Akka 2.4 plus commercial features in Typesafe Reactive Platform

Akka 2.4.x and

Commercial Features1 September 2015

Akka 2.4 and RP commercial featureswith Konrad `@ktosopl` Malawski

Konrad `ktoso` Malawski

Akka Team,Reactive Streams TCK

Reactive Platform: Akka

• Reactive Platform: Versioning explained• Remoting / Cluster: Docker networking support• Cluster: Split Brain Resolver (beta)• Akka Persistence: Cross-Scala-version snapshot deserializer• Java 6: Extended LTS

• Akka 2.4.x (currently in Release Candidate phase)• Cluster Tools promoted to stable!• Persistence promoted to stable!• Persistence Queries (experimental)• Akka Typed (experimental)• Distributed Data (experimental)• Akka Streams (currently 1.0, will be included in 2.4.x eventually)

• Q / AAkka 2.4 and RP commercial features

with Konrad `@ktosopl` Malawski

Reactive Platform

https://together.typesafe.com/products/reactivePlatform

Reactive Platform Versioning

15v05p01

patch=

Scala 2.10.xAkka 2.3.x …

15v05p01

patch=

Scala 2.10.xAkka 2.3.x …

15v09p01 =

Scala 2.11.xAkka 2.3.12 => 2.3.++ (binary compatible!) …

How does this help?• Huge integration test suite before release• Certified to work well together• Priority updates / additional features• Back-ports, fixes, long-term support

Life cycle of each release: 2 years

NAT Support

support(NAT support)

Available in: RP 15v01p## (Akka 2.3.x), OSS only in Akka 2.4.x (work in progress)

Docker / NAT support

docker run -d -p 8000:2551 akka-app

Akka App

172.17.0.11:2551

Outside world

example.com:8000

doc.akka.io/docs/akka/2.4.0-RC1/general/remoting.html#Peer-to-Peer_vs__Client-Server

Docker / NAT support

akka.remote { netty.tcp { hostname = example.com # external (logical) hostname port = 8000 # external (logical) port

bind-hostname = 172.17.0.11 # internal (bind) hostname bind-port = 2552 # internal (bind) port }}

doc.akka.io/docs/akka/2.4.0-RC1/general/remoting.html#Peer-to-Peer_vs__Client-Server

Split Brain Resolver

Split Brain Resolver (customer beta)

Installing the Reactive Platform with Split Brain Resolver

• Fundamental Problem in all distributed systems• SBR helps to make decisions, is not a magic wand

• A set of pre-built strategies for when to down nodes in a cluster.

• Strategies:• Static Quorum (like zoo-keeper)• Keep Majority• Keep Oldest• Keep Referee

http://doc.akka.io/docs/akka/rp-15v09p01/scala/split-brain-resolver.html

• The default behaviour of Akka Cluster is “Manual Downing”:• A node needs to issue cluster.down(address)• This decision can be powered by external

monitoring,or DevOps teams observing the cluster.

• It is Safe.however involves the most human/automated work

• A naive implementation exists called “auto-downing”• It is not very safe to be used in real clusters• Definitely not a good choice for apps using

Persistence• It is not recommended for production deployments.Akka 2.4 and RP commercial features

with Konrad `@ktosopl` Malawski

http://doc.akka.io/docs/akka/rp-15v09p01/scala/split-brain-resolver.html

Heartbeats

heartbeats

Heartbeats

heartbeats

everyone is down!

Heartbeats

`n-1` is down!I’ll take over `A`!

Heartbeats

`n-1` is down!I’ll take over `A`!

good if: n-1 really is down.bad: if n-1 is just very unresponsive

Fundamentally, it is hard to distinguish the two states in distributed systems.

Static Quorum (3 (> (n/2 +1))

we need to down ourselves

Keep Majority (aka. dynamic quorum)

we need to down ourselves

referee node

Keep Referee

down-all-if-less-than-nodes

referee node

Keep Referee

can’t see referee node!

down-all-if-less-than-nodes

oldest node

Keep Oldest

can’t see oldest node!

down-if-alone

oldest node can change,if “up until now oldest node” leaves the

cluster.This is more dynamic than keep-

referee.

PersistenceCross-scala-versioncompatibility for snapshots

Persistence: Cross-scala-version compat

Enhanced compatibility for persistent snapshot envelope.(Payload compatibility depends on application.)

• Scala 2.10 is not binary compatible with 2.11• 10 => 11 is “major update” by design

• More compatible deserialisation than the language itself!

• Eases migration to latest Scala versions

• (Your journal may actually not be affected and be compatible anyway.)

• Scala 2.10 is not binary compatible with 2.11• 10 => 11 is “major update” by design

saveSnapshot( )

Akka 2.3 + Scala 2.10

saveSnapshot( )

loadSnapshotsmart serializer

Java 6 Extended LTS

Java 6: Extended LTS

• Existing RP releases keep Java 1.6 compatibility

• Akka Streams & Http currently work with 1.6• will be merged into Akka 2.4 (likely after 1.1)• we can back-port and support for RP (Akka 2.3)

• Akka 2.4 does require Java 8• Scala 2.11 + Scala 2.12 (once released)• it will enter RP once released

Akka 2.4

• 2.3 => 2.4 is a major update• additional effort made it binary compatible!• it does require Java 1.8

• i.e. update your JDK, same sources “just work”

• Future:• Version bump to 3.0 if binary incompatible

Cluster Tools

Now Stable!

Akka 2.4 Cluster Tools (Now Stable!)

• Distributed Pub Sub• Smart message batching (1 send per node)

• Cluster Singleton• useful for “master” or coordinator Actors

• Cluster Sharding• useful for sharding load onto the cluster• graceful shut-down• balancing load across cluster

doc.akka.io/docs/akka/2.4.0-RC1/scala/distributed-pub-sub.html

class Subscriber extends Actor with ActorLogging {

import DistributedPubSubMediator.{ Subscribe, SubscribeAck } val mediator = DistributedPubSub(context.system).mediator // subscribe to the topic named "content" mediator ! Subscribe("content", self) def receive = { case SubscribeAck(Subscribe("content", None, `self`)) ⇒ context become ready } def ready: Actor.Receive = { case s: String ⇒ log.info("Got {}", s) }}

Akka 2.4 Cluster Tools - PubSub (Now Stable!)

class Publisher extends Actor { import DistributedPubSubMediator.Publish // activate the extension val mediator = DistributedPubSub(context.system).mediator def receive = { case in: String ⇒ val out = in.toUpperCase mediator ! Publish("content", out) }}

doc.akka.io/docs/akka/2.4.0-RC1/scala/distributed-pub-sub.html

Akka 2.4 Cluster Tools - PubSub (Now Stable!)

http://doc.akka.io/docs/akka/2.4.0-RC1/scala/cluster-singleton.html

Akka 2.4 Cluster Tools - Cluster Singleton (Now Stable!)

role: backend-2 role: backend-2

http://doc.akka.io/docs/akka/2.4.0-RC1/scala/cluster-singleton.html

Akka 2.4 Cluster Tools - Cluster Singleton (Now Stable!)

Akka 2.4 Cluster Tools - Sharding (Now Stable!)

doc.akka.io/docs/akka/2.4.0-RC1/scala/cluster-sharding.html

Akka 2.4 Cluster Tools - Sharding (Now Stable!)

val counterRegion: ActorRef = ClusterSharding(system).start( typeName = "Counter", entityProps = Props[Counter], settings = ClusterShardingSettings(system), extractEntityId = extractEntityId, extractShardId = extractShardId)

val counterRegion: ActorRef = ClusterSharding(system).shardRegion("Counter")counterRegion ! Get(123)expectMsg(0)

Start a shard region:

Other nodes in cluster send messages to it:

doc.akka.io/docs/akka/2.4.0-RC1/scala/cluster-sharding.html

Persistence

Now Stable!

var state = S0

persistenceId = “a”

Command

Journal

Akka 2.4 Persistence (Now Stable!)

var state = S0

Journal

Generate Events

var state = S0

Journal

Generate Events

ACK “persisted”

Journal

var state = S0

“Apply” event

Journal

var state = S0

Journal

var state = S0

E1Okey!

Journal

var state = S0

E1Okey!

Journal

var state = S0

Ok, he got my $.

…sum of states…

Journal

E1 E2 E3 E4

E5 E6 E7 E8

Snapshot Store

snapshot!

state until [E5]

S5Journal

E1 E2 E3 E4

E5 E6 E7 E8

Snapshot Store

state until [E8]

S8Journal

E1 E2 E3 E4

E5 E6 E7 E8

state until [E8]

Snapshot Store

Journal

E1 E2 E3 E4

E5 E6 E7 E8

crash!

Snapshot Store

Journal

E1 E2 E3 E4

E5 E6 E7 E8

crash!

“bring me up-to-date!”

Snapshot Store

Journal

E1 E2 E3 E4

E5 E6 E7 E8

restart!

replay!

“bring me up-to-date!”

Snapshot Store

restart!

replay!

S5Journal

E1 E2 E3 E4

E5 E6 E7 E8

state until [E8]

Snapshot Store

restart!

replay!

S8Journal

E1 E2 E3 E4

E5 E6 E7 E8

Advanced support for long-term schema evolution.

EventAdapters & StringManifestSerializers

Persistence Query

New module, experimental!

Akka 2.4 Persistence Queries (experimental)

API still work in progress, should be polished very soon.

val query: Source[RichEvent, QueryStats] = readJournal.query(ByTagsWithStats(Set("red", "blue")))

query .map { event => s"Event payload: ${event.payload}" } .runWith(Sink.ignore)

Akka 2.4 Persistence Queries (experimental)

API still work in progress, should be polished very soon.

val query: Source[RichEvent, QueryStats] = readJournal.query(ByTagsWithStats(Set("red", "blue")))

query .map { event => s"Event payload: ${event.payload}" } .runWith(Sink.ignore)

Journalwrite-side

query-side

QueryOptimised

Journal

query-side

Simple view / result

Akka Typed

doc.akka.io/docs/akka/2.4.0-RC1/scala/typed-actors.html

class Greeter extends Actor {

def receive = { case msg: Greet ⇒ println(s"Hello ${msg.whom}!") sender() ! Greeted(msg.whom) }

val system: ActorSystem = ActorSystem(“akka-actor-system“)

val greeter = system.actorOf(Props[Greeter])

system ! Greet("kapi", system.deadLetters)

Akka Actor

Akka 2.4 Typed (experimental)

val greeter = Total[Greet] { msg ⇒

println(s"Hello ${msg.whom}!") msg.replyTo ! Greeted(msg.whom)

val system: ActorSystem[Greet] = ActorSystem(“typed", Props(totalGreeter))

Akka Actor Akka Typed

The main concept is Behaviour[T]Explicit protocols for the win!

Since Behaviour[Greet] is typed,

msg is-a Greet.

The Behaviour[T]is the receive.

sender() is no more.Explicit protocols for the win!

final case class Greet(whom: String, replyTo: ActorRef[Greeted])

ActorRef[T] is now typed!

def receive = { case msg: Greet ⇒ println(s"Hello ${msg.whom}!") sender() ! Greeted(msg.whom)

become()is required.

And replaced by returning the “next” Behaviour[T]

// context.become(receive)

And replaced by returning the “next” Behaviour[T]On a conceptual level at least,

we provide Static[T]if you don’t need become.

And replaced by returning the “next” Behaviour[T]Special behaviors:

Same / Unhandled / Empty / Stopped / Ignore

“Root actor” is not user-defined for ActorSystem[T]

Encourages thinking about supervision.

Akka Distributed Data

Akka 2.4 Distributed Data (experimental)

for “small, fast data”

Implements various CRDTs and gossips changes through the Cluster.

CRDTs = Conflict-free Replicated Data TypesData structures that can be concurrently updatedand always eventually converge on the same value.

doc.akka.io/docs/akka/2.4.0-RC1/scala/distributed-data.html

for “small, fast data”

Implements various CRDTs and gossips changes through the Cluster.

CRDTs = Conflict-free Replicated Data TypesData structures that can be concurrently updatedand always eventually converge on the same value.

value = 5n1: 2n2: 0n3: 3 Akka Cluster (gossip)

GCounter example:

value = 5n1: 2n2: 0n3: 3

node-1 node-2

node-3

value = 6n1: 2+1n2: 0n3: 3 Akka Cluster (gossip)

GCounter example:

value = 5n1: 2n2: 0n3: 3

value = 6n1: 2n2: 0n3: 3+1

node-1 node-2

node-3

node-1 node-2

node-3

value = 7n1: 2+1n2: 0

n3: 3+1 Akka Cluster (gossip)

GCounter example:

value = 5n1: 2n2: 0n3: 3

value = 6n1: 2n2: 0n3: 3+1

node-1 node-2

node-3

value = 7n1: 2+1n2: 0

n3: 3+1 Akka Cluster (gossip)

GCounter example:

value = 7n1: 2+1n2: 0

n3: 3+1

value = 7n1: 2+1n2: 0n3: 3+1

implicit val node = Cluster(system)val replicator = DistributedData(system).replicator val Counter1Key = PNCounterKey("counter1")

replicator ! Update(Counter1Key, PNCounter(), WriteLocal)(_ + 1)

Provided data types:• Counters: GCounter, PNCounter• Sets: GSet, ORSet• Maps: ORMap, ORMultiMap, LWWMap, PNCounterMap• Registers: LWWRegister, Flag

Akka Streams & Http

1.0 (experimental) currently.will join the Akka 2.4.x release.

Akka Streams & Http (experimental, to eventually join Akka 2.4.x)

Akka StreamsAsynchronous Back-pressured Stream ProcessingAn implementation of Reactive Streams.

Reactive Streamsan initiative co-lead by Typesafe, Netflix, Pivotal, RedHat),allowing for inter-op of asynchronous streaming libraries.

Akka Http Superseeds Spray.io, the well known high-performance Http serverFully based on Akka Streams.

http://doc.akka.io/docs/akka-stream-and-http-experimental/1.0/scala.html

http://www.reactive-streams.org/

Reactive Streams (1.0, en route to be included in JDK9)

Akka Streams <-> Actors – Advanced

val subscriber = ActorSubscriber( system.actorOf(Props[SubStreamParent], ”parent”))

Source(1 to 100) .map(_.toString) .filter(_.length == 2) .drop(2) .conflate(seed => seed)((acc, i) => acc + i) .groupBy(_.last) .runWith(subscriber)

All the usual ops available for Linear Flows.

http://doc.akka.io/docs/akka-stream-and-http-experimental/1.0/scala.html

Links• akka.io• reactive-streams.org• akka-user• https://www.typesafe.com/subscription

• Streams and Http• http://doc.akka.io/docs/akka-stream-and-http-exp

erimental/1.0/scala.html• http://doc.akka.io/docs/akka-stream-and-http-exp

erimental/1.0/java.html

• Akka 2.4 RC1• http://doc.akka.io/docs/akka/2.4.0-RC1/scala.html• http://doc.akka.io/docs/akka/2.4.0-RC1/java.html

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Akka 2.4 plus commercial features in Typesafe Reactive Platform

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