A Scala & Akka-Cluster based PnP leader election library for use in AWS
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README.md

aws-leader-election

A Scala & Akka-Cluster based PnP leader election library for use in AWS, built on Akka & using the akka-cluster cluster singleton to perform leader elected tasks.

Designed for use in a distributed Play application, deployed in an auto-scaling cluster in Amazon EC2 (in a single region only). Uses AWS's auto-scaling java client to discover EC2 instances and creates an akka-cluster from the auto-scaling group members.

Settings

Settings read from application.conf at the root of the classpath, or as JVM run parameters.

  • akka.port - The port to look for akka-cluster instances on.
  • aws.leader.local - true to run locally and bypass AWS discovery.
  • aws.credentials - access-key & secret-key to pass to the AWS client for EC2 instance discovery

Maven Central Dependency

"com.teambytes" %% "aws-leader-election" % "1.0.0"

Example Usage (Play Application)

Global.scala

import com.teambytes.awsleader.AwsLeaderElection

object Global extends play.api.GlobalSettings {

  implicit val ec = play.api.libs.concurrent.Execution.defaultContext

  override def onStart(app: play.api.Application) = {
    AwsLeaderElection.startLeaderElection(new TestLeaderElectionHandler(), app.configuration.underlying)
  }

}

TestLeaderElectionHandler.scala

import java.util.concurrent.{Executors, SchedulingLeaderActionsHandler}

import com.teambytes.awsleader.{PeriodicTask, SchedulingInflatableLeader}
import play.core.NamedThreadFactory

class TestLeaderElectionHandler extends SchedulingLeaderActionsHandler {

  val tasks = Set(new TestPeriodicJob())

  override def leaderExecutor: ScheduledExecutorService = Executors.newScheduledThreadPool(1, new NamedThreadFactory("test-job"))

  override def leaderTasks: Iterable[PeriodicTask] = tasks
}

TestPeriodicJob.scala

import com.teambytes.awsleader.PeriodicTask
import play.api.Logger

class TestPeriodicJob extends PeriodicTask {

  import scala.concurrent.duration._

  override def periodMs: Long = 5.seconds.toMillis

  override def run(): Unit = {
    Logger.info(
      """
        |
        |
        |
        |
        |Running test periodic job here and now!!!!!!!
        |
        |
        |
        |
      """.stripMargin)
  }
}

Potential problems to be aware of

This library uses the Akka cluster singleton pattern, which has several drawbacks, some of them are listed below:

  • the cluster singleton may quickly become a performance bottleneck,
  • you can not rely on the cluster singleton to be non-stop available - e.g. when node on which the singleton was running dies, it will take a few seconds for this to be noticed and the singleton be migrated to another node,
  • in the case of a network partition appearing in a Cluster that is using Automatic Downing (Automatic vs. Manual Downing), it may happen that the isolated clusters each decide to spin up their own singleton, meaning that there might be multiple singletons running in the system, yet the Clusters have no way of finding out about them (because of the network partition).

Especially the last point is something you should be aware of - in general when using the Cluster Singleton pattern you should take care of downing nodes yourself and not rely on the timing based auto-down feature.

Running Locally

When running locally, make sure to provide -Daws.leader.local=true

License

Apache 2.0

Links & kudos