Migration Guide 2.5.x to 2.6.x

Akka 2.6.x is binary backwards compatible with 2.5.x with the ordinary exceptions listed in the Binary Compatibility Rules.

This means that updating an application from Akka 2.5.x to 2.6.x should be a smooth process, and that libraries built for Akka 2.5.x can also be used with Akka 2.6.x. For example Akka HTTP 10.1.10 and Akka Management 1.0.3 can be used with Akka 2.6.0 dependencies. You may have to add explicit dependencies to the new Akka version in your build.

That said, there are some changes to configuration and behavior that should be considered, so reading this migration guide and testing your application thoroughly is recommended.

Rolling updates are possible without shutting down all nodes of the Akka Cluster, but will require configuration adjustments as described in the Remoting section of this migration guide.

Scala 2.11 no longer supported

If you are still using Scala 2.11 then you must upgrade to 2.12 or 2.13

Auto-downing removed

Auto-downing of unreachable Cluster members have been removed after warnings and recommendations against using it for many years. It was by default disabled, but could be enabled with configuration akka.cluster.auto-down-unreachable-after.

For alternatives see the documentation about Downing.

Auto-downing was a naïve approach to remove unreachable nodes from the cluster membership. In a production environment it will eventually break down the cluster. When a network partition occurs, both sides of the partition will see the other side as unreachable and remove it from the cluster. This results in the formation of two separate, disconnected, clusters (known as Split Brain).

This behavior is not limited to network partitions. It can also occur if a node in the cluster is overloaded, or experiences a long GC pause.

When using Cluster Singleton or Cluster Sharding it can break the contract provided by those features. Both provide a guarantee that an actor will be unique in a cluster. With the auto-down feature enabled, it is possible for multiple independent clusters to form (*Split Brain*). When this happens the guaranteed uniqueness will no longer be true resulting in undesirable behavior in the system.

This is even more severe when Akka Persistence is used in conjunction with Cluster Sharding. In this case, the lack of unique actors can cause multiple actors to write to the same journal. Akka Persistence operates on a single writer principle. Having multiple writers will corrupt the journal and make it unusable.

Finally, even if you don’t use features such as Persistence, Sharding, or Singletons, auto-downing can lead the system to form multiple small clusters. These small clusters will be independent from each other. They will be unable to communicate and as a result you may experience performance degradation. Once this condition occurs, it will require manual intervention in order to reform the cluster.

Because of these issues, auto-downing should never be used in a production environment.

Removed features that were deprecated

After being deprecated since 2.5.0, the following have been removed in Akka 2.6.0.

  • akka-camel module
    • As an alternative we recommend Alpakka.
    • This is of course not a drop-in replacement. If there is community interest we are open to setting up akka-camel as a separate community-maintained repository.
  • akka-agent module
    • If there is interest it may be moved to a separate, community-maintained repository.
  • akka-contrib module
    • To migrate, take the components you are using from Akka 2.5 and include them in your own project or library under your own package name.
  • Actor DSL
    • Actor DSL is a rarely used feature. Use plain system.actorOf instead of the DSL to create Actors if you have been using it.
  • akka.stream.extra.Timing operator
  • Netty UDP (Classic remoting over UDP)
    • To continue to use UDP configure Artery UDP or migrate to Artery TCP.
    • A full cluster restart is required to change to Artery.
  • UntypedActor
    • Use AbstractActor instead.
  • JavaTestKit
    • Use akka.testkit.javadsl.TestKit instead.
  • UntypedPersistentActor
    • Use AbstractPersistentActor instead.
  • UntypedPersistentActorWithAtLeastOnceDelivery
  • akka.stream.actor.ActorSubscriber and akka.stream.actor.ActorPublisher
    • Use GraphStage instead.

After being deprecated since 2.4.0, the following have been removed in Akka 2.6.0.

  • Secure cookie in Classic Akka Remoting

After being deprecated since 2.2, the following have been removed in Akka 2.6.0.

  • actorFor
    • Use ActorSelection instead.

Removed methods

  • Logging.getLogger(UntypedActor) UntypedActor has been removed, use AbstractActor instead.
  • LoggingReceive.create(Receive, ActorContext) use AbstractActor.Receive instead.
  • ActorMaterialzierSettings.withAutoFusing disabling fusing is no longer possible.
  • AbstractActor.getChild use findChild instead.
  • Actor.getRef use Actor.getActorRef instead.
  • CircuitBreaker.onOpen use CircuitBreaker.addOnOpenListener
  • CircuitBreaker.onHalfOpen use CircuitBreaker.addOnHalfOpenListener
  • CircuitBreaker.onClose use CircuitBreaker.addOnCloseListener
  • Source.actorSubscriber, use Source.fromGraph instead.
  • Source.actorActorPublisher, use Source.fromGraph instead.

Deprecated features

PersistentFSM

Migration guide to Persistence Typed is in the PersistentFSM documentation.

TypedActor

akka.actor.TypedActor has been deprecated as of 2.6.0 in favor of the akka.actor.typed API which should be used instead.

There are several reasons for phasing out the old TypedActor. The primary reason is they use transparent remoting which is not our recommended way of implementing and interacting with actors. Transparent remoting is when you try to make remote method invocations look like local calls. In contrast we believe in location transparency with explicit messaging between actors (same type of messaging for both local and remote actors). They also have limited functionality compared to ordinary actors, and worse performance.

To summarize the fallacy of transparent remoting: * Was used in CORBA, RMI, and DCOM, and all of them failed. Those problems were noted by Waldo et al already in 1994 * Partial failure is a major problem. Remote calls introduce uncertainty whether the function was invoked or not. Typically handled by using timeouts but the client can’t always know the result of the call. * Latency of calls over a network are several order of magnitudes longer than latency of local calls, which can be more than surprising if encoded as an innocent looking local method call. * Remote invocations have much lower throughput due to the need of serializing the data and you can’t just pass huge datasets in the same way.

Therefore explicit message passing is preferred. It looks different from local method calls (actorRef ! messageactorRef.tell(message)) and there is no misconception that sending a message will result in it being processed instantaneously. The goal of location transparency is to unify message passing for both local and remote interactions, versus attempting to make remote interactions look like local method calls.

Warnings about TypedActor have been mentioned in documentation for many years.

Cluster Client

Cluster client has been deprecated as of 2.6.0 in favor of Akka gRPC. It is not advised to build new applications with Cluster client, and existing users should migrate to Akka gRPC.

akka-protobuf

akka-protobuf was never intended to be used by end users but perhaps this was not well-documented. Applications should use standard Protobuf dependency instead of akka-protobuf. The artifact is still published, but the transitive dependency to akka-protobuf has been removed.

Akka is now using Protobuf version 3.9.0 for serialization of messages defined by Akka.

ByteString.empty

It is now recommended to use ByteStringByteString.emptyByteString() instead of ByteStringByteString.empty() when using Java because ByteStringByteString.empty() is no longer available as a static method in the artifacts built for Scala 2.13.

AkkaSslConfig

AkkaSslConfig has been deprecated in favor of setting up TLS with javax.net.ssl.SSLEngine directly.

This also means that methods Akka Streams TLS and Tcp that take SSLContext or AkkaSslConfig have been deprecated and replaced with corresponding methods that takes a factory function for creating the SSLEngine.

See documentation of streaming IO with TLS.

JavaLogger

akka.event.jul.JavaLogger for integration with java.util.logging has been deprecated. Use SLF4J instead, which also has support for java.util.logging.

akka.Main

akka.Main is deprecated in favour of starting the ActorSystem from a custom main class instead. akka.Main was not adding much value and typically a custom main class is needed anyway.

Pluggable DNS

Plugging in your own DNS implementation is now deprecated and will be removed in 2.7.0, it was originally added to support a third party DNS provided that supported SRV records. The built in async-dns now supports SRV records.

The resolve and cached methods on the DNS extension have also been deprecated in favour of ones that take in DnsProtocol.Resolve. These methods return a new types that include SRV records.

Remoting

Default remoting is now Artery TCP

Artery TCP is now the default remoting implementation. Classic remoting has been deprecated and will be removed in 2.7.0.

Migrating from classic remoting to Artery

Artery has the same functionality as classic remoting and you should normally only have to change the configuration to switch.

To switch a full cluster restart is required and any overrides for classic remoting need to be ported to Artery configuration. Artery has a completely different protocol, which means that a rolling update is not supported.

Artery defaults to TCP (see selected transport) which is a good start when migrating from classic remoting.

The protocol part in the Akka Address, for example "akka.tcp://[email protected]:2552/user/actorName" has changed from akka.tcp to akka. If you have configured or hardcoded any such addresses you have to change them to "akka://[email protected]:25520/user/actorName". akka is used also when TLS is enabled. One typical place where such address is used is in the seed-nodes configuration.

The default port is 25520 instead of 2552 to avoid connections between Artery and classic remoting due to misconfiguration. You can run Artery on 2552 if you prefer that (e.g. existing firewall rules) and then you have to configure the port with:

akka.remote.artery.canonical.port = 2552

The configuration for Artery is different, so you might have to revisit any custom configuration. See the full reference configuration for Artery and reference configuration for classic remoting.

Configuration that is likely required to be ported:

  • akka.remote.netty.tcp.hostname => akka.remote.artery.canonical.hostname
  • akka.remote.netty.tcp.port=> akka.remote.artery.canonical.port

If using SSL then tcp-tls needs to be enabled and setup. See Artery docs for SSL for how to do this.

The following events that are published to the eventStream have changed:

  • classic akka.remote.QuarantinedEvent is akka.remote.artery.QuarantinedEvent in Artery
  • classic akka.remote.GracefulShutdownQuarantinedEvent is akka.remote.artery.GracefulShutdownQuarantinedEvent in Artery
  • classic akka.remote.ThisActorSystemQuarantinedEvent is akka.remote.artery.ThisActorSystemQuarantinedEvent in Artery

Migration from 2.5.x Artery to 2.6.x Artery

The following defaults have changed:

  • akka.remote.artery.transport default has changed from aeron-udp to tcp

The following properties have moved. If you don’t adjust these from their defaults no changes are required:

For Aeron-UDP:

  • akka.remote.artery.log-aeron-counters to akka.remote.artery.advanced.aeron.log-aeron-counters
  • akka.remote.artery.advanced.embedded-media-driver to akka.remote.artery.advanced.aeron.embedded-media-driver
  • akka.remote.artery.advanced.aeron-dir to akka.remote.artery.advanced.aeron.aeron-dir
  • akka.remote.artery.advanced.delete-aeron-dir to akka.remote.artery.advanced.aeron.aeron-delete-dir
  • akka.remote.artery.advanced.idle-cpu-level to akka.remote.artery.advanced.aeron.idle-cpu-level
  • akka.remote.artery.advanced.give-up-message-after to akka.remote.artery.advanced.aeron.give-up-message-after
  • akka.remote.artery.advanced.client-liveness-timeout to akka.remote.artery.advanced.aeron.client-liveness-timeout
  • akka.remote.artery.advanced.image-liveless-timeout to akka.remote.artery.advanced.aeron.image-liveness-timeout
  • akka.remote.artery.advanced.driver-timeout to akka.remote.artery.advanced.aeron.driver-timeout

For TCP:

  • akka.remote.artery.advanced.connection-timeout to akka.remote.artery.advanced.tcp.connection-timeout

Remaining with Classic remoting (not recommended)

Classic remoting is deprecated but can be used in 2.6.x Rolling update from Classic remoting to Artery is not supported so if you want to update from Akka 2.5.x with Classic remoting to Akka 2.6.x without a full shut down of the Cluster you have to enable Classic remoting. Later, you can plan for a full shutdown and migrate from classic remoting to Artery as a separate step.

Explicitly disable Artery by setting property akka.remote.artery.enabled to false. Further, any configuration under akka.remote that is specific to classic remoting needs to be moved to akka.remote.classic. To see which configuration options are specific to classic search for them in: akka-remote/reference.conf.

Persistent mode for Cluster Sharding

Cluster Sharding coordinator and Remembering Entities state could previously be stored in Distributed Data or via Akka Persistence. The Persistence mode has been deprecated in favour of using the Distributed Data mode for the coordinator state. A replacement for the state for Remembered Entities is tracked in issue 27763.

Java Serialization

Java serialization is known to be slow and prone to attacks of various kinds - it never was designed for high throughput messaging after all. One may think that network bandwidth and latency limit the performance of remote messaging, but serialization is a more typical bottleneck.

From Akka 2.6.0 the Akka serialization with Java serialization is disabled by default and Akka itself doesn’t use Java serialization for any of its internal messages.

You have to enable serialization to send messages between ActorSystems (nodes) in the Cluster. Serialization with Jackson is a good choice in many cases, and our recommendation if you don’t have other preferences or constraints.

For compatibility with older systems that rely on Java serialization it can be enabled with the following configuration:

akka.actor.allow-java-serialization = on

Akka will still log warning when Java serialization is used and to silent that you may add:

akka.actor.warn-about-java-serializer-usage = off

Rolling update

Please see the rolling update procedure from Java serialization to Jackson.

Java serialization in consistent hashing

When using a consistent hashing router keys that were not bytes or a String are serialized. You might have to add a serializer for you hash keys, unless one of the default serializer are not handling that type and it was previously “accidentally” serialized with Java serialization.

Configuration and behavior changes

The following documents configuration changes and behavior changes where no action is required. In some cases the old behavior can be restored via configuration.

Remoting dependencies have been made optional

Classic remoting depends on Netty and Artery UDP depends on Aeron. These are now both optional dependencies that need to be explicitly added. See classic remoting or artery remoting for instructions.

Remote watch and deployment have been disabled without Cluster use

By default, these remoting features are disabled when not using Akka Cluster:

  • Remote Deployment: falls back to creating a local actor
  • Remote Watch: ignores the watch and unwatch request, and Terminated will not be delivered when the remote actor is stopped or if a remote node crashes

Watching an actor on a node outside the cluster may have unexpected consequences, such as quarantining so it has been disabled by default in Akka 2.6.x This is the case if either cluster is not used at all (only plain remoting) or when watching an actor outside of the cluster.

On the other hand, failure detection between nodes of the same cluster do not have that shortcoming. Thus, when remote watching or deployment is used within the same cluster, they are working the same in 2.6.x as before, except that a remote watch attempt before a node has joined will log a warning and be ignored, it must be done after the node has joined.

To optionally enable a watch without Akka Cluster or across a Cluster boundary between Cluster and non Cluster, knowing the consequences, all watchers (cluster as well as remote) need to set:

akka.remote.use-unsafe-remote-features-outside-cluster = on`.

When enabled

  • An initial warning is logged on startup of RemoteActorRefProvider
  • A warning will be logged on remote watch attempts, which you can suppress by setting

    akka.remote.warn-unsafe-watch-outside-cluster = off
    

Schedule periodically with fixed-delay vs. fixed-rate

The Scheduler.schedule method has been deprecated in favor of selecting scheduleWithFixedDelay or scheduleAtFixedRate.

The Scheduler documentation describes the difference between fixed-delay and fixed-rate scheduling. If you are uncertain of which one to use you should pick startTimerWithFixedDelay.

The deprecated schedule method had the same semantics as scheduleAtFixedRate, but since that can result in bursts of scheduled tasks or messages after long garbage collection pauses and in worst case cause undesired load on the system scheduleWithFixedDelay is often preferred.

For the same reason the following methods have also been deprecated:

  • TimerScheduler.startPeriodicTimer, replaced by startTimerWithFixedDelay or startTimerAtFixedRate
  • FSM.setTimer, replaced by startSingleTimer, startTimerWithFixedDelay or startTimerAtFixedRate
  • PersistentFSM.setTimer, replaced by startSingleTimer, startTimerWithFixedDelay or startTimerAtFixedRate

Internal dispatcher introduced

To protect the Akka internals against starvation when user code blocks the default dispatcher (for example by accidental use of blocking APIs from actors) a new internal dispatcher has been added. All of Akka’s internal, non-blocking actors now run on the internal dispatcher by default.

The dispatcher can be configured through akka.actor.internal-dispatcher.

For maximum performance, you might want to use a single shared dispatcher for all non-blocking, asynchronous actors, user actors and Akka internal actors. In that case, can configure the akka.actor.internal-dispatcher with a string value of akka.actor.default-dispatcher. This reinstantiates the behavior from previous Akka versions but also removes the isolation between user and Akka internals. So, use at your own risk!

Several use-dispatcher configuration settings that previously accepted an empty value to fall back to the default dispatcher has now gotten an explicit value of akka.actor.internal-dispatcher and no longer accept an empty string as value. If such an empty value is used in your application.conf the same result is achieved by simply removing that entry completely and having the default apply.

For more details about configuring dispatchers, see the Dispatchers

Default dispatcher size

Previously the factor for the default dispatcher was set a bit high (3.0) to give some extra threads in case of accidental blocking and protect a bit against starving the internal actors. Since the internal actors are now on a separate dispatcher the default dispatcher has been adjusted down to 1.0 which means the number of threads will be one per core, but at least 8 and at most 64. This can be tuned using the individual settings in akka.actor.default-dispatcher.fork-join-executor.

Mixed version

Startup will fail if mixed versions of a product family (such as Akka) are accidentally used. This was previously only logged as a warning. There is no guarantee mixed modules will work and it’s better to fail early than that the application is crashing at a later time than startup.

Cluster Sharding

waiting-for-state-timeout reduced to 2s

This has been reduced to speed up ShardCoordinator initialization in smaller clusters. The read from ddata is a ReadMajority. For small clusters (< majority-min-cap) every node needs to respond so it is more likely to timeout if there are nodes restarting, for example when there is a rolling re-deploy happening.

Passivate idle entity

The configuration akka.cluster.sharding.passivate-idle-entity-after is now enabled by default. Sharding will passivate entities when they have not received any messages after this duration. To disable passivation you can use configuration:

akka.cluster.sharding.passivate-idle-entity-after = off

It is always disabled if Remembering Entities is enabled.

Cluster Sharding stats

A new field has been added to the response of a ShardRegion.GetClusterShardingStats command for any shards per region that may have failed or not responded within the new configurable akka.cluster.sharding.shard-region-query-timeout. This is described further in inspecting sharding state.

Distributed Data

Config for message payload size

Configuration properties for controlling sizes of Gossip and DeltaPropagation messages in Distributed Data have been reduced. Previous defaults sometimes resulted in messages exceeding max payload size for remote actor messages.

The new configuration properties are:

akka.cluster.distributed-data.max-delta-elements = 500
akka.cluster.distributed-data.delta-crdt.max-delta-size = 50

DataDeleted

DataDeleted has been changed in its usage. While it is still a possible response to a Delete request, it is no longer the response when an Update or Get request couldn’t be performed because the entry has been deleted. In its place are two new possible responses to a request, UpdateDataDeleted for an Update and GetDataDeleted for a Get.

The reason for this change is that DataDeleted didn’t extend the UpdateResponse and GetResponse types and could therefore cause problems when Update and Get were used with ask. This was also a problem for Akka Typed.

CoordinatedShutdown is run from ActorSystem.terminate

No migration is needed but it is mentioned here because it is a change in behavior.

When ActorSystem.terminate() is called, CoordinatedShutdown will be run in Akka 2.6.x, which wasn’t the case in 2.5.x. For example, if using Akka Cluster this means that member will attempt to leave the cluster gracefully.

If this is not desired behavior, for example in tests, you can disable this feature with the following configuration and then it will behave as in Akka 2.5.x:

akka.coordinated-shutdown.run-by-actor-system-terminate = off

Scheduler not running tasks when shutdown

When the ActorSystem was shutting down and the Scheduler was closed all outstanding scheduled tasks were run, which was needed for some internals in Akka but a surprising behavior for end users. Therefore this behavior has changed in Akka 2.6.x and outstanding tasks are not run when the system is terminated.

Instead, system.registerOnTermination or CoordinatedShutdown can be used for running such tasks when the shutting down.

IOSources & FileIO

FileIO.toPath, StreamConverters.fromInputStream, and StreamConverters.fromOutputStream now always fail the materialized value in case of failure. It is no longer required to both check the materialized value and the Try[Done] inside the IOResultIOResult. In case of an IO failure the exception will be IOOperationIncompleteExceptionIOOperationIncompleteException instead of AbruptIOTerminationExceptionAbruptIOTerminationException.

Additionally when downstream of the IO-sources cancels with a failure, the materialized value is failed with that failure rather than completed successfully.

Akka now uses Fork Join Pool from JDK

Previously, Akka contained a shaded copy of the ForkJoinPool. In benchmarks, we could not find significant benefits of keeping our own copy, so from Akka 2.6.0 on, the default FJP from the JDK will be used. The Akka FJP copy was removed.

Logging of dead letters

When the number of dead letters have reached configured akka.log-dead-letters value it didn’t log more dead letters in Akka 2.5.x. In Akka 2.6.x the count is reset after configured akka.log-dead-letters-suspend-duration.

akka.log-dead-letters-during-shutdown default configuration changed from on to off.

Cluster failure detection

Default number of nodes that each node is observing for failure detection has increased from 5 to 9. The reason is to have better coverage and unreachability information for downing decisions.

Configuration property:

akka.cluster.monitored-by-nr-of-members = 9

TestKit

expectNoMessage() without timeout parameter is now using a new configuration property akka.test.expect-no-message-default (short timeout) instead of remainingOrDefault (long timeout).

Config library resolution change

The Lightbend Config Library has been updated to load both reference.conf and user config files such as application.conf before substitution of variables used in the reference.conf. This makes it possible to override such variables in reference.conf with user configuration.

For example, the default config for Cluster Sharding, refers to the default config for Distributed Data, in reference.conf like this:

akka.cluster.sharding.distributed-data = ${akka.cluster.distributed-data}

In Akka 2.5.x this meant that to override default gossip interval for both direct use of Distributed Data and Cluster Sharding in the same application you would have to change two settings:

akka.cluster.distributed-data.gossip-interval = 3s
akka.cluster.sharding.distributed-data = 3s

In Akka 2.6.0 and forward, changing the default in the akka.cluster.distributed-data config block will be done before the variable in reference.conf is resolved, so that the same change only needs to be done once:

akka.cluster.distributed-data.gossip-interval = 3s

The following default settings in Akka are using such substitution and may be affected if you are changing the right hand config path in your application.conf:

akka.cluster.sharding.coordinator-singleton = ${akka.cluster.singleton}
akka.cluster.sharding.distributed-data = ${akka.cluster.distributed-data}
akka.cluster.singleton-proxy.singleton-name = ${akka.cluster.singleton.singleton-name}
akka.cluster.typed.receptionist.distributed-data = ${akka.cluster.distributed-data}
akka.remote.classic.netty.ssl = ${akka.remote.classic.netty.tcp}
akka.remote.artery.advanced.materializer = ${akka.stream.materializer}

Source incompatibilities

StreamRefs

The materialized value for StreamRefs.sinkRef and StreamRefs.sourceRef is no longer wrapped in Future/CompletionStage. It can be sent as reply to sender() immediately without using the pipe pattern.

StreamRefs was marked as may change.

Akka Typed

Naming convention changed

In needing a way to distinguish the new APIs in code and docs from the original, Akka used the naming convention untyped. All references of the original have now been changed to classic. The reference of the new APIs as typed is going away as it becomes the primary APIs.

Receptionist has moved

The receptionist had a name clash with the default Cluster Client Receptionist at /system/receptionist and will now instead either run under /system/localReceptionist or /system/clusterReceptionist.

The path change means that the receptionist information will not be disseminated between 2.5.x and 2.6.x nodes during a rolling update from 2.5.x to 2.6.x if you use Akka Typed. See rolling updates with typed Receptionist

Cluster Receptionist using own Distributed Data

In 2.5.x the Cluster Receptionist was using the shared Distributed Data extension but that could result in undesired configuration changes if the application was also using that and changed for example the role configuration.

In 2.6.x the Cluster Receptionist is using it’s own independent instance of Distributed Data.

This means that the receptionist information will not be disseminated between 2.5.x and 2.6.x nodes during a rolling update from 2.5.x to 2.6.x if you use Akka Typed. See rolling updates with typed Cluster Receptionist

Akka Typed API changes

Akka Typed APIs were still marked as may change in Akka 2.5.x and a few changes were made before finalizing the APIs. Compared to Akka 2.5.x the source incompatible changes are:

  • Behaviors.intercept now takes a factory function for the interceptor.
  • ActorSystem.scheduler previously gave access to the classic akka.actor.Scheduler but now returns a specific akka.actor.typed.Scheduler. Additionally schedule method has been replaced by scheduleWithFixedDelay and scheduleAtFixedRate. Actors that needs to schedule tasks should prefer Behaviors.withTimers.
  • TimerScheduler.startPeriodicTimer, replaced by startTimerWithFixedDelay or startTimerAtFixedRate
  • Routers.pool now take a factory function rather than a Behavior to protect against accidentally sharing same behavior instance and state across routees.
  • The request parameter in Distributed Data commands was removed, in favor of using ask with the new ReplicatorMessageAdapter.
  • Removed Behavior.same, Behavior.unhandled, Behavior.stopped, Behavior.empty, and Behavior.ignore since they were redundant with corresponding scaladsl.Behaviors.xjavadsl.Behaviors.x.
  • ActorContext parameter removed in javadsl.ReceiveBuilder for the functional style in Java. Use Behaviors.setup to retrieve ActorContext, and use an enclosing class to hold initialization parameters and ActorContext.
  • Java EntityRef ask timeout now takes a java.time.Duration rather than a TimeoutTimeout
  • Changed method signature for EventAdapter.fromJournal and support for manifest in EventAdapter.
  • Renamed widenBehaviors.widen to transformMessagesBehaviors.transformMessages
  • BehaviorInterceptor, Behaviors.monitor, Behaviors.withMdc and transformMessagesBehaviors.transformMessages takes a ClassTag parameter (probably source compatible)interceptMessageClass parameter. interceptMessageType method in BehaviorInterceptor is replaced with this ClassTagClass parameter.
  • Behavior.orElse has been removed because it wasn’t safe together with narrow.
  • StashBuffers are now created with Behaviors.withStash rather than instantiating directly
  • To align with the Akka Typed style guide SpawnProtocol is now created through SpawnProtocol()SpawnProtocol.create(), the special Spawn message factories has been removed and the top level of the actor protocol is now SpawnProtocol.Command
  • Future removed from ActorSystem.systemActorOf.
  • toUntyped has been renamed to toClassic.
  • Akka Typed is now using SLF4J as the logging API. ActorContext.logActorContext.getLog returns an org.slf4j.Logger. MDC has been changed to only support String values.
  • setLoggerClass in ActorContext has been renamed to setLoggerName.
  • GetDataDeleted and UpdateDataDeleted introduced as described in DataDeleted.
  • SubscribeResponse introduced in Subscribe because the responses can be both Changed and Deleted.
  • ReplicationDeleteFailure renamed to DeleteFailure.
  • EventSourcedEntity removed in favor using plain EventSourcedBehavior because the alternative way was causing more confusion than adding value. Construction of PersistentId for the EventSourcedBehavior is facilitated by factory methods in PersistenceId.
  • PersistenceId.apply(String) renamed to PersistenceId.ofUniqueId(String)
  • akka.cluster.sharding.typed.scaladsl.Entity.apply changed to use two parameter lists because the new EntityContext.entityTypeKey required additional type parameter that is inferred better with a secondary parameter list.
  • EventSourcedBehavior.withEnforcedReplies signature changed. Command is not required to extend ExpectingReply anymore. ExpectingReply has therefore been removed.
  • ActorContext is now a mandatory constructor parameter in AbstractBehavior. Create via Behaviors.setup. The reason is to encourage right usage and detect mistakes like not creating a new instance (viasetup`) when the behavior is supervised and restarted.
  • LoggingEventFilter has been renamed to LoggingTestKit and its intercept method renamed to assert
  • Scala ask from AskPattern now implicitly converts an implicit ActorSystem[_] to Scheduler to eliminate some boilerplate.

Akka Typed Stream API changes

  • ActorSource.actorRef relying on PartialFunction has been replaced in the Java API with a variant more suitable to be called by Java.
  • Factories for creating a materializer from an akka.actor.typed.ActorSystem have been removed. A stream can be run with an akka.actor.typed.ActorSystem in implicit scopeparameter and therefore the need for creating a materializer has been reduced.
  • actorRefWithAck has been renamed to actorRefWithBackpressure

Akka Stream changes

Materializer changes

A default materializer is now provided out of the box. For the Java API just pass system when running streams, for Scala an implicit materializer is provided if there is an implicit ActorSystem available. This avoids leaking materializers and simplifies most stream use cases somewhat.

The ActorMaterializer factories has been deprecated and replaced with a few corresponding factories in akka.stream.Materializer. New factories with per-materializer settings has not been provided but should instead be done globally through config or per stream, see below for more details.

Having a default materializer available means that most, if not all, usages of Java ActorMaterializer.create() and Scala implicit val materializer = ActorMaterializer() should be removed.

Details about the stream materializer can be found in Actor Materializer Lifecycle

When using streams from typed the same factories and methods for creating materializers and running streams as from classic can now be used with typed. The akka.stream.typed.scaladsl.ActorMaterializer and akka.stream.typed.javadsl.ActorMaterializerFactory that previously existed in the akka-stream-typed module has been removed.

Materializer settings deprecated

The ActorMaterializerSettings class has been deprecated.

All materializer settings are available as configuration to change the system default or through attributes that can be used for individual streams when they are materialized.

MaterializerSettings Corresponding attribute Config
initialInputBufferSize Attributes.inputBuffer(initial, max) akka.stream.materializer.initial-input-buffer-size
maxInputBufferSize Attributes.inputBuffer(initial, max) akka.stream.materializer.max-input-buffer-size
dispatcher ActorAttributes.dispatcher(name) akka.stream.materializer.dispatcher
supervisionDecider ActorAttributes.supervisionStrategy na
debugLogging ActorAttributes.debugLogging akka.stream.materializer.debug-logging
outputBurstLimit ActorAttributes.outputBurstLimit akka.stream.materializer.output-burst-limit
fuzzingMode ActorAttributes.fuzzingMode akka.stream.materializer.debug.fuzzing-mode
autoFusing no longer used (since 2.5.0) na
maxFixedBufferSize ActorAttributes.maxFixedBufferSize akka.stream.materializer.max-fixed-buffer-size
syncProcessingLimit ActorAttributes.syncProcessingLimit akka.stream.materializer.sync-processing-limit
IOSettings.tcpWriteBufferSize Tcp.writeBufferSize akka.stream.materializer.io.tcp.write-buffer-size
blockingIoDispatcher na akka.stream.materializer.blocking-io-dispatcher
StreamRefSettings Corresponding StreamRefAttributes Config
bufferCapacity bufferCapacity akka.stream.materializer.stream-ref.buffer-capacity
demandRedeliveryInterval demandRedeliveryInterval akka.stream.materializer.stream-ref.demand-redelivery-interval
subscriptionTimeout subscriptionTimeout akka.stream.materializer.stream-ref.subscription-timeout
finalTerminationSignalDeadline finalTerminationSignalDeadline akka.stream.materializer.stream-ref.final-termination-signal-deadline
SubscriptionTimeoutSettings Corresponding ActorAttributes Config
subscriptionTimeoutSettings.mode streamSubscriptionTimeoutMode akka.stream.materializer.subscription-timeout.mode
subscriptionTimeoutSettings.timeout streamSubscriptionTimeout akka.stream.materializer.subscription-timeout.timeout

Setting attributes on individual streams can be done like so:

Scala
val stream: RunnableGraph[Future[Done]] =
  Source(1 to 10)
    .map(_.toString)
    .toMat(Sink.foreach(println))(Keep.right)
    .withAttributes(Attributes.inputBuffer(4, 4) and
    ActorAttributes.dispatcher("my-stream-dispatcher") and
    TcpAttributes.tcpWriteBufferSize(2048))

stream.run()
Java
RunnableGraph<CompletionStage<Done>> stream =
    Source.range(1, 10)
        .map(Object::toString)
        .toMat(Sink.foreach(System.out::println), Keep.right())
        .withAttributes(
            Attributes.inputBuffer(4, 4)
                .and(ActorAttributes.dispatcher("my-stream-dispatcher"))
                .and(TcpAttributes.tcpWriteBufferSize(2048)));

    stream.run(system);

Stream cancellation available upstream

Previously an Akka streams stage or operator failed it was impossible to discern this from the stage just cancelling. This has been improved so that when a stream stage fails the cause will be propagated upstream.

The following operators have a slight change in behavior because of this:

  • FileIO.fromPath, FileIO.fromFile and StreamConverters.fromInputStream will fail the materialized future with an IOOperationIncompleteException when downstream fails
  • .watchTermination will fail the materialized Future or CompletionStage rather than completing it when downstream fails
  • StreamRef - SourceRef will cancel with a failure when the receiving node is downed

This also means that custom GraphStage implementations should be changed to pass on the cancellation cause when downstream cancels by implementing the OutHandler.onDownstreamFinish signature taking a cause parameter and calling cancelStage(cause) to pass the cause upstream. The old zero-argument onDownstreamFinish method has been deprecated.

Lazy and async stream operator changes

The operators that provide support for lazy and FutureCompletionStage stream construction were revised to be more consistent.

The materialized value is now no longer wrapped in an OptionOptional, instead the FutureCompletionStage is failed with a akka.stream.NeverMaterializedException in the cases that would previously lead to Nonean empty Optional

A deferred creation of the stream based on the initial element like how the deprecated lazyInit worked can be achieved by combining future(Flow|Sink) completionStage(Flow|Sink) with prefixAndTail. See example in futureFlow completionStageFlow.

javadsl.Flow

old new
lazyInit lazyCompletionStageFlow in combination with prefixAndTail(1)
lazyInitAsync lazyCompletionStageFlow
completionStageFlow
lazyFlow

javadsl.Sink

old new
lazyInit lazyCompletionStageSink in combination with Flow.prefixAndTail(1)
lazyInitAsync lazyCompletionStageSink
completionStageSink
lazySink

javadsl.Source

old new
fromFuture future
fromCompletionStage completionStage
fromFutureSource futureSource
fromSourceCompletionStage completionStageSource
lazily lazySource
lazilyAsync lazyCompletionStage
lazySingle
lazyCompletionStageSource

scaladsl.Flow

old new
lazyInit lazyFutureFlow
lazyInitAsync lazyFutureFlow
futureFlow
lazyFlow

scaladsl.Sink

old new
lazyInit lazyFutureSink in combination with Flow.prefixAndTail(1)
lazyInitAsync lazyFutureSink
futureSink
lazySink

scaladsl.Source

old new
fromFuture future
fromCompletionStage completionStage
fromFutureSource futureSource
fromSourceCompletionStage
lazily lazySource
lazilyAsync lazyFuture
lazySingle
lazyFutureSource
Found an error in this documentation? The source code for this page can be found here. Please feel free to edit and contribute a pull request.