Holly Cummins Senior Principal Software Engineer, Quarkus Voxxed Days Zurich March 7, 2024 @[email protected] faster greener happier why quarkus should be your next tech stack

@holly_cummins #RedHat

@holly_cummins #RedHat

@holly_cummins #RedHat software test cycle

@holly_cummins #RedHat software test cycle

@holly_cummins #RedHat software test cycle

@holly_cummins #RedHat software test cycle

@holly_cummins #RedHat software test cycle

@holly_cummins #RedHat software test cycle

@holly_cummins #RedHat software test cycle

@holly_cummins #RedHat software test cycle

@holly_cummins #RedHat software test cycle

@holly_cummins #RedHat

@holly_cummins #RedHat the problem:

@holly_cummins #RedHat tea: slow feedback loop→developers drink a lot of tea the problem:

@holly_cummins #RedHat 2010s-era java web frameworks are verbose there is a lot of typing

@holly_cummins #RedHat tea: slow feedback loop→developers drink a lot of tea the problems:

@holly_cummins #RedHat tea: slow feedback loop→developers drink a lot of tea the problems: typing: verbose programming model → repetitive boilerplate

@holly_cummins #RedHat tea: slow feedback loop→developers drink a lot of tea the problems: typing: verbose programming model → repetitive boilerplate tedium

@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 CTO

@holly_cummins #RedHat in production, it’s worse

@holly_cummins #RedHat in production, it’s worse

@holly_cummins #RedHat in production, it’s worse example microservices maths:

@holly_cummins #RedHat in production, it’s worse example microservices maths: airline maintenance scheduling system

@holly_cummins #RedHat in production, it’s worse example microservices maths: airline maintenance scheduling system single service: ½ core + 1 GB RAM

@holly_cummins #RedHat in production, it’s worse example microservices maths: airline maintenance scheduling system single service: ½ core + 1 GB RAM HA → 3x instances

@holly_cummins #RedHat in production, it’s worse example microservices maths: airline maintenance scheduling system single service: ½ core + 1 GB RAM HA → 3x instances ~100 microservices

@holly_cummins #RedHat in production, it’s worse example microservices maths: airline maintenance scheduling system single service: ½ core + 1 GB RAM HA → 3x instances ~100 microservices = 150 cores + 300 GB RAM

@holly_cummins #RedHat java was not designed for the cloud

@holly_cummins #RedHat Container platform machine go go go go go go go go go go go go go go

@holly_cummins #RedHat Container platform 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 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 all this resource usage is expensive

@holly_cummins #RedHat tea: slow feedback loop→developers drink a lot of tea the problems: typing: verbose programming model → repetitive boilerplate

@holly_cummins #RedHat tea: slow feedback loop→developers drink a lot of tea the problems: typing: verbose programming model → repetitive boilerplate treasure: high resource usage → cloud vendors get lots of money

@holly_cummins #RedHat why is this happening? mismatch between what we need and what the platform is optimised for

@holly_cummins #RedHat what old frameworks were optimised for

@holly_cummins #RedHat on-prem what old frameworks were optimised for

@holly_cummins #RedHat on-prem dedicated hardware what old frameworks were optimised for

@holly_cummins #RedHat on-prem dedicated hardware long-lived processes what old frameworks were optimised for

@holly_cummins #RedHat on-prem dedicated hardware long-lived processes deployment is an annual event what old frameworks were optimised for

@holly_cummins #RedHat on-prem dedicated hardware long-lived processes deployment is an annual event late-binding what old frameworks were optimised for

@holly_cummins #RedHat on-prem dedicated hardware long-lived processes deployment is an annual event late-binding re-configurable without restart what old frameworks were optimised for

can we do better than that?

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enter … 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 made stuff 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)

@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)

quarkus applications start fast quarkus + graalvm 0.014 Seconds rest application 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

faster than a lightbulb

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/ quarkus improves 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 (!)

ok but does memory footprint matter?

ok but does memory footprint matter? in the cloud, memory footprint is money

@holly_cummins #RedHat remember the airline scheduling application?

@holly_cummins #RedHat remember the airline scheduling application? “[With Quarkus], we can run 3 times denser deployments without sacrificing availability and response times of services. ” – Fawaz Thorsten Pohl

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

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

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

quarkus applications also 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

quarkus applications also 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

@holly_cummins #RedHat application frameworks were optimised for dynamism

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

@holly_cummins #RedHat paying a dynamism tax … even though the app is not dynamic

@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 java framework start?

@holly_cummins #RedHat how does a java framework start? build time

@holly_cummins #RedHat how does a java framework start? build time runtime

@holly_cummins #RedHat how does a java framework start? build time runtime

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

@holly_cummins #RedHat how does a java framework start? build time runtime

@holly_cummins #RedHat how does a java framework start? build time runtime

@holly_cummins #RedHat how does a java framework start? > build time runtime load and parse • config files • properties • yaml • xml • etc.

@holly_cummins #RedHat how does a java framework start? > build time runtime

@holly_cummins #RedHat how does a java framework start? @ @ > build time runtime • classpath scanning and annotation discovery • attempt to load class to enable/disable features

@holly_cummins #RedHat how does a java framework start? @ @ > build time runtime

@holly_cummins #RedHat how does a java framework start? @ @ > build time runtime build a metamodel of the world

@holly_cummins #RedHat how does a java framework start? @ @ > build time runtime

@holly_cummins #RedHat how does a java framework start? @ @ > build time runtime start • thread pools • I/O • etc.

@holly_cummins #RedHat how does a java framework start? @ @ > build time runtime ready to do work!

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

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

@holly_cummins #RedHat @ @ > build time runtime start • thread pools • I/O • etc. what if we initialize at build time?

@holly_cummins #RedHat @ @ > build time runtime ready to do work! start • thread pools • I/O • etc. 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

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

ok but we don’t need native

ok but we don’t need native quarkus is faster and smaller than legacy frameworks, even running on the jvm

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 runtime build time @ @ >

doing more up-front enables better devex 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

ok but we don’t need reactive

ok but we don’t need reactive quarkus is good at reactive, but it’s also very good at normal programming

ok but we don’t need reactive quarkus is good at reactive, but it’s also very good at normal programming most quarkus users do not use reactive

@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 ok but i don’t like magic

@holly_cummins #RedHat ok but i don’t like magic enrichment happens at build time

@holly_cummins #RedHat ok but i don’t like magic enrichment happens at build time no performance drag

@holly_cummins #RedHat ok but i still don’t like magic

@holly_cummins #RedHat the old ways all still work ok but i still don’t like magic

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

@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 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 RAPL

@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 another last thing …

@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

@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

@holly_cummins #RedHat tl;sdpa (too long still didn’t pay attention) what problems is quarkus solving? tea typing tedium taxes treasure

slides Holly Cummins Red Hat http://hollycummins.com/greener-faster-happier-quarkus-voxxed-zurich/