Distributed Websocket server with Akka HTTP

The goal of my previous post was to handle each websocket connection with an actor. This post goes on to achieve the same thing in a distributed setting.

As described in the Server Side Websocket Support page of Akka Http, a Websocket connection is modelled as a Flow that ingests messages and returns messages.
In order to achieve a full bi-directional communication, where messages can independently be sent to the other end, the handling actor needs a way to “enter” such flow without a request from the connected client. The trick (inspired by
this post by Bartek Kalinka) is to pre-materialize a Source.actorRef connected to a publisher Sink.

val (down, publisher) = Source
.actorRef[String](1000, OverflowStrategy.fail)
.toMat(Sink.asPublisher(fanout = false))(Keep.both)
.run()


At this point, each message sent to the down actorRef will end up in the publisher Sink. We can then create a Source out of this sink, and use that source as the output for the Websocket Flow required by Akka Http.

So far, same as previous post. The missing step is, how to connect this source originating on a remote node? This is what we want to achieve:

StreamRef to the rescue

The glorious Akka Streams library has everything we need. An experimental feature lets us materialize a local Source into a StreamRef. You can think of that as the equivalent of ActorRef for Streams; to name one, they both accomplish location transparency. We can then pass the reference to the server and create there the handling Flow.

In this example, as the server receives an incoming Websocket connection, it asks its supervisor to provide a materialized source for streaming down messages:

type HandlingFlow = Flow[Message, Message, _]
val routes = path("connect") {
info(s"client connected")
val futureFlow = (supervisor ? ProvideConnectionHandler) (3.seconds).mapTo[HandlingFlow]
onComplete(futureFlow) {
case Success(flow) => handleWebSocketMessages(flow)
case Failure(err) => complete(HttpResponse(StatusCodes.InternalServerError, entity = HttpEntity(err.getMessage)))
}
}


The supervisor forwards the request to one of the registered handling nodes - here chosen randomly:

case pch@ProvideConnectionHandler =>
// forward it to a random node, if any
val chosenNode = nodes(Random.nextInt(nodes.size))
(chosenNode ? pch) (3.seconds) .... // more details below


The handling actor, running on a remote node does a few things:

• Upon creation, registers with the listener node.
• Creates a source of Strings and materialises it as a remote source.
• Pushes a greeting down that source every time it receives a message.
class Handler extends Actor with LogSupport {

implicit val as = context.system
implicit val am = ActorMaterializer()

// make sure that we register only once we are effectively up
val cluster = Cluster(as)
cluster registerOnMemberUp {
}

// every message this actor sends to the down actorRef will end up in the publisher sink...
val (down, publisher) = Source
.actorRef[String](1000, OverflowStrategy.fail)
.toMat(Sink.asPublisher(fanout = false))(Keep.both)
.run()

// ... and every message in the publisher sink will be published by this Source. The final effect is
// that messages sent to the down actorRef will be published to this source.
val streamRef = Source.fromPublisher(publisher).runWith(StreamRefs.sourceRef())

case ProvideConnectionHandler =>
// send the streamRef reference back
streamRef.map(ConnectionHandler(self, _)).pipeTo(sender)

case s: String =>
// in this example, all strings coming in are from the websocket client. Reply with a salute.
down ! "Hello " + s + "!"
}

}


Once the SourceRef has come back, the supervisor can create the needed flow:

case pch@ProvideConnectionHandler =>
// forward it to a random node, if any
val chosenNode = nodes(Random.nextInt(nodes.size))
(chosenNode ? pch) (3.seconds)
.mapTo[ConnectionHandler]
.map { case ConnectionHandler(handlingActor, sourceRef) =>

// create a handling flow to send back
Flow.fromGraph(GraphDSL.create() { implicit b =>

.mapAsync(1) {
case tm: TextMessage => tm.toStrict(3.seconds).map(_.text)
case bm: BinaryMessage =>
bm.dataStream.runWith(Sink.ignore)
Future.failed(new Exception("yuck"))
})

// map strings coming from this source to TextMessage

// forward each message to the handling actor
textMsgFlow ~> Sink.foreach[String](handlingActor ! _)

FlowShape(textMsgFlow.in, pubSrc.out)
})
}
.pipeTo(sender)


Full code is available on a GitHub repository. Note that this code is not meant for production - the StreamRef feature itself is marked as ‘may change’ at the moment of writing: thread carefully! (Pun intended.)