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Regulator

Regulator provides adaptive concurrency limits around external resources.

Regulator.install(:service, {Regulator.Limit.AIMD, [timeout: 500]})

Regulator.ask(:service, fn ->
  Finch.request(:get, "https://keathley.io")
end)

Why do I need this?

If you're used to circuit breakers, you can think of Regulator as an adaptive, dynamic circuit breaker. Regulator determines if there are errors or potential for errors by measuring the running system. When it detects errors - more specifically it detects queueing - it begins to lower the number of concurrent things that can happen in the system.

For instance, Regulator has determined that it can allow 4 concurrent requests to a downstream API, and 4 requests are initiated, any further requests will be rejected immediately.

Rejecting the request allows you, the programmer, to determine what to do if Regulator is shedding load. here's an example where we will normally serve requests from a downstream system, but under load shedding, we return a cached value.

def fetch(id) do
  case Regulator.ask(:service) do
    {:ok, token} ->
      case api_call(id) do
        {:ok, resp} ->
          :ok = Regulator.ok(token)
          :ok = Cache.put(id, resp)
          {:ok, resp}

        {:error, error} ->
          Regulator.error(token)
          {:error, error}
      end

    :dropped ->
      case Cache.get(id) do
        nil ->
          {:error, :not_found}

        resp ->
          {:ok, resp}
      end
  end)
end

Limit algorithms

Regulator provides different limit algorithms for different use cases; AIMD, Gradient, and Static.

AIMD updates the concurrency limit using a technique known as "additive increase, multiplicative decrease". If regulator detects that more concurrency tokens are required, no errors have ocured, and the average latency is below the target value, Regulator will additively increase the concurrency limit. If there are errors or the average latency begins to rise, than regulator will multiplicatively decrease the limit.

The Gradient limit algorithm looks at the gradient of change between long term latency and the current average latency. If this gradient of change begins to exceed acceptable bounds, the limiter will begin to decrease the concurrency limit.

The static limit simply uses a fixed value which is never updated.

Should I use this

There are additional tests that need to be added and there may be performance improvements required around concurrency token monitoring. But, this has been used heavily in production and has supported 10s of thousands of requests per second. I feel confident in saying that you can use this in production at this point.