SpringOne2GX 2014 Day 1 Keynote: Platform Reinvented

Unless otherwise indicated, these slides are © 2013-2014 Pivotal Software, Inc. and licensed under a

Creative Commons Attribution-NonCommercial l icense: http://creativecommons.org/licenses/by-nc/3.0/



Day 1 Keynote: Platform Reinvented

Hugh Williams, Juergen Hoeller, Dave Syer, Andy Glover, Graeme Rocher



Spring IO Platform Reprise

2

Jobs, Steps,

Readers, Writers

Ingestion, Export,

Orchestration, Hadoop

Controllers, REST,

WebSocket

Channels, Adapters,

Filters, Transformers

WEB INTEGRATION BATCH BIG DATA

SPRING CORE

FRAMEWORK SECURITY GROOVY REACTOR

DATA

RELATIONAL

DATA ACCESS

NON-RELATIONAL

DATA ACCESS

BOOT

Bootable, Minimal, Ops-Ready

GRAILS Full-stack,

Web

XD Stream, Taps,

Jobs

IO EXECUTION

IO FOUNDATION



Spring IO Platform

3

Grails

Spring IO Platform Distribution

Spring XD

Spring Foundation

Apps

3rd Party Dependencies

Spring Boot



Spring IO Platform Distribution Roadmap

4

2.0 1.0 1.1

June 2014

Spring 4.0 baseline

Nov 2014

Spring 4.1 baseline

1H 2015

12 months - major

Current: 1.0.2

6 months - minor



Spring IO Execution: Spring Boot

• Execution layer: eliminate boilerplate

configuration

• Spring Boot 1.1.x Released

• 88 contributors

• Foundation for all Spring IO Execution

Layer DSRs

5



Spring IO Execution: Spring Boot

6

@RestController

class App {

@RequestMapping('/')

def home() {

"""

<html><body>Message: 'Hello World!’</body></html>

"""

}

}



Demo:



Spring Boot

7



Spring Boot Sessions

8

TUE 8:30 AM Inside spring.io: a Production Spring Reference Application

TUE 10:30 AM Booting up Spring Social

TUE 2:30 PM Spring Boot for the Web Tier

TUE 4:30 PM Making Spring Boot Even Groovier

WED 10:30 AM "Bootiful" Applications with Spring Boot

THU 8:30 AM Micro Service Architecture with Spring Boot and Groovy

WED 12:45 PM Panel: Real World Boot-up Sequences


Creative Commons Attribution-NonCommercial l icense: http://creativecommons.org/licenses/by-nc/3.0/ 9



Ten Years

Ago!



Competitive Advantage



Velocity is the Killer App









Velocity

on the JVM

is the Killer App



Spring IO and Microservices

• “Microservices” are not a free lunch

• Fortunately, many common problems have boilerplate solutions

• Spring is all about removing boilerplate:

• Foundation: business logic (Spring Framework, Spring Data, Reactor, etc.)

• Execution: configuration and runtime (Spring Boot, Spring XD, Grails)

• Coordination: patterns in distributed systems (Spring Cloud Components)



Spring IO Platform

18

Grails

Spring IO Platform Distribution

Spring XD

Spring Foundation

Apps


Spring Boot

Spring Cloud



Spring IO Platform: Coordination

19

Jobs, Steps,

Readers, Writers

Ingestion, Export,


Controllers, REST,

WebSocket

Channels, Adapters,



SPRING CORE


DATA

RELATIONAL

DATA ACCESS

NON-RELATIONAL

DATA ACCESS

BOOT


GRAILS Full-stack,

Web

XD Stream, Taps,

Jobs

IO EXECUTION

IO FOUNDATION

IO COORDINATION SPRING CLOUD



Spring IO Core: Groovy Update

• What’s new in Groovy 2.3

• Java 8 support

• Traits

• Templating

• What’s coming in Groovy 2.4

• Android support

• New documentation

• New website

20



Groovy 2.3 : Java 8 support

• Supports Java 8 runtime (not syntax)

• Use closures where you would use Java 8 lambdas

21

Java 8 Groovy

Integer youngest = persons.stream()

.filter(p -> p.getAge() > 18)

.map(Person::getAge)

.min(Comparator.<Integer>naturalOrder())

.get()

def youngest = persons.stream()

.filter { it.age > 18 }

.map { it.age }

.min { a,b -> a<=>b }

.get()



Groovy 2.3: Traits

• Composition of behaviors

with traits

• Favors composition over

inheritance

• Compatible with

@CompileStatic

• Callable from Java

22

trait Flying {

void fly() { println "I'm flying!" }

}

trait Speaking {

void speak() { println "I'm speaking!" }

}

class SpeakingDuck implements Flying,

Speaking {

void quack() { println "I'm quacking!" }

void speak() { prinln quack() }

}

def duck = new SpeakingDuck()

duck.fly()

duck.quack()



Groovy 2.3: New Template Engine

• MarkupTemplateEngine

• Primarily aimed at XML-like contents

• Builder syntax, Layouts and Type Checking

• Supported in Spring 4.1 and Spring Boot

23

@Controller @RequestMapping("/person") class PersonController { @RequestMapping("list") def list() { new ModelAndView( 'views/person/list', [persons: Person.list()] ) }}

ul { persons.each { person -> li { a(href: "/person/$person.id", "$person.lastName $person.firstName") } } }



Groovy 2.4 : Android Support

• Develop a full Android application in Groovy

• Gradle plugin

24



Groovy Housekeeping

• Shiny new website

• Statically generated

• New documentation

25

POWERED BY ASCIIDOCTOR



Spring IO Execution: Grails Update

• Grails 2.4

• Current release 2.4.3

• Ongoing maintenance

• 1150 Plugins!

• What’s coming in Grails 3.0

• Complete rewrite

26



Spring IO Execution: Grails 3.0 on Boot

• Grails 3.0 built on Spring Boot

• Spring IO Execution Layer

• Full support for Micro Services

• Traditional, Fat JAR and

embedded deployment

• Native Gradle and Maven support

• Ground up rewrite

27



Spring IO Execution: Grails 3.0 Goals

• Plugin Model / Event Driven

• Multi Project Builds

• Microservices

• App Profiles: Netty, Servlet, Batch etc.

• Remove Bloat

• Reduce Dependencies

• Allow scaling from micro to modular monolith

28



Spring IO Execution: Grails 3.0 Plugins

29

Gra

ils.s

h

Sta

tic v

oid

ma

in

Gra

dle

Bu

ild

Forked Grails Runtime

test-app

shell run-app

console

Codegen

Plugins Build Time

Plugins

Runtime

Plugins



Spring IO Execution: Grails Microservices

30

@Grab("com.h2database:h2:1.3.173")

import grails.persistence.*

@Entity

@Resource(uri='/books')

class Book {

String title

}



Demo:



Grails 3.0

31



Groovy and Grails Sessions

32

TUE 8:30 AM Groovy in 2014 and beyond

TUE 10:30 AM Grails 3.0 Preview

TUE 12:45 PM Groovy, in the light of Java 8

TUE 2:30 PM Rethinking API Design with Traits

WED 8:30 AM Microservices Architecture with Grails

WED 2:30 PM Ratpack & Grails 3.0





Day 2 Keynote: Platform Reinvented

Juergen Hoeller, Mark Fisher, Dave Syer, Jon Brisbin

33



Spring IO Platform

34

Jobs, Steps,

Readers, Writers

Ingestion, Export,


Controllers, REST,

WebSocket

Channels, Adapters,



SPRING CORE


DATA

RELATIONAL

DATA ACCESS

NON-RELATIONAL

DATA ACCESS

BOOT


GRAILS Full-stack,

Web

XD Stream, Taps,

Jobs

IO EXECUTION

IO FOUNDATION

IO COORDINATION SPRING CLOUD



Spring IO Core: Spring Framework 4.1 GA

• Annotated JMS listener methods

• Comprehensive support for JCache (JSR-107) annotations

• Flexible resolution and transformation of static web resources

• MVC views: declarative resolution + Groovy markup templates

• Performance: SpEL compiler mode + concurrency fine-tuning

35



Spring 4.1: Annotated JMS listener methods

36

@Component

public class MyService {

@JmsListener(destination = "myQueue")

public void processOrder(Order order, @Header("order_type") String type) {

...

}

}



Spring 4.1: Support for JCache annotations

37

@Component

public class MyService {

@CacheResult(cacheName = "book")

public Book findBook(@CacheKey ISBN isbn, boolean checkWarehouse) {

...

}

}



Spring 4.1: Flexible web resource handling

• Flexible resource resolution chain:path resolution, caching,

compression, versioning

• Flexible resource transformation chain:CSS links, caching,

HTML5 AppCache manifests

• Talk: “Resource Handling in Spring MVC 4.1”

by Brian Clozel and Rossen Stoyanchev - Wednesday 8:30

• Showcase: https://github.com/bclozel/spring-resource-handling

38



Spring 4.1: Declarative MVC view resolution

39

@Configuration

@EnableWebMvc

public class WebConfig extends WebMvcConfigurerAdapter {

public void configureViewResolvers(ViewResolverRegistry registry) {

registry.enableContentNegotiation(new MappingJackson2JsonView());

registry.freeMarker().cache(false);

}

}



Spring 4.1: Many further improvements...

• Java 8's Optional for injection points and MVC handler

parameters

• Annotated @Lookup methods with support for method arguments

• Direct field binding support with auto-growing for nested fields

• WebSocket scope, SockJS client support, WebSocket stats

• Declarative SQL scripts and programmatic transactions for tests

40



Spring XD – Big Data, Little Time

41



Spring XD: Unified Platform for Big Data

42

Spring XD Runtime

BIDIRECTIONAL

Compute

HDFS

RDBMS

NoSQL

R, SAS

Streams Jobs

ingest workflow

export

taps

Predictive Modelling

>_

Redis



Spring XD: Quality of Service

• High Availability

• Cluster Management built upon ZooKeeper

• Leader Election for Admin Nodes

• Module Redeployment across Container Nodes

• Customizable Deployment

• Module Count and Criteria Properties

• Data Partitioning by Key (with SpEL support)

• Direct Binding for Co-located Modules (reduce network IO)

43



Demo Domain: Smart Grid Data

44

http://www.cse.iitb.ac.in/debs2014 *

Inspired by ACM DEBS 2014 Grand Challenge* Demonstrate the applicability of event-based systems to provide scalable, real-time analytics over high volume sensor data to compute load forecasting.

Field Name Description

ID Unique ID of the measurement

Timestamp Number of seconds since epoch

Load Load in watts

House ID The house where the plug is located

Household ID The household inside the house

Plug ID The unique ID of the smart plug



Demo Domain: Smart Grid Data

45

Field Name Description

ID Unique ID of the measurement

Timestamp Number of seconds since epoch

Load Load in watts

House ID The house where the plug is located

Household ID The household inside the house

Plug ID The unique ID of the smart plug

Inspired by ACM DEBS 2014 Grand Challenge* Demonstrate the applicability of event-based systems to provide scalable, real-time analytics over high volume sensor data to compute load forecasting.



Demo Objectives

• Predictive models for energy consumption demand

• generated via R and exported as PMML

• Ingesting household meter data to HDFS via HTTP

• partitioning based on House ID

• Real-time data filtering and enrichment

• Real-time model scoring

• performed via Spring XD’s analytics-pmml processor module

• Real-time computed data aggregation

• Asynchronous UI updates

46



Demo Topology

47

XD Admin

Zoo Keeper Zoo Keeper Zoo Keeper

Load

Balancer Generator

XD Container

HTTP

XD Container

HTTP

XD Container

HDFS

XD Container

HDFS

XD Container

HDFS Redis

Rabbit MQ

Hadoop



Demo:



Spring XD

48



Looking Ahead

• Programming Model • Further Unification of the Batch and Stream Models

• Reactive Streams Support

• Developer Experience • Support for Java Config and Spring Integration DSLs

• Spring Boot-based Module Deployment and Packaging

• Deployment Targets • Spring XD as a PCF service

• Spring XD on Docker

• Spring XD on Mesos

• Quality of Service • Batching and Compression via Message Bus Interceptors

• Comprehensive Security Model

49



Spring XD Sessions

50

TUE 2:30 PM Develop powerful Big Data Applications easily with Spring XD

TUE 4:30 PM Spring XD - A Guided Tour

WED 10:30 AM Building a Recommendation Engine with Spring and Hadoop

WED 2:30 PM IoT Realized - The Connected Car

THU 10:30 AM Spring XD for Real-time Hadoop Workload Analysis

THU 12:45 PM Implementing the Lambda Architecture with Spring XD



Spring IO Platform

51

Grails

Spring IO Platform

Spring XD

Spring Foundation

Apps

Spring Cloud


Spring Boot



No Man (Microservice) is an Island

It's excellent to be able to implement a microservice really easily

(Spring Boot), but building a system that way surfaces

"non-functional" requirements that you otherwise didn't have.

There are laws of physics that make some problems unsolvable

(consistency, latency), but brittleness and manageability can be

addressed with generic, boiler plate patterns.

52



Emergent features of micro-service systems

Coordination of distributed systems leads to boiler plate patterns

• Distributed/versioned configuration

• Service registration and discovery

• Routing

• Service-to-service calls

• Load balancing

• Circuit Breaker

• Asynchronous

• Distributed messaging

53



Spring Cloud Components

54

Client Bindings

Service

Discovery

Config

Server

Circuit

Breakers

Edge

Service

Intelligent

Router

Leader

Election

One-time

Tokens

Global

Locks

Cluster

State

Event Bus



Demo:



Spring Cloud

Components

55



Spring Cloud Components

• Common features of distributed systems developed by users as

Spring Boot apps

• Highly configurable and customizable

• Always do something sensible out of the box

• Works nicely as standalone apps on developer box

• Easy migration to Cloud and PCF

56



Spring Cloud Sessions

57

TUE 4:30 PM Security for Microservices with Spring and OAuth2

WED 12:45 PM Simplify Cloud Applications using Spring Cloud

WED 12:45 PM Spring Cloud, Spring Boot and Netflix OSS

WED 2:30 PM Developing Microservices for PaaS with Spring and Cloud Foundry



Demo:



Reactor

58



Spring IO Core: Reactor

• Microservices proliferate in modern architectures

• No Microservice is an Island

• More Microservices === More Runtime Resources required

• More More Runtime Resources required === More $$$

• Microservices have acute need for efficiency

• Contrary to myth: Runtime Resources aren’t free/cheap

• Microservices are natural fit for Reactive Architecture

59




• What is Reactive Programming?

• Event-driven

• Modular

• Scalable

• Highly-available

• Non-blocking/async

o Blocking IO (BIO) is expensive

o Non-blocking IO (NIO) is more efficient

o NIO means async patterns, which can be hard

60



Reactive Architecture

• Reactive is usually Asynchronous

• Asynchronous !== Concurrent

• Non-blocking versus Blocking (usually IO)

• Provides Isolation

• Resource usage

• Failure

• Events are replayable

• Reactive can be complex

• Too low-level for most end users



Reactor

Spring IO: Components → Reactor

62

Task Queue

Micro

Service

Micro

Service

Micro

Service

Micro

Service

Event

Event Event



Reactive Stream Contributors

63

ccv

Doug Lea – SUNY Oswego




What is Reactive Streams?

64

“...provide a standard for asynchronous stream processing with

non-blocking backpressure.”

github.com/reactive-streams/reactive-streams

Available as a library

org.reactivestreams:reactive-streams:0.4.0.M2




• Reactive Streams API

• Publisher

• Subscriber

• Subscription

• Reactor’s Stream API implements Reactive Streams standard

65



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