Go Reactive: Building Responsive, Resilient, Elastic & Message-Driven Systems

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Jonas Bonér CTO Typesafe @jboner Go Reactive Building Responsive, Resilient, Elastic & Message-Driven Systems

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The rules of the game have changed

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3 Yesterday Today

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3 Yesterday Today Single machines Clusters of machines

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3 Yesterday Today Single machines Clusters of machines Single core processors Multicore processors

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3 Yesterday Today Single machines Clusters of machines Single core processors Multicore processors Expensive RAM Cheap RAM

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3 Yesterday Today Single machines Clusters of machines Single core processors Multicore processors Expensive RAM Cheap RAM Expensive disk Cheap disk

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3 Yesterday Today Single machines Clusters of machines Single core processors Multicore processors Expensive RAM Cheap RAM Expensive disk Cheap disk Slow networks Fast networks

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3 Yesterday Today 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

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Reactive “Readily responsive to a stimulus” - Merriam Webster

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Reactive Applications The Principles of Reactive Systems 6

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http://reactivemanifesto.org

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Responsive “Quick to respond or react appropriately” - Merriam Webster

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9 The system should always be responsive

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9 1. Blue skies 2. Heavy load 3. Failures The system should always be responsive

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Resilient “The ability of a substance or object to spring back into shape” “The capacity to recover quickly from difﬁculties” - Merriam Webster

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Think Vending Machine

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Coffee Machine Programmer Think Vending Machine

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Coffee Machine Programmer Inserts coins Think Vending Machine

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Coffee Machine Programmer Inserts coins Add more coins Think Vending Machine

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Coffee Machine Programmer Inserts coins Gets coffee Add more coins Think Vending Machine

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Coffee Machine Programmer Think Vending Machine

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Coffee Machine Programmer Inserts coins Think Vending Machine

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Coffee Machine Programmer Inserts coins Think Vending Machine Out of coffee beans error

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Coffee Machine Programmer Inserts coins Think Vending Machine Out of coffee beans error WRONG

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Coffee Machine Programmer Inserts coins Think Vending Machine

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Coffee Machine Programmer Inserts coins Out of coffee beans failure Think Vending Machine

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Coffee Machine Programmer Service Guy Inserts coins Out of coffee beans failure Think Vending Machine

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Coffee Machine Programmer Service Guy Inserts coins Out of coffee beans failure Adds more beans Think Vending Machine

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Coffee Machine Programmer Service Guy Inserts coins Gets coffee Out of coffee beans failure Adds more beans Think Vending Machine

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The Right Way Service Client

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The Right Way Service Client Request

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The Right Way Service Client Request Response

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The Right Way Service Client Request Response Validation Error

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The Right Way Service Client Request Response Validation Error Application Failure

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The Right Way Service Client Supervisor Request Response Validation Error Application Failure

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The Right Way Service Client Supervisor Request Response Validation Error Application Failure Manages Failure

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Resilience Is By Design

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1. Isolate the failure 2. Compartmentalize 3. Manage failure locally 4. Avoid cascading failures Use Bulkheads

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1. Isolate the failure 2. Compartmentalize 3. Manage failure locally 4. Avoid cascading failures Use Bulkheads

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Enter Supervision

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A B Bar Foo C B E A D C Automatic and mandatory supervision Supervisor hierarchies

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A B Bar Foo C E A D C Automatic and mandatory supervision Supervisor hierarchies B

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19 Every single actor has a default supervisor strategy. Which is usually suﬀicient. But it can be overridden. Supervision in Akka

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19 class Supervisor extends AbstractActor { private SupervisorStrategy strategy = new OneForOneStrategy( 10, Duration.create(1, TimeUnit.MINUTES), DirectiveBuilder. match(ArithmeticException.class, e -> resume()). match(NullPointerException.class, e -> restart()). matchAny( e -> escalate()). build()); … // rest of actor omitted } } Supervision in Akka

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Resilience requires a Message-Driven Architecture

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Elastic “Capable of ready change or easy expansion or contraction” - Merriam Webster

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UP Scale

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UP Scale and down

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1. Minimize Contention 2. Maximize Locality of Reference 23 We need to

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Common points of Application Physical contention

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25 GO

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Async 25 GO

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26 Never ever

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26 Never ever

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Block 26 Never ever

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27 NOTHING share

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28 Needs to be async and non-blocking all the way down…

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28 Needs to be async and non-blocking all the way down…

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29 Single Writer Principle

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29 Single Writer Principle IO device Producers SERIAL & CONTENDED

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29 Single Writer Principle IO device Producers SERIAL & CONTENDED IO device Producers Actor or Queue BATCHED & UNCONTENDED

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The Role of Immutable State 30

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The Role of Immutable State 30

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The Role of Immutable State • Great to represent facts • Messages and Events • Database snapshots • Representing the succession of time 30

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The Role of Immutable State • Great to represent facts • Messages and Events • Database snapshots • Representing the succession of time • Mutable State is ok if local and contained • Allows Single-threaded processing • Allows single writer principle • Feels more natural • Publish the results to the world as Immutable State 30

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Divide & Conquer 31

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32 Pipelining

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ON DEMAND 33 scale

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OUT Scale

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OUT Scale and in

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• Mobile • Cloud Services, REST etc. • NOSQL DBs • Big Data 35 Distributed Computing is the new normal

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What is the essence of distributed systems? 36

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What is the essence of distributed systems? To try to overcome that 1. Information travels at the speed of light 2. Independent things fail independently 36

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Slow node Dead node No diﬀerence 37 and a Between a

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The network is 38

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The network is 38 http://aphyr.com/posts/288-the-network-is-reliable Inherently Unreliable

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39 Graveyard of distributed systems

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39 Graveyard of distributed systems • Distributed Shared Mutable State • EVIL (where N is number of nodes) N

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39 Graveyard of distributed systems • Distributed Shared Mutable State • EVIL (where N is number of nodes) N • Serializable Distributed Transactions

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39 Graveyard of distributed systems • Distributed Shared Mutable State • EVIL (where N is number of nodes) N • Serializable Distributed Transactions • Synchronous RPC

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39 Graveyard of distributed systems • Distributed Shared Mutable State • EVIL (where N is number of nodes) N • Serializable Distributed Transactions • Synchronous RPC • Guaranteed Delivery

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39 Graveyard of distributed systems • Distributed Shared Mutable State • EVIL (where N is number of nodes) N • Serializable Distributed Transactions • Synchronous RPC • Guaranteed Delivery • Distributed Objects • “Sucks like an inverted hurricane” - Martin Fowler

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Instead 40

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Embrace the Network Instead 40 and be done with it Use Asynchronous Message Passing

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TRANSPARENCY 41 location

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42 Scaling Up and Out is essentially the same thing

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Elasticity requires a Message-Driven Architecture

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Asynchronous Message-Passing is the enabler

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45 Typesafe Reactive Platform • Actors are lightweight, isolated and and communicate via asynchronous message passing • Supervision and clustering in support of fault tolerance • Purely asynchronous and non-blocking web framework • No container required, no inherent bottlenecks in session management • Asynchronous and immutable programming constructs • Composable abstractions enabling simpler concurrency and parallelism

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Typesafe Activator http://typesafe.com/platform/getstarted

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47 Finance Internet/Social Media Mfg/Hardware Government Retail

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Jonas Bonér CTO Typesafe @jboner Go Reactive Building Responsive, Resilient, Elastic & Message-Driven Systems