Holly Cummins Senior Principal Software Engineer, quarkus Cloud Builders Java Conf November 20, 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 1 local deploy 1 cup of tea

@holly_cummins #RedHat 2015 “please do not make unfavourable tea analogies in your writing.” 1 local deploy 1 cup of tea

@holly_cummins #RedHat 2022

@holly_cummins #RedHat 2011 microservices

@holly_cummins #RedHat 2013 containers (almost) change everything

@holly_cummins #RedHat 2013 containers (almost) change everything

@holly_cummins #RedHat 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 node.js node.js node.js node.js node.js node.js node.js 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 node.js node.js node.js node.js node.js node.js node.js 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 in the cloud, apps get started and stopped often

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

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

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

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

uh, can we do better than that?

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enter … quarkus

an open source stack to write java apps quarkus

@holly_cummins #RedHat traditional cloud-native java stack traditional cloud-native java stack traditional cloud-native java stack traditional cloud-native java stack node.js node.js node.js node.js node.js node.js node.js go go machine go go go go go go go go go go go go go go go go go go go quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus spoiler: we did better :) container orchestration machine machine machine https:/ /developers.redhat.com/blog/2017/03/14/java-inside-docker/

@holly_cummins #RedHat machine quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus container orchestration machine 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

@holly_cummins #RedHat machine quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus quarkus container orchestration machine 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 (but quarkus on jvm is also way smaller than traditional java)

do quarkus applications start faster? quarkus + graalvm 0.014 Seconds REST quarkus + open jdk 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 target/code-with-quarkus-1.0.0-SNAPSHOT-runner

do quarkus native applications start faster than lightbulbs?

do quarkus native 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?

@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 runtime build time

@ @ > doing more up-front enables better devex @ @ > build time runtime runtime build time we can do cool code introspections here that would be too expensive and annoying to do at runtime

to the code! @holly_cummins #RedHat

@holly_cummins #RedHat mvn quarkus:dev zero-config live coding

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

@holly_cummins #RedHat developer UI

@holly_cummins #RedHat 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

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

@holly_cummins #RedHat more opinions, less boilerplate

@holly_cummins #RedHat package com.example; import org.jboss.logging.Logger; public class MyService { private static final Logger log = Logger.getLogger(MyService.class); public void doSomething() { log.info("It works!"); } } example: logging

@holly_cummins #RedHat package com.example; import org.jboss.logging.Logger; public class MyService { private static final Logger log = Logger.getLogger(MyService.class); public void doSomething() { log.info("It works!"); } } example: logging import io.quarkus.logging.Log; Log

@holly_cummins #RedHat example: query parameters public String hello(@QueryParam("name") String name) {

@holly_cummins #RedHat example: query parameters public String hello(@RestQuery String name) {

@holly_cummins #RedHat 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 example: declaring an application

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

@holly_cummins #RedHat 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 example: panache + hibernate

@holly_cummins #RedHat 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 int port = 8081; ClientInterceptor[] interceptors = new ClientInterceptor[3]; interceptors[0] = new EventLoopBlockingCheckInterceptor(); interceptors[1] = new IOThreadClientInterceptor(); interceptors[2] = new StorkMeasuringGrpcInterceptor(); // etc Channel channel = ManagedChannelBuilder .forAddress(“localhost", port) .usePlaintext() .build(); GreeterGrpc.GreeterStub greeter = GreeterGrpc .newStub(channel) .withInterceptors(interceptors); example: gRPC

@holly_cummins #RedHat example: gRPC @GrpcClient Greeter greeter;

@holly_cummins #RedHat magic optional

@holly_cummins #RedHat the old ways all still work magic optional

@holly_cummins #RedHat the old ways all still work but you don’t have to type all the stuff unless you want to magic optional

@holly_cummins #RedHat 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

ok but we use kotlin

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@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 门 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

slides Holly Cummins Red Hat