Services & Filters

Services and filters constitute the core abstractions with which clients and servers are constructed with the Finagle network library. They are very simple, but also quite versatile. Most of Finagle’s internals are structured around Services and Filters.


A service, at its heart, is a simple function:

trait Service[Req, Rep] extends (Req => Future[Rep])

Put another way, a service takes some request of type Req and returns to you a Future representing the eventual result (or failure) of type Rep.

Services are used to represent both clients and servers. An instance of a service is used through a client; a server implements a Service.

To use an HTTP client:

import com.twitter.finagle.Service
import com.twitter.finagle.http

val httpService: Service[http.Request, http.Request] = ???

httpService(Request("/foo/bar")).onSuccess { response: http.Response =>
  println("received response " + response.contentString)

or to provide an HTTP server:

import com.twitter.finagle.Service
import com.twitter.finagle.http
import com.twitter.util.Future

val httpService = new Service[http.Request, http.Response] {
  def apply(req: http.Request): Future[http.Response] =
    Future.value(Response()) // HTTP 200

Services implement application logic. You might, for instance, define a Service[http.Request, http.Response] to implement your application’s external API.


It is often useful to define application-agnostic behavior as well. A common example of this is to implement timeouts: if a request fails to complete within a certain time, the timeout mechanism fails it with a timeout exception.

Like services, filters are also simple functions:


or: given a request of type ReqIn and a service of type Service[ReqOut, RepIn], return a Future of type RepOut (the reply type). All types are parameterized so that filters may also transform request or reply types; visualized:


In most common cases, ReqIn is equal to ReqOut, and RepIn is equal to RepOut — this is in fact sufficiently common to warrant its own alias:

trait SimpleFilter[Req, Rep] extends Filter[Req, Rep, Req, Rep]

This, then, is a complete definition of a timeout filter:

import com.twitter.finagle.{Service, SimpleFilter}
import com.twitter.util.{Duration, Future, Timer}

class TimeoutFilter[Req, Rep](timeout: Duration, timer: Timer)
  extends SimpleFilter[Req, Rep] {

    val res = service(request)
    res.within(timer, timeout)

The filter is given a request and the next service in the filter chain. It then dispatches this request, applying a timeout on the returned Futurewithin is a method on Future which applies the given timeout, failing the future with a timeout exception should it fail to complete within the given deadline.

Composing filters and services

Filters and services compose with the andThen method. For example to furnish a service with timeout behavior:

import com.twitter.finagle.Service
import com.twitter.finagle.http

val service: Service[http.Request, http.Response] = ...
val timeoutFilter = new TimeoutFilter[http.Request, http.Response](...)

val serviceWithTimeout: Service[http.Request, http.Response] =

Applying a filter to a Service produces a new Service whose requests are first filtered through timeoutFilter.

We can also compose filters with andThen, creating composite filters, so that

import com.twitter.finagle.Filter
import com.twitter.finagle.service.RetryFilter

def retry[Req, Rep]: RetryFilter[Req, Rep] = ???
def retryWithTimeoutFilter[Req, Rep]: Filter[Req, Rep, Req, Rep] =
  retry[Req, Rep].andThen(new TimeoutFilter[Req, Rep](...))

creates a filter that dispatches requests first through retryFilter and then timeoutFilter.


In certain modules, it’s important to take into account the process of acquiring a Service. For example, a connection pool would need to play a significant role in the Service acquisition phase. The ServiceFactory exists for this exact reason. It produces Service‘s over which requests can be dispatched. Its definition:

abstract class ServiceFactory[-Req, +Rep]
  extends (ClientConnection => Future[Service[Req, Rep]])

Internally, Finagle makes heavy use of this. In Finagle’s client and server stacks, modules are lifted into ServiceFactories and then composed using the aforementioned combinators.