Prorate helps us achieve the following guarantees:

  • The script will run atomically. The script is evaluated as a single Redis command. This ensures that the commands in the Lua script will never be interleaved with another client: they will always execute together.
  • Any usages of time will use the Redis time. Throttling requires a consistent and monotonic time source. The only monotonic and consistent time source which is usable in the context of Prorate, is the TIME result of Redis itself. We are throttling requests from different machines, which will invariably have clock drift between them. This way using the Redis server TIME helps achieve consistency.


After checking out the repo, run bin/setup to install dependencies. Then, run rake spec to run the tests. You can also run bin/console for an interactive prompt that will allow you to experiment.

To install this gem onto your local machine, run bundle exec rake install. To release a new version, update the version number in version.rb, and then run bundle exec rake release, which will create a git tag for the version, push git commits and tags, and push the .gem file to


Bug reports and pull requests are welcome on GitHub at


The gem is available as open source under the terms of the MIT License.


Redis-based rate limiter (with a leaky bucket implementation in Lua)








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