Classic Cluster Usage

For the full documentation of this feature and for new projects see Cluster. For specific documentation topics see:

• Cluster Specification
• Cluster Membership Service
• When and where to use Akka Cluster
• Higher level Cluster tools
• Rolling Updates
• Operating, Managing, Observability

Module info

The Akka dependencies are available from Akka’s library repository. To access them there, you need to configure the URL for this repository.

sbt

resolvers += "Akka library repository".at("https://repo.akka.io/maven")

Maven

<project>
  ...
  <repositories>
    <repository>
      <id>akka-repository</id>
      <name>Akka library repository</name>
      <url>https://repo.akka.io/maven</url>
    </repository>
  </repositories>
</project>

Gradle

repositories {
    mavenCentral()
    maven {
        url "https://repo.akka.io/maven"
    }
}

To use Akka Cluster add the following dependency in your project:

sbt

val AkkaVersion = "2.9.1"
libraryDependencies += "com.typesafe.akka" %% "akka-cluster" % AkkaVersion

Maven

<properties>
  <scala.binary.version>2.13</scala.binary.version>
</properties>
<dependencyManagement>
  <dependencies>
    <dependency>
      <groupId>com.typesafe.akka</groupId>
      <artifactId>akka-bom_${scala.binary.version}</artifactId>
      <version>2.9.1</version>
      <type>pom</type>
      <scope>import</scope>
    </dependency>
  </dependencies>
</dependencyManagement>
<dependencies>
  <dependency>
    <groupId>com.typesafe.akka</groupId>
    <artifactId>akka-cluster_${scala.binary.version}</artifactId>
  </dependency>
</dependencies>

Gradle

def versions = [
  ScalaBinary: "2.13"
]
dependencies {
  implementation platform("com.typesafe.akka:akka-bom_${versions.ScalaBinary}:2.9.1")

  implementation "com.typesafe.akka:akka-cluster_${versions.ScalaBinary}"
}

When and where to use Akka Cluster

See Choosing Akka Cluster in the documentation of the new APIs.

Cluster API Extension

The following configuration enables the ClusterCluster extension to be used. It joins the cluster and an actor subscribes to cluster membership events and logs them.

An actor that uses the cluster extension may look like this:

Scala

copysource/*
 * Copyright (C) 2018-2023 Lightbend Inc. <https://www.lightbend.com>
 */

package scala.docs.cluster

import akka.cluster.Cluster
import akka.cluster.ClusterEvent._
import akka.actor.ActorLogging
import akka.actor.Actor

class SimpleClusterListener extends Actor with ActorLogging {

  val cluster = Cluster(context.system)

  // subscribe to cluster changes, re-subscribe when restart
  override def preStart(): Unit = {
    //#subscribe
    cluster.subscribe(self, initialStateMode = InitialStateAsEvents, classOf[MemberEvent], classOf[UnreachableMember])
    //#subscribe
  }
  override def postStop(): Unit = cluster.unsubscribe(self)

  def receive = {
    case MemberUp(member) =>
      log.info("Member is Up: {}", member.address)
    case UnreachableMember(member) =>
      log.info("Member detected as unreachable: {}", member)
    case MemberRemoved(member, previousStatus) =>
      log.info("Member is Removed: {} after {}", member.address, previousStatus)
    case _: MemberEvent => // ignore
  }
}

Java

copysource/*
 * Copyright (C) 2018-2023 Lightbend Inc. <https://www.lightbend.com>
 */

package jdocs.cluster;

import akka.actor.AbstractActor;
import akka.cluster.Cluster;
import akka.cluster.ClusterEvent;
import akka.cluster.ClusterEvent.MemberEvent;
import akka.cluster.ClusterEvent.MemberRemoved;
import akka.cluster.ClusterEvent.MemberUp;
import akka.cluster.ClusterEvent.UnreachableMember;
import akka.event.Logging;
import akka.event.LoggingAdapter;

public class SimpleClusterListener extends AbstractActor {
  LoggingAdapter log = Logging.getLogger(getContext().getSystem(), this);
  Cluster cluster = Cluster.get(getContext().getSystem());

  // subscribe to cluster changes
  @Override
  public void preStart() {
    // #subscribe
    cluster.subscribe(
        getSelf(), ClusterEvent.initialStateAsEvents(), MemberEvent.class, UnreachableMember.class);
    // #subscribe
  }

  // re-subscribe when restart
  @Override
  public void postStop() {
    cluster.unsubscribe(getSelf());
  }

  @Override
  public Receive createReceive() {
    return receiveBuilder()
        .match(
            MemberUp.class,
            mUp -> {
              log.info("Member is Up: {}", mUp.member());
            })
        .match(
            UnreachableMember.class,
            mUnreachable -> {
              log.info("Member detected as unreachable: {}", mUnreachable.member());
            })
        .match(
            MemberRemoved.class,
            mRemoved -> {
              log.info("Member is Removed: {}", mRemoved.member());
            })
        .match(
            MemberEvent.class,
            message -> {
              // ignore
            })
        .build();
  }
}

And the minimum configuration required is to set a host/port for remoting and the akka.actor.provider = "cluster".

copysourceakka {
  actor {
    provider = "cluster"
  }
  remote.artery {
    canonical {
      hostname = "127.0.0.1"
      port = 2551
    }
  }

  cluster {
    seed-nodes = [
      "akka://[email protected]:2551",
      "akka://[email protected]:2552"]
    
    downing-provider-class = "akka.cluster.sbr.SplitBrainResolverProvider"
  }
}

The actor registers itself as subscriber of certain cluster events. It receives events corresponding to the current state of the cluster when the subscription starts and then it receives events for changes that happen in the cluster.

Cluster Membership API

This section shows the basic usage of the membership API. For the in-depth descriptions on joining, joining to seed nodes, downing and leaving of any node in the cluster please see the full Cluster Membership API documentation.

Joining to Seed Nodes

The seed nodes are initial contact points for joining a cluster, which can be done in different ways:

• automatically with Cluster Bootstrap
• with configuration of seed-nodes
• programatically

After the joining process the seed nodes are not special and they participate in the cluster in exactly the same way as other nodes.

Joining programmatically to seed nodes

You may also join programmatically, which is attractive when dynamically discovering other nodes at startup by using some external tool or API.

Scala

copysourceimport akka.actor.Address
import akka.cluster.Cluster

val cluster = Cluster(system)
val list: List[Address] = ??? //your method to dynamically get seed nodes
cluster.joinSeedNodes(list)

Java

copysourceimport akka.actor.Address;
import akka.cluster.Cluster;

final Cluster cluster = Cluster.get(system);
List<Address> list =
    new LinkedList<>(); // replace this with your method to dynamically get seed nodes
cluster.joinSeedNodes(list);

For more information see tuning joins

It’s also possible to specifically join a single node as illustrated in below example, but joinSeedNodesjoinSeedNodes should be preferred since it has redundancy and retry mechanisms built-in.

Scala

copysourceval cluster = Cluster(context.system)
  cluster.join(cluster.selfAddress)

Java

copysourceCluster cluster = Cluster.get(getContext().getSystem());
  cluster.join(cluster.selfAddress());

Leaving

See Leaving in the documentation of the new APIs.

Downing

See Downing in the documentation of the new APIs.

Subscribe to Cluster Events

You can subscribe to change notifications of the cluster membership by using Cluster(system).subscribeCluster.get(system).subscribe.

Scala

copysourcecluster.subscribe(self, classOf[MemberEvent], classOf[UnreachableMember])

Java

copysourcecluster.subscribe(getSelf(), MemberEvent.class, UnreachableMember.class);

A snapshot of the full state, CurrentClusterStateCurrentClusterState, is sent to the subscriber as the first message, followed by events for incremental updates.

Note that you may receive an empty CurrentClusterState, containing no members, followed by MemberUpMemberUp events from other nodes which already joined, if you start the subscription before the initial join procedure has completed. This may for example happen when you start the subscription immediately after cluster.join()cluster.join() like below. This is expected behavior. When the node has been accepted in the cluster you will receive MemberUp for that node, and other nodes.

Scala

copysourceval cluster = Cluster(context.system)
  cluster.join(cluster.selfAddress)
cluster.subscribe(self, classOf[MemberEvent], classOf[UnreachableMember])

Java

copysourceCluster cluster = Cluster.get(getContext().getSystem());
  cluster.join(cluster.selfAddress());
cluster.subscribe(getSelf(), MemberEvent.class, UnreachableMember.class);

To avoid receiving an empty CurrentClusterState at the beginning, you can use it like shown in the following example, to defer subscription until the MemberUp event for the own node is received:

Scala

copysourceval cluster = Cluster(context.system)
  cluster.join(cluster.selfAddress)
cluster.registerOnMemberUp {
  cluster.subscribe(self, classOf[MemberEvent], classOf[UnreachableMember])
}

Java

copysourceCluster cluster = Cluster.get(getContext().getSystem());
  cluster.join(cluster.selfAddress());
cluster.registerOnMemberUp(
    () -> cluster.subscribe(getSelf(), MemberEvent.class, UnreachableMember.class));

If you find it inconvenient to handle the CurrentClusterState you can use ClusterEvent.InitialStateAsEvents ClusterEvent.initialStateAsEvents() as parameter to subscribesubscribe. That means that instead of receiving CurrentClusterState as the first message you will receive the events corresponding to the current state to mimic what you would have seen if you were listening to the events when they occurred in the past. Note that those initial events only correspond to the current state and it is not the full history of all changes that actually has occurred in the cluster.

Scala

copysourcecluster.subscribe(self, initialStateMode = InitialStateAsEvents, classOf[MemberEvent], classOf[UnreachableMember])

Java

copysourcecluster.subscribe(
    getSelf(), ClusterEvent.initialStateAsEvents(), MemberEvent.class, UnreachableMember.class);

Worker Dial-in Example

Let’s take a look at an example that illustrates how workers, here named backend, can detect and register to new master nodes, here named frontend.

The example application provides a service to transform text. When some text is sent to one of the frontend services, it will be delegated to one of the backend workers, which performs the transformation job, and sends the result back to the original client. New backend nodes, as well as new frontend nodes, can be added or removed to the cluster dynamically.

Messages:

Scala

copysourcefinal case class TransformationJob(text: String)
final case class TransformationResult(text: String)
final case class JobFailed(reason: String, job: TransformationJob)
case object BackendRegistration

Java

copysourcepublic interface TransformationMessages {

  public static class TransformationJob implements Serializable {
    private final String text;

    public TransformationJob(String text) {
      this.text = text;
    }

    public String getText() {
      return text;
    }
  }

  public static class TransformationResult implements Serializable {
    private final String text;

    public TransformationResult(String text) {
      this.text = text;
    }

    public String getText() {
      return text;
    }

    @Override
    public String toString() {
      return "TransformationResult(" + text + ")";
    }
  }

  public static class JobFailed implements Serializable {
    private final String reason;
    private final TransformationJob job;

    public JobFailed(String reason, TransformationJob job) {
      this.reason = reason;
      this.job = job;
    }

    public String getReason() {
      return reason;
    }

    public TransformationJob getJob() {
      return job;
    }

    @Override
    public String toString() {
      return "JobFailed(" + reason + ")";
    }
  }

  public static final String BACKEND_REGISTRATION = "BackendRegistration";
}

The backend worker that performs the transformation job:

Scala

copysourceclass TransformationBackend extends Actor {

  val cluster = Cluster(context.system)

  // subscribe to cluster changes, MemberUp
  // re-subscribe when restart
  override def preStart(): Unit = cluster.subscribe(self, classOf[MemberUp])
  override def postStop(): Unit = cluster.unsubscribe(self)

  def receive = {
    case TransformationJob(text) => sender() ! TransformationResult(text.toUpperCase)
    case state: CurrentClusterState =>
      state.members.filter(_.status == MemberStatus.Up).foreach(register)
    case MemberUp(m) => register(m)
  }

  def register(member: Member): Unit =
    if (member.hasRole("frontend"))
      context.actorSelection(RootActorPath(member.address) / "user" / "frontend") !
      BackendRegistration
}

Java

copysourcepublic class TransformationBackend extends AbstractActor {

  Cluster cluster = Cluster.get(getContext().getSystem());

  // subscribe to cluster changes, MemberUp
  @Override
  public void preStart() {
    cluster.subscribe(getSelf(), MemberUp.class);
  }

  // re-subscribe when restart
  @Override
  public void postStop() {
    cluster.unsubscribe(getSelf());
  }

  @Override
  public Receive createReceive() {
    return receiveBuilder()
        .match(
            TransformationJob.class,
            job -> {
              getSender().tell(new TransformationResult(job.getText().toUpperCase()), getSelf());
            })
        .match(
            CurrentClusterState.class,
            state -> {
              for (Member member : state.getMembers()) {
                if (member.status().equals(MemberStatus.up())) {
                  register(member);
                }
              }
            })
        .match(
            MemberUp.class,
            mUp -> {
              register(mUp.member());
            })
        .build();
  }

  void register(Member member) {
    if (member.hasRole("frontend"))
      getContext()
          .actorSelection(member.address() + "/user/frontend")
          .tell(BACKEND_REGISTRATION, getSelf());
  }
}

Note that the TransformationBackend actor subscribes to cluster events to detect new, potential, frontend nodes, and send them a registration message so that they know that they can use the backend worker.

The frontend that receives user jobs and delegates to one of the registered backend workers:

Scala

copysourceclass TransformationFrontend extends Actor {

  var backends = IndexedSeq.empty[ActorRef]
  var jobCounter = 0

  def receive = {
    case job: TransformationJob if backends.isEmpty =>
      sender() ! JobFailed("Service unavailable, try again later", job)

    case job: TransformationJob =>
      jobCounter += 1
      backends(jobCounter % backends.size).forward(job)

    case BackendRegistration if !backends.contains(sender()) =>
      context.watch(sender())
      backends = backends :+ sender()

    case Terminated(a) =>
      backends = backends.filterNot(_ == a)
  }
}

Java

copysourcepublic class TransformationFrontend extends AbstractActor {

  List<ActorRef> backends = new ArrayList<ActorRef>();
  int jobCounter = 0;

  @Override
  public Receive createReceive() {
    return receiveBuilder()
        .match(
            TransformationJob.class,
            job -> backends.isEmpty(),
            job -> {
              getSender()
                  .tell(new JobFailed("Service unavailable, try again later", job), getSender());
            })
        .match(
            TransformationJob.class,
            job -> {
              jobCounter++;
              backends.get(jobCounter % backends.size()).forward(job, getContext());
            })
        .matchEquals(
            BACKEND_REGISTRATION,
            x -> {
              getContext().watch(getSender());
              backends.add(getSender());
            })
        .match(
            Terminated.class,
            terminated -> {
              backends.remove(terminated.getActor());
            })
        .build();
  }
}

Note that the TransformationFrontend actor watch the registered backend to be able to remove it from its list of available backend workers. Death watch uses the cluster failure detector for nodes in the cluster, i.e. it detects network failures and JVM crashes, in addition to graceful termination of watched actor. Death watch generates the TerminatedTerminated message to the watching actor when the unreachable cluster node has been downed and removed.

Node Roles

See Cluster Node Roles in the documentation of the new APIs.

How To Startup when Cluster Size Reached

See How to startup when a minimum number of members in the cluster is reached in the documentation of the new APIs.

How To Startup when Member is Up

A common use case is to start actors after the cluster has been initialized, members have joined, and the cluster has reached a certain size.

With a configuration option you can define required number of members before the leader changes member status of ‘Joining’ members to ‘Up’.:

akka.cluster.min-nr-of-members = 3

In a similar way you can define required number of members of a certain role before the leader changes member status of ‘Joining’ members to ‘Up’.:

akka.cluster.role {
  frontend.min-nr-of-members = 1
  backend.min-nr-of-members = 2
}

You can start actors or trigger any functions using the registerOnMemberUpregisterOnMemberUp callback, which will be invoked when the current member status is changed to ‘Up’. This can additionally be used with akka.cluster.min-nr-of-members optional configuration to defer an action until the cluster has reached a certain size.

Scala

copysourceCluster(system).registerOnMemberUp {
  system.actorOf(Props(classOf[FactorialFrontend], upToN, true), name = "factorialFrontend")
}

Java

copysourceCluster.get(system)
    .registerOnMemberUp(
        new Runnable() {
          @Override
          public void run() {
            system.actorOf(
                Props.create(FactorialFrontend.class, upToN, true), "factorialFrontend");
          }
        });

How To Cleanup when Member is Removed

You can do some clean up in a registerOnMemberRemovedregisterOnMemberRemoved callback, which will be invoked when the current member status is changed to ‘Removed’ or the cluster have been shutdown.

An alternative is to register tasks to the Coordinated Shutdown.

Higher level Cluster tools

Cluster Singleton

For some use cases it is convenient or necessary to ensure only one actor of a certain type is running somewhere in the cluster. This can be implemented by subscribing to member events, but there are several corner cases to consider. Therefore, this specific use case is covered by the Cluster Singleton.

See Cluster Singleton.

Cluster Sharding

Distributes actors across several nodes in the cluster and supports interaction with the actors using their logical identifier, but without having to care about their physical location in the cluster.

See Cluster Sharding.

Distributed Data

Distributed Data is useful when you need to share data between nodes in an Akka Cluster. The data is accessed with an actor providing a key-value store like API.

See Distributed Data.

Distributed Publish Subscribe

Publish-subscribe messaging between actors in the cluster based on a topic, i.e. the sender does not have to know on which node the destination actor is running.

See Cluster Distributed Publish Subscribe.

Cluster Aware Routers

All routers can be made aware of member nodes in the cluster, i.e. deploying new routees or looking up routees on nodes in the cluster. When a node becomes unreachable or leaves the cluster the routees of that node are automatically unregistered from the router. When new nodes join the cluster, additional routees are added to the router, according to the configuration.

See Cluster Aware Routers and Routers.

Cluster across multiple data centers

Akka Cluster can be used across multiple data centers, availability zones or regions, so that one Cluster can span multiple data centers and still be tolerant to network partitions.

See Cluster Multi-DC.

Cluster Metrics

The member nodes of the cluster can collect system health metrics and publish that to other cluster nodes and to the registered subscribers on the system event bus.

See Cluster Metrics.

Failure Detector

The nodes in the cluster monitor each other by sending heartbeats to detect if a node is unreachable from the rest of the cluster. Please see:

• Failure Detector specification
• Phi Accrual Failure Detector implementation
• Using the Failure Detector

How to Test

copysourceimport akka.remote.testkit.MultiNodeConfig
import com.typesafe.config.ConfigFactory

object StatsSampleSpecConfig extends MultiNodeConfig {
  // register the named roles (nodes) of the test
  val first = role("first")
  val second = role("second")
  val third = role("third")

  def nodeList = Seq(first, second, third)

  // Extract individual sigar library for every node.
  nodeList.foreach { role =>
    nodeConfig(role) {
      ConfigFactory.parseString(s"""
      # Enable metrics extension in akka-cluster-metrics.
      akka.extensions=["akka.cluster.metrics.ClusterMetricsExtension"]
      # Sigar native library extract location during tests.
      akka.cluster.metrics.native-library-extract-folder=target/native/${role.name}
      """)
    }
  }

  // this configuration will be used for all nodes
  // note that no fixed host names and ports are used
  commonConfig(ConfigFactory.parseString("""
    akka.actor.provider = cluster
    akka.cluster.roles = [compute]
    akka.actor.deployment {
      /statsService/workerRouter {
          router = consistent-hashing-group
          routees.paths = ["/user/statsWorker"]
          cluster {
            enabled = on
            allow-local-routees = on
            use-roles = ["compute"]
          }
        }
    }
    """))

}

copysource// need one concrete test class per node
class StatsSampleSpecMultiJvmNode1 extends StatsSampleSpec
class StatsSampleSpecMultiJvmNode2 extends StatsSampleSpec
class StatsSampleSpecMultiJvmNode3 extends StatsSampleSpec

copysourceimport akka.remote.testkit.MultiNodeSpec
import akka.testkit.ImplicitSender
import org.scalatest.BeforeAndAfterAll
import org.scalatest.matchers.should.Matchers
import org.scalatest.wordspec.AnyWordSpecLike

abstract class StatsSampleSpec
    extends MultiNodeSpec(StatsSampleSpecConfig)
    with AnyWordSpecLike
    with Matchers
    with BeforeAndAfterAll
    with ImplicitSender {

  import StatsSampleSpecConfig._

  override def initialParticipants = roles.size

  override def beforeAll() = multiNodeSpecBeforeAll()

  override def afterAll() = multiNodeSpecAfterAll()

copysource"illustrate how to startup cluster" in within(15 seconds) {
  Cluster(system).subscribe(testActor, classOf[MemberUp])
  expectMsgClass(classOf[CurrentClusterState])

  val firstAddress = node(first).address
  val secondAddress = node(second).address
  val thirdAddress = node(third).address

  Cluster(system).join(firstAddress)

  system.actorOf(Props[StatsWorker](), "statsWorker")
  system.actorOf(Props[StatsService](), "statsService")

  receiveN(3).collect { case MemberUp(m) => m.address }.toSet should be(
    Set(firstAddress, secondAddress, thirdAddress))

  Cluster(system).unsubscribe(testActor)

  testConductor.enter("all-up")
}

copysourceCluster(system).join(firstAddress)

copysource"show usage of the statsService from one node" in within(15 seconds) {
  runOn(second) {
    assertServiceOk()
  }

  testConductor.enter("done-2")
}

def assertServiceOk(): Unit = {
  val service = system.actorSelection(node(third) / "user" / "statsService")
  // eventually the service should be ok,
  // first attempts might fail because worker actors not started yet
  awaitAssert {
    service ! StatsJob("this is the text that will be analyzed")
    expectMsgType[StatsResult](1.second).meanWordLength should be(3.875 +- 0.001)
  }

}

copysourceval firstAddress = node(first).address
val secondAddress = node(second).address
val thirdAddress = node(third).address

Management

There are several management tools for the cluster. Please refer to the Cluster Management for more information.

Command Line

The cluster can be managed with the script akka-cluster provided in the Akka GitHub repository here. Place the script and the jmxsh-R5.jar library in the same directory.

Run it without parameters to see instructions about how to use the script:

Usage: ./akka-cluster <node-hostname> <jmx-port> <command> ...

Supported commands are:
           join <node-url> - Sends request a JOIN node with the specified URL
          leave <node-url> - Sends a request for node with URL to LEAVE the cluster
           down <node-url> - Sends a request for marking node with URL as DOWN
             member-status - Asks the member node for its current status
                   members - Asks the cluster for addresses of current members
               unreachable - Asks the cluster for addresses of unreachable members
            cluster-status - Asks the cluster for its current status (member ring,
                             unavailable nodes, meta data etc.)
                    leader - Asks the cluster who the current leader is
              is-singleton - Checks if the cluster is a singleton cluster (single
                             node cluster)
              is-available - Checks if the member node is available
Where the <node-url> should be on the format of
  'akka.<protocol>://<actor-system-name>@<hostname>:<port>'

Examples: ./akka-cluster localhost 9999 is-available
          ./akka-cluster localhost 9999 join akka://MySystem@darkstar:2552
          ./akka-cluster localhost 9999 cluster-status

To be able to use the script you must enable remote monitoring and management when starting the JVMs of the cluster nodes, as described in Monitoring and Management Using JMX Technology. Make sure you understand the security implications of enabling remote monitoring and management.

Configuration

There are several configuration properties for the cluster, and the full reference configuration for complete information.