sentinel

Boilerplate for creating reactive TCP clients / servers on Akka Streams

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Sentinel

Sentinel is boilerplate for TCP based servers and clients through Using Akka IO and Akka Streams.

The framework's focus is to abstract away the nitty gritty parts of stream based communication to have a solution for reactive TCP communication with reasonable defaults.
Sentinel is designed for usage in persistent connection environments, making it less suited for things like HTTP and best suited for database clients and persistent communication stacks stacks.

Sentinel brings a symmetrical design through Processors, resulting in the same request and response handling on both clients and servers. This not only makes it simple to share code on both sides, but also opens the possibility to inverse request & response flow from server to client.

Status

The current codebase of Sentinel can change heavily over releases.
In overall, treat Sentinel as alpha software.

Currently available in Sentinel:

  • Easy initialization of TCP clients, capable of handing normal request and response based flows as streaming requests and responses.
  • Connection pooling and management and accompanied flow handling for clients.
  • Reactive manner how handling available hosts / endpoints on clients.
  • Basic server template using the same constructs / protocol as client.

The following is currently missing in Sentinel, but will be added soon:

  • A far more solid test suite.
  • Better error handling and recovery.
  • Default functionality for callback based protocols.
  • More solid server implementation, with possibility of direct server to client communication.

(Currently) known issues:

  • There is no active (demand) buffering process within the client; when a stream is requested, but not consumed, additional requests on the same socket aren't demanded and therefore not pulled into new requests.
  • No real performance testing has been done yet, so consider things shaky.

Installation

You can install Sentinel through source (by publishing it into your local Ivy repository):

./sbt publish-local

Or by adding the repo:
"gideondk-repo" at "https://raw.github.com/gideondk/gideondk-mvn-repo/master"

to your SBT configuration and adding Sentinel to your library dependencies (currently only build against Scala 2.11):

libraryDependencies ++= Seq(
"nl.gideondk" %% "sentinel" % "0.8-M1"
)

Architecture

The internal structure of Sentinel relies on the Processor BidiFlow. The Processor represents the connection between a client and a server and handles both the outgoing commands as incoming events through a ProducerStage and ConsumerStage.

Both clients as servers share the same Processor, which results in a symmetrical design for sending and receiving commands. When a message is received from the opposing host, a Resolver is used to determine the action or reaction on the received event. Based on the used protocol (which is defined as an additional BidiFlow, converting ByteStrings to Events and Commands to ByteStrings, a host can process the event and decide whether the consume the received event or to respond with new values (as in a normal request -> response way).

Actions

The handle incoming events, multiple actions are defined which can be used to implement logic on top of the used protocol. Actions are split into consumer actions and producers actions, which make a antenna able to:

Consumer Actions

AcceptSignal: Accept and consume a incoming signal and apply it on a pending registration

AcceptError: Accept a incoming error message and apply it as a failure on a pending registration

ConsumeStreamChunk: Accept a incoming stream chunk and consume add it to the current running stream

EndStream: Accept a incoming stream terminator and end the current ongoing stream

ConsumeChunkAndEndStream: Consumes the chunk and terminates the stream (combination of the two above)

Producer Actions

Signal: Responds to the incoming signal with a new (async) signal

CosumeStream: Starts consuming the stream until a EndStream is received

ProduceStream: Produces a stream (Enumerator) for the requesting hosts

Synchronicity

Normally, Sentinel clients connect to servers through multiple sockets to increase parallel performance on top of the synchronous nature of TCP sockets.

Because of the synchronous nature of the underlying semantics, you have to handle each receiving signal in a appropriate way. Not handling all signals correctly could result in values ending up in incorrect order etc.

Initialization

Resolver

The default resolver for a client is one that automatically accepts all signals. This default behaviour makes it able to handle basic protocols asynchronously without defining a custom resolver on the client side.

It's easy to extend the behaviour on the client side for receiving stream responses by defining a custom Resolver:

trait DefaultSimpleMessageHandler extends Resolver[SimpleMessageFormat, SimpleMessageFormat] {
   def process(implicit mat: Materializer): PartialFunction[SimpleMessageFormat, Action] = {
    case SimpleStreamChunk(x)              ⇒ if (x.length > 0) ConsumerAction.ConsumeStreamChunk else ConsumerAction.EndStream
    case x: SimpleError                    ⇒ ConsumerAction.AcceptError
    case x: SimpleReply                    ⇒ ConsumerAction.AcceptSignal
    case SimpleCommand(PING_PONG, payload) ⇒ ProducerAction.Signal { x: SimpleCommand ⇒ Future(SimpleReply("PONG")) }
  }
}

object SimpleClientHandler extends DefaultSimpleMessageHandler

In a traditional structure, a different resolver should be used on the server side, handling incoming requests and responding with the appropriate response. The partial function taking a event and resulting in a action fully exposes the event to route the messages to the current action:

object SimpleServerHandler extends DefaultSimpleMessageHandler {

  def process(implicit mat: Materializer): PartialFunction[SimpleMessageFormat, Action] = {
    case SimpleStreamChunk(x)              ⇒ if (x.length > 0) ConsumerAction.ConsumeStreamChunk else ConsumerAction.EndStream
    case SimpleCommand(PING_PONG, payload) ⇒ ProducerAction.Signal { x: SimpleCommand ⇒ Future(SimpleReply("PONG")) }
    case SimpleCommand(TOTAL_CHUNK_SIZE, payload) ⇒ ProducerAction.ConsumeStream { x: Source[SimpleStreamChunk, Any] ⇒
      x.runWith(Sink.fold[Int, SimpleMessageFormat](0) { (b, a) ⇒ b + a.payload.length }).map(x ⇒ SimpleReply(x.toString))
    }
    case SimpleCommand(GENERATE_NUMBERS, payload) ⇒ ProducerAction.ProduceStream { x: SimpleCommand ⇒
      val count = payload.toInt
      Future(Source(List.range(0, count)).map(x ⇒ SimpleStreamChunk(x.toString)) ++ Source.single(SimpleStreamChunk("")))
    }
    case SimpleCommand(ECHO, payload) ⇒ ProducerAction.Signal { x: SimpleCommand ⇒ Future(SimpleReply(x.payload)) }
  }
}

Like illustrated, the ProducerAction.Signal producer action makes it able to respond with a Async response. Taking a function which handles the incoming event and producing a new value, wrapped in a Future.

ProducerAction.ConsumeStream takes a function handling the incoming Source with the consequential chunks, resulting in a new value wrapped in a Future

ProducerAction.ProduceStream takes a function handling the incoming event and returning a corresponding stream as a Source wrapped in a Future

Client

After the definition of the pipeline, a client is easily created:

val client = Client(Source.single(ClientStage.HostUp(Host("localhost", port))), SimpleHandler, false, OverflowStrategy.backpressure, SimpleMessage.protocol)

The client takes a Source[HostEvent, Any]] as hosts parameter. Using this stream of either HostUp or HostDown events, the client updates its connection pool to a potentially changing set of endpoints.

The Client succeedingly takes the Resolver as parameter, a shouldReact parameter to configure the client if it should react to incoming events (for server to client communication), the to-be-used OverflowStrategy for incoming commands and the protocol BidiFlow to be used (BidiFlow[Cmd, ByteString, ByteString, Evt, Any])

The client has a set of configurable settings:

nl.gideondk.sentinel {
  client {
    host {
      max-connections = 32
      max-failures = 16
      failure-recovery-duration = 4 seconds
      auto-reconnect = true
      reconnect-duration = 2 seconds
    }
    input-buffer-size = 1024
  }
}

max-connections: defines the amount of sockets to be opened per connected host.

max-failures: defines the amount of (socket) failures a host may encounter before the host is removed from the connection pool.

failure-recovery-duration: period after which the failure rate is resetted per connection.

auto-reconnect: when set, HostDown events from the client (after disconnect) are refeeded back as HostUp events into the client for reconnection purposes.

reconnect-duration: the reconnection delay.

input-buffer-size: The input buffer size of the client (before the configured OverFlowStrategy is used.

Server

When the protocol and resolver are defined, creation of a server is very straight forward:

Server("localhost", port, SimpleServerHandler, SimpleMessage.protocol.reversed)

This will automatically start the server with the corresponding processor and handler, in the future, separate functionality for starting, restarting and stopping services will be available.

Client usage

Once a client and / or server has been set up, the ask method can be used on the client to send a command to the connected server. Results are wrapped into a Future containing the type Evt defined in the incoming stage of the client.

client.ask(SimpleCommand(PING_PONG, "PING"))`
res0: Future[SimpleMessageFormat]

The bare bone approach to sending / receiving messages is focussed on the idea that a higher-level API on top of Sentinel is responsible to make client usage more comfortable.

Streamed requests / responses

Sentinels structure for streaming requests and responses works best with protocols which somehow pad chunks and terminators. As the resolver has to be sure whether to consume a stream chunk and when to end the incoming stream, length based header structures are difficult to implement. Unstructured binary stream chunks can however be matched by protocol implementations if they are fundamentally different then other chunks, simply ignoring initial length headers and for instance breaking on zero terminators could be a way to implement non-padded stream chunks.

Sending

It's possible to stream content towards Sentinel clients by using the the ?<<- command, expecting the command to be send to the server, accompanied by the actual stream:

val stream = Source.single(SimpleCommand(TOTAL_CHUNK_SIZE, "")) ++ Source(List.fill(1024)(SimpleStreamChunk("A"))) ++ Source.single(SimpleStreamChunk(""))

client.sendStream(stream)
res0: Future[SimpleMessageFormat]

The content within the Source is sent over the TCP connection (returning in the Evt type, defined through the pipeline).

Receiving

In the same manner, a stream can be requested from the server:

client.askStream(SimpleCommand(GENERATE_NUMBERS, "1024"))
res0: Future[Source[SimpleMessageFormat, Any]]

Credits

The idea and internals for a large part of the client's connection pooling comes from Maciej Ciołeks his wonderful akka-http-lb library.

License

Copyright © 2017 Gideon de Kok

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Overview

Name With Ownergideondk/sentinel
Primary LanguageScala
Program languageScala (Language Count: 2)
Platform
License:Apache License 2.0
Release Count2
Last Release Name0.8-M1 (Posted on 2017-01-06 13:16:37)
First Release Name0.6.7 (Posted on 2014-05-13 09:16:42)
Created At2013-04-01 11:15:26
Pushed At2017-07-08 15:28:17
Last Commit At2017-07-08 17:28:17
Stargazers Count166
Watchers Count18
Fork Count12
Commits Count147
Has Issues Enabled
Issues Count0
Issue Open Count0
Pull Requests Count6
Pull Requests Open Count0
Pull Requests Close Count0
Has Wiki Enabled
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