The document outlines the agenda for a workshop on 'event-sourced systems through reactive streams', including presentations and exercises focused on reactive programming and project reactor. It discusses the importance of reactive programming in addressing modern application challenges and introduces concepts like data pipelines, reactive streams, and event sourcing. Additionally, it highlights tools and frameworks like NATS and Project Reactor, emphasizing their role in creating scalable, resilient architectures.

1. Event-sourced system
through Reactive Streams
Workshop

2. Agenda
• 18:30 presentation introduction
• 19:00 exercise project reactor intro
• 19:30 short break
• 19:40 presentation event-sourcing
• 19:50 workshop
• 21:00 Closing & Networking

3. Reactive programming Belgium
R be

4. Reactive Programming Belgium
Your non-blocking resource in a reactive world
“We believe that RP is a good fit for
the challenges that
current applications/architectures entail”

5. Reactive Programming Belgium
Your non-blocking resource in a reactive world
• Research
• Share
• Blog
http://www.reactiveprogramming.be
• Meetups
https://www.meetup.com/Reactive-Programming-Belgium/
• Presentations
• ...

6. Reactive Programming Belgium
Your non-blocking resource in a reactive world
• Want to help?
• Writing articles (blog)
• Ideas/speakers/presenting…
• Prepare workshops
• Ad-hoc experiments
• ...

7. Reactive Programming Belgium
Your non-blocking resource in a reactive world
• Workshop :
‘Event-sourced system through Reactive Streams’

8. Reactive programming

9. Reactive programming
Applications today
• Applications today
• Increased magnitude of scale
• Big data (IoT, devices, …)
• Realtime
• Ex. Flight recorder
1 sec of flight = 1.5 TB of data
• Re-think the way we create applications

10. Reactive programming
Origin
• Origin @ Microsoft
• Erik Meijer
• Reactive programming framework (Reactive Extensions) for .NET

11. Reactive programming
Yet another programming model?
• Reactive
Something that responds to stimuli and actions
• Reactive Programming
• Rehashed programming model that emphasizes on scalability & response
• A way to build a scalable architecture that’s resilient and quick to react to
stimuli
• Ex. spreadsheet

12. Reactive programming
Data pipeline
• CRUD
• database -> function/process -> database
• Data pipeline
• data -> function -> data -> function -> data
• Data transformation instead of data manipulation

13. Reactive programming
Programming model – Reactive Streams
• Publisher (emit data)
• Subscriber (receive data)
• Subscription (~ session / context info)
• Processor
Flux.range(1, 10)
.filter(i -> isEven(i))
.map(i -> i * 2)
.subscribe(System.out::println);
Project reactor

14. Reactive programming
Programming model – Reactive Streams
• Publisher
onComplete()
onError()
next()

15. Reactive programming
Programming model – Reactive Streams
• Backpressure

16. Reactive programming
Programming model – Reactive Streams
• Java 9 Reactive Streams
• API (Publisher, Subscriber, Subscription, Processor)
= Reactive streams spec
• Frameworks/implementations
• RxJava (Netflix), project reactor, Akka-Streams, …
• RxJava 2
• Observable vs. Flowable >> both Publishers
• Project reactor
• Mono (0 - 1), flux (0 ..) >> both Publishers
• Reactive toolkit
• Vert.x

17. Reactive system

18. Reactive System
Reactive manifesto
• Elastic
• Message-driven
• Responsive
• Resilience
• Failure = first-class citizen

19. Reactive System
1 JVM
JVM
data -> function -> data -> function -> data
JVM

20. Reactive System
Distributed system
JVM
data -> data -> function -> data -> data-> function -> data
JVM
JVM JVM
JVM JVM

21. Reactive System
Distributed system
• Between jvm's
• http (spring webclient)
• gRPC, RSocket
• Messaging
• Between jvm & database
• non-sql vs sql
• Between jvm & UI
• RxJS

22. Project reactor

23. Project reactor
Flux & mono
• Flux = Publisher <0 .. N>
• Mono = Publisher <0 – 1>

24. Project reactor
Getting started
• Exercises
• Publisher / subscriber
• onComplete
• Error handling
• Backpressure

25. Project reactor
Getting started
• https://github.com/vanseverk/projectreactorintro
• IDE
• IntelliJ : mark ‘test’ folder as ‘test sources root’
• TODO 01 – 06
• Extra (backpressure)
• TODO 07 - 08

26. Event sourcing

27. Event Sourcing
Intro
• Persist events instead of domain objects
• Immutable event-log
• Replaying events can help development, debugging
• No need to lock DB tables
• Can be a perfect fit in event-driven architectures
• Can be designed to handle temporary partitioning
• Microservices handle (or replay) events and store what they require
• Eventual consistency
• Reactive Programming + Events -> Reactive Event Streaming

28. Event Sourcing
Intro
• Introducting: NATS
• https://nats.io/
• High performance messaging system for cloud native applications, IoT
messaging, and microservices architectures
• High performance, lightweight, many extensions

29. Event Sourcing
Intro
• Introducing: NATS Streaming
• Event Sourcing + Streaming including replay from time or sequence number
• Durable subscriptions for transient clients
• Persistent/guaranteed (at least once) message delivery
• Pub/Sub ; Request/Reply; Queueing to share work

30. Workshop

31. Reactive system: measurements
Architecture

32. Reactive system: measurements
Practical
• https://github.com/vanseverk/anomalydetection-nats
• 2 branches
• master = exercise (TODO)
• solution
• workshop.pdf