The document discusses reactive programming, a paradigm that allows for building responsive, resilient, and elastic systems by enabling asynchronous operations and message-driven architectures. It emphasizes the importance of responsiveness for usability, and outlines the use of reactive extensions like RxJava for managing asynchronous data flows. Key concepts include managing failures through isolation, adapting to workload changes, and utilizing non-blocking communication to reduce system overhead.

1. Going Reactive
Mesut Can Gürle

2. ● Extreme Programmer
● Open Source
Enthusiast
● PhD Student
● Devops Turkey, Istanbul
Coders
● #793 @LKD
● @mesutcang
● Jedi

3. Agenda ❏ Basics
❏ Java toolset
❏ Rx Java
❏ Questions

5. Reactive
Programming
● A programming paradigm that helps you to
build ‘Reactive Systems’.
● In a reactive world, we can't just wait for a
function result, a network call, or a database
query to return.
● Every moment we wait for something, we
lose the opportunity to do other things in
parallel.
● Reactive programming can be done in
several ways
Akka Actors
Reactive Extensions (Rx) – reactive + functional

6. Use Cases
● External Service Calls
● Highly Concurrent Message Consumers
● Spreadsheets
● Abstraction Over (A)synchronous Processing

7. Iterator?

9. Callback?

12. Responsive
● Responsiveness is the cornerstone of usability and utility
● Responsiveness means that problems may be detected quickly and dealt
with effectively.
● Responsive systems focus on providing rapid and consistent response
times, establishing reliable upper bounds so they deliver a consistent
quality of service.
● This consistent behaviour in turn simplifies error handling, builds end user
confidence, and encourages further interaction.

13. Resilient
● The system stays responsive in the face of failure.
● Resilience is achieved by replication, containment, isolation and
delegation. Failures are contained within each component, isolating
components from each other and thereby ensuring that parts of the system
can fail and recover without compromising the system as a whole.

14. Elastic
● The system stays responsive under varying workload.
● Reactive Systems can react to changes in the input rate by increasing or
decreasing the resources allocated to service these inputs.
● They achieve elasticity in a cost-effective way on commodity hardware and
software platforms.

15. Message Driven
● Reactive Systems rely on asynchronous message-passing to establish a
boundary between components that ensures loose coupling, isolation and
location transparency.
● Employing explicit message-passing enables load management, elasticity,
and flow control by shaping and monitoring the message queues in the
system and applying back-pressure when necessary.
● Non-blocking communication allows recipients to only consume resources
while active, leading to less system overhead.

16. Reactive Extensions
● ReactiveX is a library for composing asynchronous and event-based
programs by using observable sequences.
● ‘The Observer pattern done right.’
● Initially implemented for C# by Microsoft, later ported to many languages
by Netflix Rx.
● Rx-Java is the Java implementation.

18. Before
● Call a method
● Wait for result
● Store the return value from that method in a variable
● Use that variable and its new value to do something
useful

19. Rx Java
● The Subscribe method connects an Observer to an
Observable
● Once you Subscribe, no need to block the thread
● Values will come to your Observer when they are
ready

26. Schedulers ● immediate
● newThread
● computaion
● io
subscribeOn - specify the Scheduler on which an
Observable will operate
observeOn - specify the Scheduler on which an
observer will observe this Observable