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Holly Cummins Senior Principal Software Engineer, Quarkus GOTO Amsterdam June 27, 2023 @[email protected] faster greener happier why quarkus should be your next tech stack

@holly_cummins #RedHat let’s remember how computers used to be

@holly_cummins #RedHat let’s remember how computers used to be 1832

@holly_cummins #RedHat on-prem dedicated hardware long-lived processes 2005

@holly_cummins #RedHat 2015 “please do not make unfavourable tea analogies in your writing.”

@holly_cummins #RedHat 2022

@holly_cummins #RedHat #GOTOams 2011 microservices

@holly_cummins #RedHat #GOTOams 2013 containers (almost) change everything

@holly_cummins #RedHat #GOTOams 2013 containers (almost) change everything

@holly_cummins #RedHat #GOTOams java apps run on the cloud, but have they really adapted to cloud?

@holly_cummins #RedHat Container platform um … no machine Go Go Go Go Go Go Go Go Go Go Go Go Go Go

@holly_cummins #RedHat Container platform um … no machine NodeJS NodeJS NodeJS NodeJS NodeJS NodeJS NodeJS machine Go Go Go Go Go Go Go Go Go Go Go Go Go Go

@holly_cummins #RedHat Container platform um … no machine HotSpot Heap HotSpot Heap HotSpot Heap HotSpot Heap machine NodeJS NodeJS NodeJS NodeJS NodeJS NodeJS NodeJS machine Go Go Go Go Go Go Go Go Go Go Go Go Go Go

@holly_cummins #RedHat

@holly_cummins #RedHat “I can’t bring up the microservices in my Java dev stack

@holly_cummins #RedHat “I can’t bring up the microservices in my Java dev stack … on my brand new Apple laptop with a M1 chip and 64GB of RAM.” - fintech developer

@holly_cummins #RedHat #GOTOams in the cloud, apps get started and stopped often

@holly_cummins #RedHat #GOTOams in the cloud, apps get started and stopped often

@holly_cummins #RedHat #GOTOams java servers are not very much like light switches

@holly_cummins #RedHat #GOTOams java servers are not very much like light switches

@holly_cummins #RedHat #GOTOams java servers are not very much like light switches (historically)

uh, can we do better than that?

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enter … quarkus

@holly_cummins #RedHat spoiler: we did better :) CONTAINER ORCHESTRATION Machine Machine Traditional Cloud-Native Java Stack Traditional Cloud-Native Java Stack Traditional Cloud-Native Java Stack Traditional Cloud-Native Java Stack Machine NodeJS NodeJS NodeJS NodeJS NodeJS NodeJS NodeJS Go Go Go Go Go Go Go Go Go Go Go Go Go Go Go Go Go Go Go Go Go Machine Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus https:/ /developers.redhat.com/blog/2017/03/14/java-inside-docker/

@holly_cummins #RedHat Container orchestration Node Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Quarkus Node Traditional Cloud-Native Java Stack Traditional Cloud-Native Java Stack Traditional Cloud-Native Java Stack Traditional Cloud-Native Java Stack … a lot better quarkus native

an open source stack to write java apps quarkus

an open source stack to write java apps quarkus

@holly_cummins #RedHat #GOTOams so, did we adapt to the cloud?

do quarkus applications start faster? Quarkus + GraalVM 0.014 Seconds REST Quarkus + OpenJDK 0.75 Seconds Traditional Cloud-Native Stack 4.3 Seconds https://quarkus.io/blog/runtime-performance/

@holly_cummins to the code! demo!

@holly_cummins #RedHat mvn quarkus:build -Pnative -DskipTests target/code-with-quarkus-1.0.0-SNAPSHOT-runner

do quarkus applications start faster than lightbulbs?

do quarkus applications start faster than lightbulbs? ridiculously, yes

ok but does startup time matter?

ok but does startup time matter? fast boot time means auto-scaling works better more resilience to load spikes

Quarkus + GraalVM 13 MB Quarkus + OpenJDK 74 MB Traditional Cloud-Native Stack 140 MB rest application https://quarkus.io/blog/runtime-performance/ does quarkus improve memory utilization?

#Quarkus @holly_cummins

#Quarkus @holly_cummins hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus?

#Quarkus @holly_cummins hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus? uhh … are you supposed to shut down applications after using them?

#Quarkus @holly_cummins hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus? hey, wanna see quarkus? uhh … are you supposed to shut down applications after using them? 120 instances (!)

in the cloud, memory footprint matters

in the cloud, memory footprint matters

do quarkus applications have higher throughput? https://www.redhat.com/en/resources/mi-quarkus-lab-validation-idc-analyst-paper

do quarkus applications have higher throughput? 48 concurrent connections https://www.redhat.com/en/resources/mi-quarkus-lab-validation-idc-analyst-paper

do quarkus applications have higher throughput? 48 concurrent connections quarkus native 3212 req/s https://www.redhat.com/en/resources/mi-quarkus-lab-validation-idc-analyst-paper

do quarkus applications have higher throughput? 48 concurrent connections traditional cloud native stack 3555 req/s quarkus native 3212 req/s https://www.redhat.com/en/resources/mi-quarkus-lab-validation-idc-analyst-paper

do quarkus applications have higher throughput? 48 concurrent connections traditional cloud native stack 3555 req/s quarkus on jvm 6389 req/s quarkus native 3212 req/s https://www.redhat.com/en/resources/mi-quarkus-lab-validation-idc-analyst-paper

@holly_cummins #RedHat https://medium.com/arconsis/spring-boot-vs-quarkus-part-2-jvm-runtime-performance-af45d0db116e

@holly_cummins #RedHat https://medium.com/arconsis/spring-boot-vs-quarkus-part-2-jvm-runtime-performance-af45d0db116e spring boot quarkus response time 1901 ms 294 ms throughput 523 req/s 3374 req/s

#Quarkus @holly_cummins users care (a lot) about response time

better startup better footprint better throughput wait, isn’t that something for nothing?

@holly_cummins #RedHat the two ways of improving performance •trade off one thing against another •eliminate waste

traditional cloud native stack 3555 req/s quarkus on jvm 6389 req/s quarkus native 3212 req/s https://www.redhat.com/en/resources/mi-quarkus-lab-validation-idc-analyst-paper

traditional cloud native stack 3555 req/s quarkus on jvm 6389 req/s quarkus native 3212 req/s https://www.redhat.com/en/resources/mi-quarkus-lab-validation-idc-analyst-paper a trade-off of throughput against footprint

traditional cloud native stack 3555 req/s quarkus on jvm 6389 req/s quarkus native 3212 req/s https://www.redhat.com/en/resources/mi-quarkus-lab-validation-idc-analyst-paper no trade-off, just better :) a trade-off of throughput against footprint

@holly_cummins #RedHat where the win comes from 1832

@holly_cummins #RedHat 2010 multiple applications share a single application server instance application re-deployed many times between server restarts application dependencies changed while it is running

@holly_cummins #RedHat application frameworks optimised for dynamism

@holly_cummins #RedHat application frameworks optimised for dynamism dynamism has a cost

@holly_cummins #RedHat cloud apps are immutable now

@holly_cummins #RedHat cloud apps are immutable now

@holly_cummins #RedHat cloud apps are immutable now

@holly_cummins #RedHat cloud apps are immutable now

@holly_cummins #RedHat cloud apps are immutable now

@holly_cummins #RedHat cloud apps are immutable now

@holly_cummins #RedHat a highly dynamic runtime in a container is pointless

@holly_cummins #RedHat a highly dynamic runtime in a container is pointless loading classes that aren’t needed

@holly_cummins #RedHat a highly dynamic runtime in a container is pointless loading classes that aren’t needed expensive, slow, reflection

@holly_cummins #RedHat a highly dynamic runtime in a container is pointless loading classes that aren’t needed expensive, slow, reflection the same initialisation on every startup

@holly_cummins #RedHat how does a framework start? @ 
 @ > packaging 
 (maven, gradle…) build time runtime

@holly_cummins #RedHat @ 
 @ > load and parse config files, properties, yaml, xml, etc. Build Time Runtime how does a framework start?

@holly_cummins #RedHat @ 
 @ > • classpath scanning and annotation discovery • attempt to load class to enable/disable features Build Time Runtime how does a framework start?

@holly_cummins #RedHat @ 
 @ > build a metamodel of the world Build Time Runtime How does a framework start? how does a framework start?

@holly_cummins #RedHat @ 
 @ > start thread pools, I/O, etc. Build Time Runtime how does a framework start?

@holly_cummins #RedHat what if we initialize at build time?

@holly_cummins #RedHat @ 
 @ > build time what if we initialize at build time?

@holly_cummins #RedHat @ 
 @ > runtime build time what if we initialize at build time?

@holly_cummins #RedHat quarkus makes a “closed-world” assumption

@holly_cummins #RedHat the quarkus way enables native compilation native (graalvm) @ 
 @ > jvm build time

ok but is performance all there is?

ok but is performance all there is? developer joy

@holly_cummins #RedHat

doing more up-front enables better devex @ 
 @ > build time runtime

@ 
 @ > doing more up-front enables better devex @ 
 @ > build time runtime build time

@ 
 @ > doing more up-front enables better devex @ 
 @ > build time runtime runtime build time

to the code! @holly_cummins #RedHat

@holly_cummins #RedHat #GOTOams zero-config live coding

@holly_cummins #RedHat #GOTOams tests are run on every code change “reverse code coverage” means only relevant tests run continuous testing

@holly_cummins #RedHat #GOTOams developer UI

@holly_cummins #RedHat #GOTOams zero-config testcontainers

@holly_cummins #RedHat testcontainers integration … without quarkus @TestConfiguration(proxyBeanMethods = false) public class ContainersConfig { @Bean @ServiceConnection public PostgreSQLContainer> postgres() { return new PostgreSQLContainer<>(DockerImageName.parse("postgres:14")); } } public class TestApplication { public static void main(String[] args) { SpringApplication .from(MySpringDataApplication::main) .with(ContainersConfig.class) .run(args); } } @Import(ContainersConfig.class)

@holly_cummins #RedHat testcontainers integration … without quarkus @TestConfiguration(proxyBeanMethods = false) public class ContainersConfig { @Bean @ServiceConnection public PostgreSQLContainer> postgres() { return new PostgreSQLContainer<>(DockerImageName.parse("postgres:14")); } } public class TestApplication { public static void main(String[] args) { SpringApplication .from(MySpringDataApplication::main) .with(ContainersConfig.class) .run(args); } }

@holly_cummins #RedHat testcontainers integration … without quarkus

@holly_cummins #RedHat zero-config testcontainers integration the only thing you need to do to make testcontainers work is not configure anything # configure your datasource quarkus.datasource.db-kind = postgresql quarkus.datasource.username = sarah quarkus.datasource.password = connor quarkus.datasource.jdbc.url = jdbc:postgresql://localhost:5432/mydatabase # drop and create the database at startup quarkus.hibernate-orm.database.generation = drop-and-create

@holly_cummins #RedHat zero-config testcontainers integration the only thing you need to do to make testcontainers work is not configure anything # drop and create the database at startup quarkus.hibernate-orm.database.generation = drop-and-create

@holly_cummins #RedHat zero-config testcontainers integration the only thing you need to do to make testcontainers work is not configure anything

@holly_cummins #RedHat zero-config testcontainers integration the only thing you need to do to make testcontainers work is not configure anything quarkus also auto-invokes flyway and liquibase

@holly_cummins #RedHat zero-config testcontainers integration realistically, use profiles so things work in production :) # configure your datasource %prod.quarkus.datasource.db-kind = postgresql %prod.quarkus.datasource.username = sarah %prod.quarkus.datasource.password = connor %prod.quarkus.datasource.jdbc.url = jdbc:postgresql://localhost:5432/mydatabase # on real databases, defaults to ‘none’, but let’s validate %prod.quarkus.hibernate-orm.database.generation = validate

@holly_cummins #RedHat #GOTOams • databases • redis • keycloak • kafka • elasticsearch • kubernetes • … or add your own auto-provision services “dev services” using testcontainers under the hood

@holly_cummins #RedHat #GOTOams more opinions, less boilerplate

@holly_cummins #RedHat #GOTOams package org.acme; import org.springframework.boot.SpringApplication; import org.springframework.boot.autoconfigure.SpringBootApplication; @SpringBootApplication public class SpringDemo { public static void main(String[] args) { SpringApplication.run(SpringDemo.class, args); } } example: declaring an application

@holly_cummins #RedHat #GOTOams example: declaring an application

@holly_cummins #RedHat #GOTOams @ApplicationScoped public class GreetingRepository { public Entity findByName(int name) { return find("name", name).firstResult(); } void persist(Entity entity) {} void delete(Entity entity) {} Entity findById(Id id) {} List list(String query, Sort sort, Object... params) { return null; } Stream stream(String query, Object... params) { return null; } long count() { return 0; } long count(String query, Object... params) { return 0; } } example: panache + hibernate

@holly_cummins #RedHat #GOTOams example: panache + hibernate @ApplicationScoped public class GreetingRepository implements PanacheRepository { public Entity findByName(int name) { return find("name", name).firstResult(); } }

@holly_cummins #RedHat #GOTOams DAO example: panache + hibernate @ApplicationScoped public class GreetingRepository implements PanacheRepository { public Entity findByName(int name) { return find("name", name).firstResult(); } } repository pattern

@holly_cummins #RedHat #GOTOams example: panache + hibernate

@holly_cummins #RedHat #GOTOams example: panache + hibernate active record pattern @Entity public class Greeting extends PanacheEntity { public String name; public LocalDate issued; @Version public int version; public static List getTodaysGreetings() { return list("date", LocalDate.now()); } }

@holly_cummins #RedHat #GOTOams io.quarkus quarkus-spring-web io.quarkus quarkus-spring-data-jpa ok but we use spring option 1: compatibility libraries option 2: migration tooling • migration toolkit for applications (mta) • windup • open rewrite

@holly_cummins #RedHat “After a week of development with Quarkus, I was able to regain the same level of productivity as when I was developing with Spring Boot.” – Fawaz Paraïso, Decathlon

@holly_cummins #RedHat open source community of contributors

@holly_cummins #RedHat Emiliia Nesterovych 
 Emmanuel Bernard 
 Emre Kaplan 
 Enrique González Martínez 
 Enrique Mingorance Cano 
 Eoin Gallinagh 
 Eric Deandrea 
 Eric Wittmann 
 Erik Åsén 
 Erik Mattheis 
 Erin Schnabel 
 Eugene Berman 
 Evan Shortiss 
 Fabricio Gregorio 
 faculbsz 
 Falko Modler 
 Fedor Dudinskiy 
 Felipe Carvalho dos Anjos Formentin 
 Felipe Henrique Gross Windmoller 
 Fernando Comunello 
 Fernando Henrique 
 fhavel 
 Fikru Mengesha 
 Filippe Spolti 
 Florian Beutel 
 Florian Bütler 
 Florian Heubeck 
 Florin Botis 
 Foivos Zakkak 
 Foobartender 
 Fouad Almalki 
 Francesco Nigro 
 Francisco Javier Tirado Sarti 
 Francois Steyn 
 Frank Eichfelder 
 franz1981 
 freakse-sa 
 Fred Bricon 
 Frédérc Blanc 
 Freeman Fang 
 Fu Cheng 
 Gabriele Cardosi 
 Galder Zamarreño 
 galiacheng 
 Gavin King 
 Gavin Ray 
 Geert Schuring 
 Geoffrey De Smet 
 Geoffrey GREBERT 
 Georg Leber 
 George Gastaldi 
 manofthepeace 
 Manyanda Chitimbo 
 Marat Gubaidullin 
 Marc Nuri 
 Marc Schlegel 
 Marc Wrobel 
 Marcel Hanser 
 Marcel Lohmann 
 Marcell Cruz 
 Marcelo Pereira 
 Marcin Czeczko 
 Marcin Kłopotek 
 Marco Bungart 
 Marco Schaub 
 Marco Yeung 
 Marco Zanghì 
 Marcus Paulo 
 Marek Goldmann 
 Marek Skacelik 
 Marián Macik 
 Mario Fusco 
 MarioHNogueira 
 Mark Lambert 
 Mark Little 
 Mark McLaughlin 
 Mark Sailes 
 marko-bekhta 
 Markus Heberling 
 Markus Himmel 
 Markus Schwer 
 Martin C. Richards 
 Martin Grammelspacher 
 Martin Kouba 
 Martin Muzikar 
 Martin Panzer 
 Martin Weiler 
 martin-kofoed-jyskebank-dk 
 MartinWitt 
 Marvin B. Lillehaug 
 masini 
 Matej Novotny 
 Matej Vasek 
 Matheus Cruz 
 Mathias Holzer 
 Matteo Mortari 
 Matthias Andreas Benkard 
 Matthias Cullmann 
 mauroal 
 Max Andersen 
 Max Gabrielsson 
 Max Rydahl Andersen 
 Victor Hugo de Oliveira Molinar 
 Vincent Sevel 
 Vincent van Dam 
 Vinícius Ferraz Campos Florentino 
 Viswa Teja Nariboina 
 Vladimir Konkov 
 Vojtech Juranek 
 Vratislav Hais 
 w.glanzer 
 Walter Medvedeo 
 Wayne Ellis 
 Werner Glanzer 
 Willem Jan Glerum 
 William Antônio Siqueira 
 Wim Goeman 
 Wippermueller, Frank 
 wojciech.stryjewski 
 Xavier 
 Xieshen 
 xstefank 
 Y. Luis 
 Yann-Thomas LE MOIGNE 
 Yannick Reifschneider 
 YassinHajaj 
 Yelzhas Suleimenov 
 yesunch9 
 Yoann Rodière 
 Yoshikazu Nojima 
 Youngmin Koo 
 Yubao Liu 
 yugoccp 
 Yukihiro Okada 
 Zaheed Beita 
 zanmagerl 
 zedbeit 
 Zheng Feng 
 Žiga Deisinger 
 Zineb Bendhiba 
 zohar 
 Zoran Regvart 
 Шумов Игорь Юрьевич 
 出⻔三不惹 open source community of contributors

@holly_cummins #RedHat one last thing …

@holly_cummins #RedHat does being faster and lighter mean quarkus is greener?

digression: how do you measure carbon?

@holly_cummins #RedHat step 1: measure power usage

@holly_cummins #RedHat step 1: measure power usage wall power measurement

@holly_cummins #RedHat step 1: measure power usage wall power measurement more complete

@holly_cummins #RedHat step 1: measure power usage wall power measurement more complete needs access to the wall

@holly_cummins #RedHat step 1: measure power usage wall power measurement more complete needs access to the wall and equipment

@holly_cummins #RedHat step 1: measure power usage wall power measurement more complete needs access to the wall and equipment RAPL

@holly_cummins #RedHat step 1: measure power usage wall power measurement more complete needs access to the wall and equipment RAPL programmatically accessible

@holly_cummins #RedHat step 1: measure power usage wall power measurement more complete needs access to the wall and equipment RAPL programmatically accessible misses some components

@holly_cummins #RedHat step 1: measure power usage wall power measurement more complete needs access to the wall and equipment data costs carbon RAPL programmatically accessible misses some components

@holly_cummins #RedHat

@holly_cummins #RedHat

@holly_cummins #RedHat

@holly_cummins #RedHat load

@holly_cummins #RedHat Source: Teads EC2 instances carbon dataset

@holly_cummins #RedHat density Source: Clement Escoffier experiment 1: cloud Setup: • 800 requests/second, over 20 days • SLA > 99% • AWS instances Assumptions: • Costs are for us-east-1 data centre

@holly_cummins #RedHat Setup: • 800 requests/second, over 20 days • SLA > 99% Assumptions: Source: Clement Escoffier x Teads cloud carbon impact of framework choice interpolated carbon metrics

@holly_cummins #RedHat Setup: • 800 requests/second, over 20 days • SLA > 99% Assumptions: Source: Clement Escoffier x Teads cloud carbon impact of framework choice the carbon is lower because the cost is lower interpolated carbon metrics

@holly_cummins #RedHat Setup: • REST + CRUD • large heap • RAPL energy measurement • multiple instances to support high load
 Assumptions: • US energy mix Source: John O’Hara experiment 2: RAPL measurements

@holly_cummins #RedHat Setup: • REST + CRUD • large heap • RAPL energy measurement • multiple instances to support high load
 Assumptions: • US energy mix Source: John O’Hara experiment 2: RAPL measurements quarkus on JVM has the lowest carbon … because it has the highest throughput

• quarkus cuts carbon by ~2-3x* • native consumes more carbon than JVM carbon measurements: conclusions

@holly_cummins #RedHat ok but is it being used in production?

@holly_cummins #RedHat “We can run 3 times denser deployments without sacrificing availability and response times of services. Quarkus live coding is a really good thing: Making changes and reloading pages instantaneously is a great feature.” – Fawaz Thorsten Pohl, Lufthansa AVIATAR

@holly_cummins #RedHat 2019: Moved digital experience to Quarkus (from Spring Boot) • Startup times 40s ➡ 12s • RAM 800 MB ➡ 360 MB • Developer productivity ⬆ 30-40% – Christos Sotiriou, Vodafone Greece

@holly_cummins #RedHat tl;dpa (too long didn’t pay attention) deployment density lower cloud bill frictionless development experience Medium Nano auto-provision services zero-config live coding continuous testing developer UI greener

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