Building Reactive Systems with Akka (in Java 8 or Scala)
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Building Reactive Systems with Akka (in Java 8 or Scala)

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Learn how to build Reactive Systems with Akka. Examples in both Java 8 and Scala. ...

Learn how to build Reactive Systems with Akka. Examples in both Java 8 and Scala.

Abstract:
The demands and expectations for applications have changed dramatically in recent years. Applications today are deployed on a wide range of infrastructure; from mobile devices up to thousands of nodes running in the cloud—all powered by multi-core processors. They need to be rich and collaborative, have a real-time feel with millisecond response time and should never stop running. Additionally, modern applications are a mashup of external services that need to be consumed and composed to provide the features at hand. We are seeing a new type of applications emerging to address these new challenges—these are being called Reactive Applications.

In this talk we will introduce you to Akka and discuss how it can help you deliver on the four key traits of Reactive; Responsive, Resilient, Elastic and Message-Driven. We will start with the basics of Akka and work our way towards some of its more advanced modules such as Akka Cluster and Akka Persistence—all driven through code and practical examples.

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Building Reactive Systems with Akka (in Java 8 or Scala) Building Reactive Systems with Akka (in Java 8 or Scala) Presentation Transcript

  • Building Reactive Systems with Akka Jonas Bonér Typesafe CTO & co-founder Twitter: @jboner
  • The rules of the game have changed
  • 3 Apps in the 60s-90s were written for Apps today are written for
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines Single core processors
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines Single core processors Multicore processors
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines Single core processors Multicore processors Expensive RAM
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines Single core processors Multicore processors Expensive RAM Cheap RAM
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines Single core processors Multicore processors Expensive RAM Cheap RAM Expensive disk
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines Single core processors Multicore processors Expensive RAM Cheap RAM Expensive disk Cheap disk
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines Single core processors Multicore processors Expensive RAM Cheap RAM Expensive disk Cheap disk Slow networks
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines Single core processors Multicore processors Expensive RAM Cheap RAM Expensive disk Cheap disk Slow networks Fast networks
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines Single core processors Multicore processors Expensive RAM Cheap RAM Expensive disk Cheap disk Slow networks Fast networks Few concurrent users
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines Single core processors Multicore processors Expensive RAM Cheap RAM Expensive disk Cheap disk Slow networks Fast networks Few concurrent users Lots of concurrent users
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines Single core processors Multicore processors Expensive RAM Cheap RAM Expensive disk Cheap disk Slow networks Fast networks Few concurrent users Lots of concurrent users Small data sets
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines Single core processors Multicore processors Expensive RAM Cheap RAM Expensive disk Cheap disk Slow networks Fast networks Few concurrent users Lots of concurrent users Small data sets Large data sets
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines Single core processors Multicore processors Expensive RAM Cheap RAM Expensive disk Cheap disk Slow networks Fast networks Few concurrent users Lots of concurrent users Small data sets Large data sets Latency in seconds
  • 3 Apps in the 60s-90s were written for Apps today are written for Single machines Clusters of machines Single core processors Multicore processors Expensive RAM Cheap RAM Expensive disk Cheap disk Slow networks Fast networks Few concurrent users Lots of concurrent users Small data sets Large data sets Latency in seconds Latency in milliseconds
  • Cost Gravity is at Work X
  • Cost Gravity is at Work X
  • Reactive applications share four traits Reactive Applications 5
  • Reactive applications enrich the user experience with low latency response.
  • Responsive • Real-time, engaging, rich and collaborative • Create an open and ongoing dialog with users • More efficient workflow; inspires a feeling of connectedness • Fully Reactive enabling push instead of pull 7 “The move to these technologies is already paying off. Response times are down for processor intensive code–such as image and PDF generation–by around 75%.” Brian Pugh, VP of Engineering, Lucid Software
  • Reactive applications react to changes in the world around them.
  • Message-Driven • Loosely coupled architecture, easier to extend, maintain, evolve • Asynchronous and non-blocking • Concurrent by design, immutable state • Lower latency and higher throughput 9 “Clearly, the goal is to do these operations concurrently and non-blocking, so that entire blocks of seats or sections are not locked. We’re able to find and allocate seats under load in less than 20ms without trying very hard to achieve it.” Andrew Headrick, Platform Architect, Ticketfly
  • Introducing the Actor Model
  • 11 The Actor Model
  • 11 The Actor Model A computational model that embodies:
  • 11 The Actor Model A computational model that embodies: ✓ Processing
  • 11 The Actor Model A computational model that embodies: ✓ Processing ✓ Storage
  • 11 The Actor Model A computational model that embodies: ✓ Processing ✓ Storage ✓ Communication
  • A computational model that embodies: ✓ Processing ✓ Storage ✓ Communication Supports 3 axioms—when an Actor receives a message it can: 11 The Actor Model
  • A computational model that embodies: ✓ Processing ✓ Storage ✓ Communication Supports 3 axioms—when an Actor receives a message it can: 1. Create new Actors 11 The Actor Model
  • A computational model that embodies: ✓ Processing ✓ Storage ✓ Communication Supports 3 axioms—when an Actor receives a message it can: 1. Create new Actors 2. Send messages to Actors it knows 11 The Actor Model
  • A computational model that embodies: ✓ Processing ✓ Storage ✓ Communication Supports 3 axioms—when an Actor receives a message it can: 1. Create new Actors 2. Send messages to Actors it knows 3. Designate how it should handle the next message it receives 11 The Actor Model
  • The essence of an actor from Akka’s perspective 0. DEFINE 1. CREATE 2. SEND 3. BECOME 4. SUPERVISE 12
  • public class Greeting implements Serializable { public final String who; public Greeting(String who) { this.who = who; } } ! public class Greeter extends AbstractActor {{ receive(ReceiveBuilder. match(Greeting.class, m -> { println(“Hello " + m.who); }). matchAny(unknown -> { println(“Unknown message " + unknown); }).build()); }} 0. DEFINE X
  • public class Greeting implements Serializable { public final String who; public Greeting(String who) { this.who = who; } } ! public class Greeter extends AbstractActor {{ receive(ReceiveBuilder. match(Greeting.class, m -> { println(“Hello " + m.who); }). matchAny(unknown -> { println(“Unknown message " + unknown); }).build()); }} 0. DEFINE X Define the message(s) the Actor should be able to respond to
  • public class Greeting implements Serializable { public final String who; public Greeting(String who) { this.who = who; } } ! public class Greeter extends AbstractActor {{ receive(ReceiveBuilder. match(Greeting.class, m -> { println(“Hello " + m.who); }). matchAny(unknown -> { println(“Unknown message " + unknown); }).build()); }} 0. DEFINE X Define the message(s) the Actor should be able to respond to Define the Actor class
  • public class Greeting implements Serializable { public final String who; public Greeting(String who) { this.who = who; } } ! public class Greeter extends AbstractActor {{ receive(ReceiveBuilder. match(Greeting.class, m -> { println(“Hello " + m.who); }). matchAny(unknown -> { println(“Unknown message " + unknown); }).build()); }} 0. DEFINE X Define the message(s) the Actor should be able to respond to Define the Actor class Define the Actor’s behavior
  • 1. CREATE ActorSystem system = ActorSystem.create("MySystem"); ! ActorRef greeter = system.actorOf(Props.create(Greeter.class), “greeter");
  • 1. CREATE Create an Actor system ActorSystem system = ActorSystem.create("MySystem"); ! ActorRef greeter = system.actorOf(Props.create(Greeter.class), “greeter");
  • 1. CREATE Create an Actor system Actor configuration ActorSystem system = ActorSystem.create("MySystem"); ! ActorRef greeter = system.actorOf(Props.create(Greeter.class), “greeter");
  • 1. CREATE Create an Actor system Actor configuration ActorSystem system = ActorSystem.create("MySystem"); ! ActorRef greeter = system.actorOf(Props.create(Greeter.class), “greeter"); Give it a name
  • 1. CREATE Create an Actor system ActorSystem system = ActorSystem.create("MySystem"); ! ActorRef greeter = system.actorOf(Props.create(Greeter.class), “greeter"); Give it a name Create the Actor Actor configuration
  • 1. CREATE Create an Actor system ActorSystem system = ActorSystem.create("MySystem"); ! ActorRef greeter = system.actorOf(Props.create(Greeter.class), “greeter"); Give it a name You get an ActorRef back Create the Actor Actor configuration
  • 0. DEFINE case class Greeting(who: String) ! class GreetingActor extends Actor with ActorLogging { def receive = { 13 case Greeting(who) => log.info(s"Hello ${who}") } }
  • 0. DEFINE 13 Define the message(s) the Actor should be able to respond to case class Greeting(who: String) ! class GreetingActor extends Actor with ActorLogging { def receive = { case Greeting(who) => log.info(s"Hello ${who}") } }
  • 0. DEFINE 13 Define the message(s) the Actor should be able to respond to Define the Actor class case class Greeting(who: String) ! class GreetingActor extends Actor with ActorLogging { def receive = { case Greeting(who) => log.info(s"Hello ${who}") } }
  • 0. DEFINE 13 Define the message(s) the Actor should be able to respond to Define the Actor class case class Greeting(who: String) ! class GreetingActor extends Actor with ActorLogging { def receive = { case Greeting(who) => log.info(s"Hello ${who}") } } Define the Actor’s behavior
  • 1. CREATE case class Greeting(who: String) ! class GreetingActor extends Actor with ActorLogging { def receive = { case Greeting(who) => log.info("Hello " + who) } } ! val system = ActorSystem("MySystem") val greeter = system.actorOf(Props[GreetingActor], name = "greeter")
  • 1. CREATE case class Greeting(who: String) ! class GreetingActor extends Actor with ActorLogging { def receive = { Create an Actor system case Greeting(who) => log.info("Hello " + who) } } ! val system = ActorSystem("MySystem") val greeter = system.actorOf(Props[GreetingActor], name = "greeter")
  • 1. CREATE case class Greeting(who: String) ! class GreetingActor extends Actor with ActorLogging { def receive = { Create an Actor system case Greeting(who) => log.info("Hello " } Actor configuration + who) } ! val system = ActorSystem("MySystem") val greeter = system.actorOf(Props[GreetingActor], name = "greeter")
  • 1. CREATE case class Greeting(who: String) ! class GreetingActor extends Actor with ActorLogging { def receive = { case Greeting(who) => log.info("Hello " + who) } } ! val system = ActorSystem("MySystem") val greeter = system.actorOf(Props[GreetingActor], name = "greeter") Give it a name Create an Actor system Actor configuration
  • 1. CREATE case class Greeting(who: String) ! class GreetingActor extends Actor with ActorLogging { def receive = { Create an Actor system case Greeting(who) => log.info("Hello " } Actor configuration + who) } ! val system = ActorSystem("MySystem") val greeter = system.actorOf(Props[GreetingActor], name = "greeter") Give it a name Create the Actor
  • 1. CREATE case class Greeting(who: String) ! class GreetingActor extends Actor with ActorLogging { def receive = { Create an Actor system case Greeting(who) => log.info("Hello " } Actor configuration + who) } ! val system = ActorSystem("MySystem") val greeter = system.actorOf(Props[GreetingActor], name = "greeter") Give it a name You get an ActorRef bCarcekate the Actor
  • Actors can form hierarchies Guardian System Actor
  • Actors can form hierarchies Guardian System Actor system.actorOf(Props.create(Foo.class), “Foo”);
  • Actors can form hierarchies Foo Guardian System Actor system.actorOf(Props.create(Foo.class), “Foo”);
  • Actors can form hierarchies Foo Guardian System Actor context().actorOf(Props.create(A.class), “A”);
  • Actors can form hierarchies A Foo Guardian System Actor context().actorOf(Props.create(A.class), “A”);
  • Actors can form hierarchies A Foo Bar B C B E A D C Guardian System Actor
  • Actors can form hierarchies Guardian System Actor
  • Actors can form hierarchies Guardian System Actor system.actorOf(Props[Foo], “Foo”)
  • Actors can form hierarchies Foo Guardian System Actor system.actorOf(Props[Foo], “Foo”)
  • Actors can form hierarchies Foo Guardian System Actor context.actorOf(Props[A], “A”)
  • Actors can form hierarchies A Foo Guardian System Actor context.actorOf(Props[A], “A”)
  • Actors can form hierarchies A Foo Bar B C B E A D C Guardian System Actor
  • Name resolution—like a file-system A Foo Bar B C B E A D C Guardian System Actor
  • Name resolution—like a file-system A Foo Bar B C B E A D C /Foo Guardian System Actor
  • Name resolution—like a file-system A Foo Bar B C B E A D C /Foo /Foo/A Guardian System Actor
  • Name resolution—like a file-system A Foo Bar B C B E A D C /Foo /Foo/A /Foo/A/B Guardian System Actor
  • Name resolution—like a file-system A Foo Bar B C B E A D C /Foo /Foo/A /Foo/A/B /Foo/A/D Guardian System Actor
  • 2. SEND X greeter.tell(new Greeting("Charlie Parker”), sender);
  • 2. SEND X greeter.tell(new Greeting("Charlie Parker”), sender); Send the message asynchronously
  • 2. SEND X Pass in the sender ActorRef greeter.tell(new Greeting("Charlie Parker”), sender); Send the message asynchronously
  • Bring it together X public class Greeting implements Serializable { public final String who; public Greeting(String who) { this.who = who; } } public class Greeter extends AbstractActor {{ receive(ReceiveBuilder. match(Greeting.class, m -> { println(“Hello " + m.who); }). matchAny(unknown -> { println(“Unknown message " + unknown); }).build()); } }} ! ActorSystem system = ActorSystem.create("MySystem"); ActorRef greeter = system.actorOf(Props.create(Greeter.class), “greeter"); greeter.tell(new Greeting(“Charlie Parker”));
  • 2. SEND 17 case class Greeting(who: String) ! class GreetingActor extends Actor with ActorLogging { def receive = { case Greeting(who) => log.info(s”Hello ${who}") } } ! val system = ActorSystem("MySystem") val greeter = system.actorOf(Props[GreetingActor], name = "greeter") greeter ! Greeting("Charlie Parker")
  • 2. SEND 17 case class Greeting(who: String) ! class GreetingActor extends Actor with ActorLogging { def receive = { case Greeting(who) => log.info(s”Hello ${who}") } } ! val system = ActorSystem("MySystem") val greeter = system.actorOf(Props[GreetingActor], name = "greeter") greeter ! Greeting("Charlie Parker") Send the message asynchronously
  • Bring it together 18 case class Greeting(who: String) ! class GreetingActor extends Actor with ActorLogging { def receive = { case Greeting(who) => log.info(s”Hello ${who}") } } ! val system = ActorSystem("MySystem") val greeter = system.actorOf(Props[GreetingActor], name = "greeter") greeter ! Greeting("Charlie Parker")
  • DEMO TIME A simple game of ping pong
  • 3. BECOME X public class Greeter extends AbstractActor { public Greeter { receive(ReceiveBuilder. match(Greeting.class, m -> { println(“Hello " + m.who); }). matchEquals(“stop" -> { !!!! }).build(); } }
  • 3. BECOME X public class Greeter extends AbstractActor { public Greeter { receive(ReceiveBuilder. match(Greeting.class, m -> { println(“Hello " + m.who); }). matchEquals(“stop" -> { !!!! }).build(); } } context().become(ReceiveBuilder.
  • 3. BECOME X public class Greeter extends AbstractActor { public Greeter { receive(ReceiveBuilder. match(Greeting.class, m -> { println(“Hello " + m.who); }). matchEquals(“stop" -> { !!!! }).build(); } } Change the behavior context().become(ReceiveBuilder.
  • 3. BECOME X public class Greeter extends AbstractActor { public Greeter { receive(ReceiveBuilder. match(Greeting.class, m -> { println(“Hello " + m.who); }). matchEquals(“stop" -> { !!!! }).build(); } } Change the behavior context().become(ReceiveBuilder. match(Greeting.class, m -> {
  • 3. BECOME X public class Greeter extends AbstractActor { public Greeter { receive(ReceiveBuilder. match(Greeting.class, m -> { println(“Hello " + m.who); }). matchEquals(“stop" -> { !!!! }).build(); } } Change the behavior context().become(ReceiveBuilder. match(Greeting.class, m -> { println(“Go Away!”);
  • 3. BECOME X public class Greeter extends AbstractActor { public Greeter { receive(ReceiveBuilder. match(Greeting.class, m -> { println(“Hello " + m.who); }). matchEquals(“stop" -> { !!!! }).build(); } } Change the behavior context().become(ReceiveBuilder. match(Greeting.class, m -> { println(“Go Away!”); }).build());
  • 3. BECOME X public class Greeter extends AbstractActor { public Greeter { receive(ReceiveBuilder. match(Greeting.class, m -> { println(“Hello " + m.who); }). matchEquals(“stop" -> { !!!! }).build(); } } Change the behavior context().become(ReceiveBuilder. match(Greeting.class, m -> { println(“Go Away!”); }).build());
  • 3. BECOME 19 class GreetingActor extends Actor with ActorLogging { def receive = happy ! val happy: Receive = { case Greeting(who) => log.info(s”Hello ${who}") case Angry => context become angry } ! val angry: Receive = { case Greeting(_) => log.info("Go away!") case Happy => context become happy } }
  • 3. BECOME 19 class GreetingActor extends Actor with ActorLogging { def receive = happy ! val happy: Receive = { case Greeting(who) => log.info(s”Hello ${who}") case Angry => context become angry } ! val angry: Receive = { case Greeting(_) => log.info("Go away!") case Happy => context become happy } } Redefine the behavior
  • Reactive applications are architected to handle failure at all levels.
  • Resilient • Failure is embraced as a natural state in the app lifecycle • Resilience is a first-class construct • Failure is detected, isolated, and managed • Applications self heal 21 “The Typesafe Reactive Platform helps us maintain a very aggressive development and deployment cycle, all in a fail-forward manner. It’s now the default choice for developing all new services.” Peter Hausel, VP Engineering, Gawker Media
  • Think Vending Machine
  • Think Vending Machine Coffee Programmer Machine
  • Think Vending Machine Coffee Inserts coins Programmer Machine
  • Think Vending Machine Coffee Inserts coins Add more coins Programmer Machine
  • Think Vending Machine Coffee Inserts coins Add more coins Programmer Machine Gets coffee
  • Think Vending Machine Coffee Programmer Machine
  • Think Vending Machine Coffee Inserts coins Programmer Machine
  • Think Vending Machine Coffee Inserts coins Out of coffee beans error Programmer Machine
  • Think Vending Machine Coffee Inserts coins OutW of corfofeen begans error Programmer Machine
  • Think Vending Machine Coffee Inserts coins Programmer Machine
  • Think Vending Machine Coffee Inserts coins Out of coffee beans error Programmer Machine
  • Think Vending Machine Service Guy Coffee Inserts coins Out of coffee beans error Programmer Machine
  • Think Vending Machine Service Guy Coffee Inserts coins Out of coffee beans error Programmer Machine Adds more beans
  • Think Vending Machine Service Guy Coffee Inserts coins Programmer Machine Gets coffee Out of coffee beans error Adds more beans
  • The Right Way Client Service
  • The Right Way Request Client Service
  • The Right Way Request Client Service Response
  • The Right Way Request Validation Error Client Service Response
  • The Right Way Request Validation Error Client Service Response Application Error
  • The Right Way Supervisor Request Validation Error Client Service Response Application Error
  • The Right Way Supervisor Request Validation Error Client Service Response Application Error Manages Failure
  • Use Bulkheads • Isolate the failure • Compartmentalize • Manage failure locally • Avoid cascading failures
  • Use Bulkheads • Isolate the failure • Compartmentalize • Manage failure locally • Avoid cascading failures
  • Enter Supervision
  • Enter Supervision
  • Supervisor hierarchies A Foo Bar B C B E A D C Automatic and mandatory supervision
  • 4. SUPERVISE X Every single actor has a default supervisor strategy. Which is usually sufficient. But it can be overridden. class Supervisor extends UntypedActor { private SupervisorStrategy strategy = new OneForOneStrategy( 10, Duration.create(1, TimeUnit.MINUTES), DeciderBuilder. match(ArithmeticException.class, e -> resume()). match(NullPointerException.class, e -> restart()). matchAny( e -> escalate()). build()); ! @Override public SupervisorStrategy supervisorStrategy() { return strategy; }
  • 4. SUPERVISE X class Supervisor extends UntypedActor { private SupervisorStrategy strategy = new OneForOneStrategy( 10, Duration.create(1, TimeUnit.MINUTES), DeciderBuilder. match(ArithmeticException.class, e -> resume()). match(NullPointerException.class, e -> restart()). matchAny( e -> escalate()). build()); ! @Override public SupervisorStrategy supervisorStrategy() { return strategy; } ActorRef worker = context.actorOf( Props.create(Worker.class), "worker"); public void onReceive(Object i) throws Exception { … } }
  • Monitor through Death Watch X public class WatchActor extends AbstractActor { final ActorRef child = context().actorOf(Props.empty(), "child"); ! public WatchActor() { context().watch(child); receive(ReceiveBuilder. match(Terminated.class, t -> t.actor().equals(child), t -> { … // handle termination }).build() ); } }
  • Monitor through Death Watch X public class WatchActor extends AbstractActor { final ActorRef child = context().actorOf(Props.empty(), "child"); ! public WatchActor() { context().watch(child); receive(ReceiveBuilder. match(Terminated.class, t -> t.actor().equals(child), t -> { … // handle termination }).build() ); } } Create a child actor
  • Monitor through Death Watch X public class WatchActor extends AbstractActor { final ActorRef child = context().actorOf(Props.empty(), "child"); ! public WatchActor() { context().watch(child); receive(ReceiveBuilder. match(Terminated.class, t -> t.actor().equals(child), t -> { … // handle termination }).build() ); } } Create a child actor Watch it
  • Monitor through Death Watch X public class WatchActor extends AbstractActor { final ActorRef child = context().actorOf(Props.empty(), "child"); ! public WatchActor() { context().watch(child); receive(ReceiveBuilder. match(Terminated.class, t -> t.actor().equals(child), t -> { … // handle termination }).build() ); } } Create a child actor Watch it Handle termination message
  • 4. SUPERVISE 29 Every single actor has a default supervisor strategy. Which is usually sufficient. But it can be overridden.
  • 4. SUPERVISE 29 Every single actor has a default supervisor strategy. Which is usually sufficient. But it can be overridden. class Supervisor extends Actor { override val supervisorStrategy = OneForOneStrategy(maxNrOfRetries = 10, withinTimeRange = 1 minute) { case _: ArithmeticException => Resume case _: NullPointerException => Restart case _: Exception => Escalate } ! val worker = context.actorOf(Props[Worker], name = "worker") ! def receive = {
  • 4. SUPERVISE 29 class Supervisor extends Actor { override val supervisorStrategy = OneForOneStrategy(maxNrOfRetries = 10, withinTimeRange = 1 minute) { case _: ArithmeticException => Resume case _: NullPointerException => Restart case _: Exception => Escalate } ! val worker = context.actorOf(Props[Worker], name = "worker") ! def receive = { case n: Int => worker forward n } } !
  • Cleanup & (Re)initialization 30 class Worker extends Actor { ... override def preRestart( reason: Throwable, message: Option[Any]) { ... // clean up before restart } override def postRestart(reason: Throwable) { ... // init after restart } }
  • Monitor through Death Watch 31 class Watcher extends Actor { val child = context.actorOf(Props.empty, "child") context.watch(child) ! def receive = { case Terminated(`child`) => … // handle child termination } }
  • Monitor through Death Watch 31 Create a child actor class Watcher extends Actor { val child = context.actorOf(Props.empty, "child") context.watch(child) ! def receive = { case Terminated(`child`) => … // handle child termination } }
  • Monitor through Death Watch 31 Create a child actor Watch it class Watcher extends Actor { val child = context.actorOf(Props.empty, "child") context.watch(child) ! def receive = { case Terminated(`child`) => … // handle child termination } }
  • Monitor through Death Watch 31 Create a child actor Watch it class Watcher extends Actor { val child = context.actorOf(Props.empty, "child") context.watch(child) Handle termination message ! def receive = { case Terminated(`child`) => … // handle child termination } }
  • Reactive applications scale up and down to meet demand.
  • Elastic • Elasticity and Scalability to embrace the Cloud • Adaptive Scale on Demand • Clustered servers support joining and leaving of nodes • More cost-efficient utilization of hardware 33 “Our traffic can increase by as much as 100x for 15 minutes each day. Until a couple of years ago, noon was a stressful time. Nowadays, it’s usually a non-event.” Eric Bowman, VP Architecture, Gilt Groupe
  • 34 Scale UP Scale OUT
  • 34 Essentially the same thing
  • 35 We need to 1. Minimize Contention 2. Maximize Locality of Reference
  • 36 Share NOTHING Design
  • Fully event-driven apps are a necessity X Amdahl’s Law will hunt you down
  • Define a router ActorRef router = context().actorOf( new RoundRobinPool(5).props(Props.create(Worker.class)), “router”) X
  • Define a router 37 val router = context.actorOf( RoundRobinPool(5).props(Props[Worker])), “router”)
  • …or from config 38 akka.actor.deployment { /service/router { router = round-robin-pool resizer { lower-bound = 12 upper-bound = 15 } } }
  • Turn on clustering 39 akka { actor { provider = "akka.cluster.ClusterActorRefProvider" ... } cluster { seed-nodes = [ “akka.tcp://ClusterSystem@127.0.0.1:2551", “akka.tcp://ClusterSystem@127.0.0.1:2552" ] auto-down = off } }
  • Use clustered routers 40 akka.actor.deployment { /service/master { router = consistent-­‐hashing-­‐pool nr-­‐of-­‐instances = 100 ! cluster { enabled = on max-nr-of-instances-per-node = 3 allow-­‐local-­‐routees = on use-­‐role = compute } } }
  • Use clustered routers 40 Or perhaps use an AdaptiveLoadBalancingPool akka.actor.deployment { /service/master { router = consistent-­‐hashing-­‐pool nr-­‐of-­‐instances = 100 ! cluster { enabled = on max-nr-of-instances-per-node = 3 allow-­‐local-­‐routees = on use-­‐role = compute } } }
  • Use clustered pub-sub 41
  • Use clustered pub-sub 41 class Subscriber extends Actor { val mediator = DistributedPubSubExtension(context.system).mediator mediator ! Subscribe(“content”, self) def receive = { … } }
  • Use clustered pub-sub 41 class Publisher extends Actor { val mediator = DistributedPubSubExtension(context.system).mediator def receive = { case in: String => mediator ! Publish("content", in.toUpperCase) } }
  • • Cluster Membership • Cluster Pub/Sub • Cluster Leader • Clustered Singleton • Cluster Roles • Cluster Sharding 42 Other Akka Cluster features
  • • Supports two different models: • Command Sourcing • Event Sourcing • Great for implementing • durable actors • replication • CQRS etc. • Messages persisted to Journal and replayed on restart 43 Use Akka Persistence
  • X Command Sourcing Event Sourcing
  • X Command Sourcing Event Sourcing write-ahead-log
  • X Command Sourcing Event Sourcing write-ahead-log derive events from a command
  • X Command Sourcing Event Sourcing write-ahead-log derive events from a command same behavior during recovery as normal operation
  • X Command Sourcing Event Sourcing write-ahead-log derive events from a command same behavior during recovery as normal operation only state-changing behavior during recovery
  • X Command Sourcing Event Sourcing write-ahead-log derive events from a command same behavior during recovery as normal operation only state-changing behavior during recovery persisted before validation
  • X Command Sourcing Event Sourcing write-ahead-log derive events from a command same behavior during recovery as normal operation only state-changing behavior during recovery persisted before validation events cannot fail
  • X Command Sourcing Event Sourcing write-ahead-log derive events from a command same behavior during recovery as normal operation only state-changing behavior during recovery persisted before validation events cannot fail allows retroactive changes to the business logic
  • X Command Sourcing Event Sourcing write-ahead-log derive events from a command same behavior during recovery as normal operation only state-changing behavior during recovery persisted before validation events cannot fail allows retroactive changes to the business logic fixing the business logic will not affect persisted events
  • X Command Sourcing Event Sourcing write-ahead-log derive events from a command same behavior during recovery as normal operation only state-changing behavior during recovery persisted before validation events cannot fail allows retroactive changes to the business logic fixing the business logic will not affect persisted events naming: represent intent, imperative
  • X Command Sourcing Event Sourcing write-ahead-log derive events from a command same behavior during recovery as normal operation only state-changing behavior during recovery persisted before validation events cannot fail allows retroactive changes to the business logic fixing the business logic will not affect persisted events naming: represent intent, imperative naming: things that have completed, verbs in past tense
  • Domain Events • Things that have completed, facts • Immutable • Verbs in past tense Akka Persistence Webinar • CustomerRelocated • CargoShipped • InvoiceSent “State transitions are an important part of our problem space and should be modeled within our domain.” Greg Young, 2008
  • Life beyond Distributed Transactions: an Apostate’s Opinion Position Paper by Pat Helland http://www-­‐db.cs.wisc.edu/cidr/cidr2007/papers/cidr07p15.pdf “In general, application developers simply do not implement large scalable applications assuming distributed transactions.” Pat Helland Akka Persistence Webinar
  • Consistency boundary • An Actor is can define an Aggregate Root • Each containing one or more Entities • Aggregate Root is the Transactional Boundary • Strong consistency within an Aggregate • Eventual consistency between Aggregates • No limit to scalability Akka Persistence Webinar
  • DEMO TIME Persist a game of ping pong
  • http://reactivemanifesto.org
  • Typesafe Activator http://typesafe.com/platform/getstarted
  • • Purely asynchronous and non-blocking web frameworks • No container required, no inherent bottlenecks in session management 48 Typesafe Reactive Platform • Actors are asynchronous and communicate via message passing • Supervision and clustering in support of fault tolerance • Asynchronous and immutable programming constructs • Composable abstractions enabling simpler concurrency and parallelism
  • Reactive is being adopted across a wide range of industries.
  • 50 Finance Internet/Social Media Mfg/Hardware Government Retail
  • Questions?
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