Streaming to a New Jakarta EE
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The document discusses the key insights from a survey of over 1800 developers regarding Jakarta EE, highlighting the need for better support for microservices, native Kubernetes integration, and faster innovation. It emphasizes the shift from monolithic applications to microservices architectures, detailing the challenges of consistency and data management in distributed systems. Additionally, it introduces reactive streams as a means to facilitate communication between services and mentions various projects and frameworks aimed at advancing cloud-native Java development.
Streaming to a New Jakarta EE
- 1. Streaming to a new Jakarta EE
- 2. @myfear
- 4. Jakarta EE Technical Directions Eclipse Foundation survey of over 1800 developers Top 3 Critical areas cited for improvement: 1. Better support for microservices 2. Native integration with Kubernetes 3. A faster pace of innovation Top Frameworks for building microservices include: Jersey, Spring, Eclipse MicroProfile, Node.js & Kubernetes 67% Currently building microservices or planning to <1 yr 40% Say large memory requirements most challenging aspect of working with Java EE #1 Reason Java EE chosen for Java applications is stability 60% Say Foundation should prioritize better support for microservices https://jakarta.ee/news/2018/04/24/jakarta-ee-community-survey/
- 5. 5 Oracle GlassFish 5.X Eclipse GlassFish 5.1 Eclipse GlassFish “Next” Java EE 8 Java EE 8 Jakarta EE 8 Sources, TCKs Jakarta EE Next High Level Roadmap for Jakarta EE
- 7. JakartaEE The New Home of Cloud Native Java https://www.youtube.com/watch?v=1Amshn3s-hg Ivar Grimstad (Cybercom Sweden) Dimitris Andreadis (Red Hat) Dmitry Kornilov (Oracle) Gaël Blondelle (Eclipse Foundation) Kevin Sutter (IBM) Markus Eisele (@lightbend ) Ondro Mihályi (Payara)
- 8. Monoliths have allowed us to take consistency for granted
- 9. With a single database, the world is easy Transactions give us an illusion of a single, consistent, current state • We can think of our data as a static thing • It sits there at rest, waiting for our operation • Failure is handled • No partial updates • Consistency is enforced • Concurrency is handled • No uncommitted reads Monoliths
- 11. In microservices, our consistent view of the world breaks down
- 12. Microservices Many databases, the world is hard There are now many states, all constantly changing • Different services have different ideas of current state • Our data is in motion, not at rest, not static • Failure is not handled for us • Partial updates likely • No enforcement of consistency • Concurrency is inherent • Operations take time to propagate
- 14. What worked in monoliths will not work in microservices
- 15. What worked in monoliths CRUD • Depends on consistent single state Relying on transactions • Depends on a single database REST • Depends on failure and consistency being handled in the database What worked in monoliths
- 16. What’s needed for microservices Events • Events convey facts • Facts remain true regardless of what else happens in the system At least once messaging • Ensures events can be reliably propagated throughout the system Stream-centric view • Our data is the events • Some may be at rest, some are in motion • No single state • Rather, system is constantly converging, propagating • Control this, using streams
- 17. Streams A B
- 18. By modelling a system using streams, we embrace events, no longer need a single state, and can take eventual consistency for granted
- 20. Reactive Streams Allows streaming between multiple technologies Not for end users, rather it’s the glue that connects things • Created by Lightbend and others (Netflix, Red Hat, etc. 2013) • Allows asynchronous propagation of messages, with asynchronous backpressure • Backpressure necessary to control resource usage • Tens of compatible, TCK verified implementations • Added to JDK9 as the java.util.concurrent.Flow API • Requires a high level API for end user control and manipulation of streams https://developer.lightbend.com/blog/2017-08-18-introduction-to-reactive-streams-for-java-developers/index.html
- 21. But there are already APIs for that?! • InputStream and OutputStream in the JDK • NIO Channel’s • Servlet 3.1 ReadListener and WriteListener extensions • JDBC ResultSet • JSR 356 @OnMessage annotations, • Message Driven Beans and JMS, • CDI events using @Observes • Java collection Stream and Iterator based APIs • JDK9 Flow API.
- 22. Reactive Streams 22 Kafka myTopic .subscribe() Akka Streams .map(kafkaMessage -> new WebSocketMessage( kafkaMessage.getPayload() ) ) WebSocket response .send(publisher) Reactive Streams Reactive Streams Messages Backpressure
- 23. https://developer.lightbend.com/blog/2018-02-06-reactive-streams-ee4j/index.html https://www.lightbend.com/blog/in-support-of-jakarta-ees-quest-to-accelerate-cloud-native-java What can Reactive Streams offer Jakarta EE?
- 24. MicroProfile Working with Reactive Streams requires a high level library like Akka Streams MicroProfile Reactive Streams Operators • Provides specification for a set of operators for Reactive Streams manipulation • map, filter, flatMap, etc. • Heavily draws on Akka Streams, RxJava 2 and Reactor • Uses java.util.stream for inspiration in naming and scope • 1.0-RC2 recently released • Long term hope is for inclusion in the JDK • Three implementations under active development https://github.com/eclipse/microprofile-reactive-streams
- 25. MicroProfile Reactive Messaging • API for connecting to common messaging sources • Kafka, AMQP, JMS, WebSockets • Based on MicroProfile Reactive Streams Operators • Uses annotations on CDI Beans to declare message subscribers and publishers • API and TCK currently under development • Two implementations being simultaneously developed • Aiming for inclusion in MicroProfile 2.2 https://github.com/eclipse/microprofile-reactive-messaging
- 27. Online Auction Demo app is an ebay clone. This technology doesn’t exist in a usable form yet, but… • Lagom, a Reactive Microservices framework, implements these principles • James Roper implemented support for the specs in their current state on top of Lagom • The online auction demo app has been ported to use the new specs
- 28. Summary • Monoliths have allowed us to take consistency for granted • In cloud native microservices, our consistent view of the world breaks down • What worked in monoliths will not work in microservices • By modelling a system using streams, we • Embrace events • No longer need a single state • Can take eventual consistency for granted • Lightbend is working with Eclipse MicroProfile to: • Build new specs for streaming • Make streaming architectures standard
- 29. Next Steps! Learn more! Project Site: http://www.microprofile.io Reactive Streams: http://www.reactive-streams.org Demo GitHub Repo: https://github.com/jroper/streaming-new-jakartaee
- 30. Wanna learn more about Streaming Architectures? http://bit.ly/fast-data-architecture
- 31. Written for architects and developers that must quickly gain a fundamental understanding of microservice-based architectures, this free O’Reilly report explores the journey from SOA to microservices, discusses approaches to dismantling your monolith, and reviews the key tenets of a Reactive microservice: • Isolate all the Things • Act Autonomously • Do One Thing, and Do It Well • Own Your State, Exclusively • Embrace Asynchronous Message-Passing • Stay Mobile, but Addressable • Collaborate as Systems to Solve Problems http://bit.ly/ReactiveMicroservice
- 32. The detailed example in this report is based on Lagom, a new framework that helps you follow the requirements for building distributed, reactive systems. • Get an overview of the Reactive Programming model and basic requirements for developing reactive microservices • Learn how to create base services, expose endpoints, and then connect them with a simple, web-based user interface • Understand how to deal with persistence, state, and clients • Use integration technologies to start a successful migration away from legacy systems http://bit.ly/DevelopReactiveMicroservice
- 33. http://bit.ly/SustainableEnterprise • Understand the challenges of starting a greenfield development vs tearing apart an existing brownfield application into services • Examine your business domain to see if microservices would be a good fit • Explore best practices for automation, high availability, data separation, and performance • Align your development teams around business capabilities and responsibilities • Inspect design patterns such as aggregator, proxy, pipeline, or shared resources to model service interactions