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October 7, 2022 Cloud Native Development with Quarkus Holly Cummins Red Hat @holly_cummins

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hi!

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@holly_cummins #RedHat how today works: 08:00: Registration and breakfast 
 09:00: Masterclass starts 
 10:30-10:45: Coffee break 
 12:00-13:00: Lunch 
 14:30-14:45: Coffee break 
 16:00: Masterclass ends

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@holly_cummins #RedHat how today works: • Quark-what? • How to be cloud native • The test pyramid and beyond • TDD with Quarkus • Writing a Quarkus REST application • Persistence with Hibernate and Panache • Microservices with Quarkus • Contract testing • JWT and Keycloak • Deciding between native and Java compilation • Deploying Quarkus apps to Kubernetes • Troubleshooting + observability • Q&A + wrap up + retrospective

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@holly_cummins #RedHat how today works: • I do • We do • You do

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@holly_cummins #RedHat how today works: • I do • We do • You do • I talk

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@holly_cummins #RedHat who are you? • what’s your name? • who do you work for? • what’s your role? • what’s in your tech stack?

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@holly_cummins #RedHat background check! spring boot?

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@holly_cummins #RedHat https://developers.redhat.com/e-books/quarkus-spring-developers

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@holly_cummins #RedHat background check! cdi?

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@holly_cummins #RedHat background check!

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@holly_cummins #RedHat background check! cloud?

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@holly_cummins #RedHat background check! cloud? kubernetes?

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@holly_cummins #RedHat interest check! test-driven-development?

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@holly_cummins #RedHat background check! quarkus?

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@holly_cummins #RedHat interest check! test-driven-development?

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@holly_cummins #RedHat background check! reactive?

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@holly_cummins #RedHat interest check! reactive?

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@holly_cummins #RedHat background check! native?

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@holly_cummins #RedHat interest check! native?

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@holly_cummins #RedHat background check! quarkus?

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quark-what?

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@holly_cummins #RedHat advantages of quarkus?

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@holly_cummins #RedHat disadvantages of quarkus?

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$18,000 Sun Sparc App Server Box (4 CPUs, 2GB of RAM) + $60,000 BEA Weblogic + $92,000 Sun Sparc DB Server Box (8 CPUs) + $243,000 Oracle RDBMS + $50,000 Symantec Visual Café for 10 developers -------------------------------------------------- $463,000 (capex) + ~$80,000 annual maint (opex) Cost of a Java-based Web App circa 1999

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Historical Enterprise Java Stack Operating System + Hardware/VM Java Virtual Machine (Hotspot) Application Server App App App App App Dynamic Application Frameworks Architecture: Monoliths 
 
 Deployment: multi-app, 
 appserver App Lifecycle: Months Memory: 1GB+ RAM Startup Time: 10s of sec

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2000 RED HAT LINUX 2007 KVM 2009 DEVOPS

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Modern Enterprise Java Stack Java Virtual Machine (Hotspot) Application Server App Dynamic Application Frameworks Architecture: Microservices 
 
 Deployment: Single App 
 
 App Lifecycle: Days Memory: 100 MB + RAM Startup Time: Seconds No Change QUARKUS WORKSHOP

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Quarkus - Optimizing the Stack Java Virtual Machine (Hotspot) App (Imperative / Reactive) Optimized Application Frameworks Architecture: Microservices, 
 Serverless 
 
 Deployment: Single App 
 
 App Lifecycle: Minutes/Days Memory: 10 MBs + RAM Startup Time: Milliseconds Optional QUARKUS WORKSHOP

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Source: https://newrelic.com/resources/ebooks/serverless-benchmark-report-aws-lambda-2020 Languages used on AWS Lambda 38% 6% Node.js 51% Python Java

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Designed for Throughput

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Designed for Throughput At the expense of footprint

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Designed to be long-running

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Designed to be long-running At the expense of startup speed

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Rich dynamic behavior built for mutable systems

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Rich dynamic behavior built for mutable systems Yet containers are primarily immutable

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An Open Source stack to write Java apps Cloud Native Microservices Serverless

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Kubernetes-Native Development with Quarkus Solid Foundation Java consistently ranks in the Top 3 of programming languages in use today with a community of 7-10 million developers. Stunning Performance Optimized to provide native-level memory footprint and startup time, allowing for increased density, performance and elasticity at lower cost. Toolchain End-to-end toolchain including OpenShift Developer Console, Code Ready Workspaces, project generators in IDE and web, live- reload for lightning fast inner loop workflow, and CI/CD integration. Community Massive catalog of extensions connects your applications with best of breed-technologies including Camel, Jaeger, Prometheus, Istio, Kafka and more. TIOBE : #1 IEEE : #1 SlashData : #2 RedMonk : #2

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Quarkus Brings Real Developer Joy A cohesive platform for optimized developer joy: ● Based on standards, but not limited ● Unified configuration ● Reactive & Imperative, all in one ● Zero config, live reload in the blink of an eye ● Streamlined code for the 80% common usages, flexible for the 20% ● No hassle native executable generation

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Quarkus + GraalVM 13 MB Quarkus + OpenJDK 74 MB Traditional Cloud-Native Stack 140 MB REST https://quarkus.io/blog/runtime-performance/ Quarkus Improves Memory Utilization

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Quarkus Improves Startup Time Quarkus + GraalVM 0.014 Seconds REST REST + CRUD Quarkus + OpenJDK 0.75 Seconds Quarkus + GraalVM 0.055 Seconds Quarkus + OpenJDK 2.5 Seconds Traditional Cloud-Native Stack 9.5 Seconds Traditional Cloud-Native Stack 4.3 Seconds https://quarkus.io/blog/runtime-performance/

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Quarkus Unifies Imperative and Reactive ● Combines both Reactive and imperative development in the same application ● Reactive Messaging - Apache Kafka, MQTT, AMQP… ● Reactive Services @Inject SayService say; @GET @Produces(MediaType.TEXT_PLAIN) public String hello() { return say.hello(); } @Inject @Stream(”kafka”) Publisher reactiveSay; @GET @Produces(MediaType.SERVER_SENT_EVENTS) public Publisher stream() { return reactiveSay; }

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Quarkus uses Best of Breed Frameworks & Standards Eclipse Vert.x Hibernate RESTEasy Apache Camel Eclipse MicroProfile Netty Kubernetes OpenShift Jaeger Prometheus Apache Kafka Infinispan Flyway Neo4j MongoDB MQTT KeyCloak Apache Tika

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40 They load way too many classes They are way too dynamic / reflective They perform a lot of initialization at Runtime What is Wrong with Java Frameworks

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@
 @ > Packaging
 (maven, gradle…) Build Time Runtime How does a framework start?

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@
 @ > Load and parse config files, properties, yaml, xml, etc. Build Time Runtime How does a framework start?

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@
 @ > Classpath scanning and annotation discovery Attempt to load class to enable/disable features Build Time Runtime How does a framework start?

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@
 @ > Build its metamodel of the world. Build Time Runtime How does a framework start?

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@
 @ > Start thread pools, IO, etc. Build Time Runtime How does a framework start?

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Do the work once, not at each start Get rid of all bootstrap classes Less time to start, less memory needed Less or no reflection nor dynamic proxies What if we Initialize at Build time?

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@
 @ > Build Time Do the work once, not at each start Get rid of all bootstrap classes Less time to start, less memory needed Less or no reflection nor dynamic proxies What if we Initialize at Build time?

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@
 @ > Runtime Build Time Do the work once, not at each start Get rid of all bootstrap classes Less time to start, less memory needed Less or no reflection nor dynamic proxies What if we Initialize at Build time?

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The Quarkus Way enables Native compilation Native @
 @ > JV M Build Time

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The Traditional vs. Quarkus Ways @
 @ > Build Time Runtime

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@
 @ > The Traditional vs. Quarkus Ways @
 @ > Build Time Runtime Build Time

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@
 @ > The Traditional vs. Quarkus Ways @
 @ > Build Time Runtime Runtime Build Time

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demo

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@holly_cummins #RedHat a note on the localization

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https://hollycummins.com/quarkus-workshops/ to the code!

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how to be cloud native

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@holly_cummins #RedHat what is cloud native?

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@holly_cummins #RedHat what is cloud native?

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@holly_cummins #RedHat containers?

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@holly_cummins #RedHat microservices?

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@holly_cummins #RedHat Capabilities of a Cloud Native Application Architectures? The benefits of cloud native application architectures enable speed of development and deployment, flexibility, quality, and reliability. More importantly, it allows developers to integrate the applications with the latest open source technologies without a steep learning curve. While there are many ways to build and architect cloud native applications following are some great ingredients for consideration: • Runtimes - More likely to be written in the container first or/and Kubernetes native language, which means runtimes such as Java, Node.js, Go, Python, and Ruby, etc. • Security - Deploying and maintaining applications in a multi cloud, hybrid cloud application environment, security becomes of utmost importance and should be part of the environment. • Observability - The ability to observer applications and their behavior in the cloud. Tools that can give realtime metrics, and more information about the use e.g., Prometheus, Grafana, Kiali, etc. • Efficiency - Focused on tiny memory footprint, small artifact size, and fast booting time to make portable applications across hybrid/multi-cloud platforms. Primarily, it will leverage an expected spice in production via rapid scaling with consuming minimal computing resources. • Interoperability - Easy to integrate cloud native apps with the latest open source technologies such as Infinispan, MicroProfile, Hibernate, Apache Kafka, Jaeger, Prometheus, and more for building standard runtimes architecture. • DevOps/DevSecOps - Designed for continuous deployment to production in line with the minimum viable product (MVP), with security as part of the tooling together with development, automating testing, and collaboration.

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@holly_cummins #RedHat Capabilities of a Cloud Native Application Architectures? The benefits of cloud native application architectures enable speed of development and deployment, flexibility, quality, and reliability. More importantly, it allows developers to integrate the applications with the latest open source technologies without a steep learning curve. While there are many ways to build and architect cloud native applications following are some great ingredients for consideration: • Runtimes - More likely to be written in the container first or/and Kubernetes native language, which means runtimes such as Java, Node.js, Go, Python, and Ruby, etc. • Security - Deploying and maintaining applications in a multi cloud, hybrid cloud application environment, security becomes of utmost importance and should be part of the environment. • Observability - The ability to observer applications and their behavior in the cloud. Tools that can give realtime metrics, and more information about the use e.g., Prometheus, Grafana, Kiali, etc. • Efficiency - Focused on tiny memory footprint, small artifact size, and fast booting time to make portable applications across hybrid/multi-cloud platforms. Primarily, it will leverage an expected spice in production via rapid scaling with consuming minimal computing resources. • Interoperability - Easy to integrate cloud native apps with the latest open source technologies such as Infinispan, MicroProfile, Hibernate, Apache Kafka, Jaeger, Prometheus, and more for building standard runtimes architecture. • DevOps/DevSecOps - Designed for continuous deployment to production in line with the minimum viable product (MVP), with security as part of the tooling together with development, automating testing, and collaboration. lots of words

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@holly_cummins #RedHat rapid release cadence

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@holly_cummins #RedHat independently deployable microservices

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@holly_cummins #RedHat how do you know if you’re decoupled?

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can you deploy independently? v5.1.4 v5.1.4 v5.1.4 v5.1.4

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can you deploy independently? v6.2.8 v65.7 v5.1.4 v1.0.5

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@holly_cummins #RedHat can you deploy at all?

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@holly_cummins #RedHat confidence allows releasing automation allows confidence

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@holly_cummins #RedHat cloud native is culture, not containers - or runtimes

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TDD with Quarkus

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@holly_cummins #RedHat TDD

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@holly_cummins #RedHat TDD: improves quality

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@holly_cummins #RedHat TDD: an excellent design tool

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@holly_cummins #RedHat

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@holly_cummins #RedHat the real reason to do TDD:

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@holly_cummins #RedHat the real reason to do TDD:

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@holly_cummins #RedHat the real reason to do TDD: gamified testing

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@holly_cummins #RedHat the first module has TDD instructions the rest do not challenge in each module, scroll forward, find the tests, and work backwards.!

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the test pyramid and beyond

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@holly_cummins #RedHat the test pyramid

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@holly_cummins #RedHat the test pyramid (you can TDD at every level)

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@holly_cummins #RedHat the test pyramid

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@holly_cummins #RedHat the test pyramid end-to-end tests

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@holly_cummins #RedHat the test pyramid end-to-end tests integration tests

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@holly_cummins #RedHat the test pyramid end-to-end tests unit tests integration tests

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@holly_cummins #RedHat the test pyramid end-to-end tests unit tests integration tests low effort

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@holly_cummins #RedHat the test pyramid end-to-end tests unit tests integration tests low effort high realism

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@holly_cummins #RedHat the test pyramid end-to-end tests unit tests integration tests low effort high realism high value

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@holly_cummins #RedHat all models are wrong some are useful

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@holly_cummins #RedHat tools evolve end-to-end tests unit tests integration tests low effort high realism

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@holly_cummins #RedHat tools evolve end-to-end tests unit tests integration tests low effort high realism tests with application server

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@holly_cummins #RedHat tools evolve end-to-end tests unit tests integration tests low effort high realism tests with application server test REST endpoints

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@holly_cummins #RedHat tools evolve end-to-end tests unit tests integration tests low effort high realism tests with application server test REST endpoints

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writing a Quarkus REST application

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@holly_cummins #RedHat https:/ /hollycummins.com/quarkus-workshops/#rest

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persistence with hibernate and panache

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79 @Entity public class Todo extends PanacheEntity { // id is inherited public String title; public boolean completed; public String url; @Column(name = "ordering") public int order; public static List search(String query) { return list("completed = ?1 and title like ?2", false, query); } public static List findNotCompleted() { return list("completed", false); } public static long deleteCompleted() { return delete("completed", true); } } Define entity with Panache

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80 @GET public List getAll() { return Todo.listAll(Sort.by("order")); } @POST @Transactional public void addTodo(@Valid Todo todo) { return todo.persist(); } @GET @Path("/search/{query}") public List search(@PathParam("query") @NotBlank String query) { return Todo.search(query); } Accessing entities with Panache Convenient methods for lazy people (aka good devs)

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@holly_cummins #RedHat https:/ /hollycummins.com/quarkus-workshops/#rest-transaction-orm

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reactive programming

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@holly_cummins #RedHat quarkus supports both blocking and reactive • it easier to become blocking on a reactive core than to become non- blocking on a blocking core

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@holly_cummins #RedHat background check! node.js?

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@holly_cummins #RedHat Uni • returning a Uni makes a method non- blocking* • a Uni is like a node.js promise • Unis mix nicely with lamdas for chaining • you can mix blocking and non-blocking in an application, but be careful how finely you mix * there are limitations - you can get some subtle bugs!

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@holly_cummins #RedHat https:/ /hollycummins.com/quarkus-workshops/#reactive

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microservices with Quarkus

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@holly_cummins #RedHat https:/ /hollycummins.com/quarkus-workshops/#microservices

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contract testing

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@holly_cummins #RedHat the limitations of unit tests “why do my colleagues tell me my code is broken, even though my unit tests all pass?”

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@holly_cummins #RedHat their code our code why unit tests aren’t enough

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@holly_cummins #RedHat their code our code why mocks aren’t enough

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@holly_cummins #RedHat their code our code why stubs aren’t enough

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@holly_cummins #RedHat our code our mock why mocks aren’t enough

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@holly_cummins #RedHat our code our mock tests ✔ why mocks aren’t enough

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@holly_cummins #RedHat our code our mock our code their actual code tests ✔ why mocks aren’t enough

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@holly_cummins #RedHat our code our mock our code their actual code tests ✔ reality ✘ why mocks aren’t enough

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@holly_cummins #RedHat our code their code why mocks aren’t enough

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@holly_cummins #RedHat our code their code contract test why mocks aren’t enough

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@holly_cummins #RedHat our code their code contract test mock why mocks aren’t enough

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@holly_cummins #RedHat our code their code contract test mock functional test why mocks aren’t enough

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@holly_cummins #RedHat our code their code contract test mock functional test our tests ✔ their tests ✔ reality ✔ why mocks aren’t enough

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@holly_cummins #RedHat our code their code contract test mock functional test why mocks aren’t enough

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@holly_cummins #RedHat our code their code contract test mock functional test our tests ✔ their tests ✘ reality ✘ why mocks aren’t enough

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@holly_cummins #RedHat our code their code contract test mock functional test why mocks aren’t enough

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@holly_cummins #RedHat our code their code contract test mock functional test our tests ✘ their tests ✔ reality ✘ why mocks aren’t enough

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@holly_cummins #RedHat

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@holly_cummins #RedHat contract-first is a great way to TDD

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@holly_cummins #RedHat contract-first is a great way to TDD (and a great design tool)

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#RedHat @holly_cummins • consumer-driven contract testing can save your bacon • pact is a mock for the consumer • pact is a functional test for the producer • shared json contracts aligns expectations across services

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@holly_cummins #RedHat pitfalls of contract testing: • we have to talk to the other team • our consumers can break our CI?! • versions • pact is hard to grok • testing the mock • but I’ve invested in wiremock • duplicated tests is overhead

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@holly_cummins #RedHat contract testing options: • pact.io • spring contract • OpenAPI schema validation + mock generation • prism • schemathesis

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@holly_cummins #RedHat pact can exercise • input parameters • state

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@holly_cummins #RedHat the story of the 204

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@holly_cummins #RedHat https:/ /hollycummins.com/quarkus-workshops/#contract-testing

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deciding between native and java compilation

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@holly_cummins #RedHat use case for native • low workload (so throughput isn’t the bottleneck) • resource-constrained or old hardware (especially memory) • high re-deploy rate (applications never get warmed up before being spun down) • serverless (of course) 
 use case for JVM • high workload (you need lots of throughput) • long-lived processes (the rapid start of native doesn’t save you much over the lifetime) • stable workload or very little elasticity in underlying orchestration is native better?

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@holly_cummins #RedHat is there a sustainability aspect? yes … and it’s just as depend-y! optimising • cost • application performance will also be optimising carbon

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@holly_cummins #RedHat native vs JVM is not an either-or • consider hybrid deployment models • a strength of Quarkus is application code is the same for native and JVM

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deploying Quarkus apps to Kubernetes

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@holly_cummins #RedHat • Kubernetes extension • uses dekorate under the covers • OpenShiftExtension • s2i

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@holly_cummins #RedHat • Kubernetes extension • uses dekorate under the covers • OpenShiftExtension • s2i

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… so in conclusion

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@holly_cummins #RedHat what did we all think?

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Customers using Quarkus Today “We could run 3 times denser deployments without sacrificing availability and response times of service” “When you adopt Quarkus, you will be productive from day one since you don’t really need to learn new technologies.” “Quarkus seemed to provide the performance boost we needed while at the same time having a good backer (Red Hat) and relying on battle- tested technologies” Thorsten Pohl Lufthansa Technik AVIATAR Product Owner Automation & Platform Architect Roberto Cortez Talkdesk Principal Architect Christos Sotiriou DXL technical lead at Vodafone Greece

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@holly_cummins #RedHat https:/ /delawen.com/2022/07/bungee-jumping-into-quarkus/ the gotchas

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@holly_cummins #RedHat

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Continue your Journey code.quarkus.io red.ht/try-quarkus red.ht/idc-quarkus-study

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thank you @holly_cummins https://hollycummins.com/cloud-native-quarkus-workshop-goto-copenhagen/