BUILDING REACTIVE PIPELINES WITH KOTLIN & SPRING MARK HECKLER - - PowerPoint PPT Presentation

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Jul 29, 2023 22 likes •204 views

BUILDING REACTIVE PIPELINES WITH KOTLIN & SPRING MARK HECKLER @mkheck Copenhagen Denmark Building Reactive Pipelines with Kotlin & Spring How to go from scalable apps to (ridiculously) scalable systems Mark Heckler Spring Developer

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Copenhagen Denmark

BUILDING REACTIVE PIPELINES WITH KOTLIN & SPRING MARK HECKLER

@mkheck

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Building Reactive Pipelines with Kotlin & Spring

How to go from scalable apps to (ridiculously) scalable systems

Mark Heckler Spring Developer & Advocate www.thehecklers.com mark@thehecklers.com mheckler@pivotal.io @mkheck

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@mkheck www.thehecklers.com

“Please do LESS with MORE!” 💱💱💱

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@mkheck www.thehecklers.com

Why are we here?

Scaling systems: traditional approaches What to do when we reach the limits? Sounds good, but how does it work?

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@mkheck www.thehecklers.com

There’s more!

Roman Elizarov 10:15 tomorrow Sebastien Deleuze 11:15 tomorrow

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@mkheck www.thehecklers.com

Who am I?

Author
Architect & Developer
Java Champion, Rockstar
Professional Problem Solver
Spring Developer & Advocate
Creador y curador de

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@mkheck www.thehecklers.com

New book!

But you can’t buy it yet…

DISCLAIMER: artist’s rendition only, not the real cover

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@mkheck www.thehecklers.com

Scaling systems: off to a good start

Microservices for independent scaling Messaging platforms Spring Cloud Stream for productivity + versatility (+ resilience, etc.)

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@mkheck www.thehecklers.com

Sink Processor

For example…

Source

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@mkheck www.thehecklers.com

Consumer Function

Evolving the API

Supplier

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@mkheck www.thehecklers.com

We’ve redlined, now what?

Change approach to scaling Scaling (connections) vs. Performance (parallelization) Coroutines (Kotlin), Reactor, Loom (?) Integration with messaging platforms…any synergies here? 🤕

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@mkheck www.thehecklers.com

–Rossen Stoyanchev, Reactor team member

“In a nutshell reactive programming is about non-blocking, event-driven applications that scale with a small number of threads with backpressure as a key ingredient that aims to ensure producers do not overwhelm consumers.”

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@mkheck www.thehecklers.com

Reactive Streams: 4 interfaces

Publisher<T> Subscriber<T> Subscription Processor<T,R>

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@mkheck www.thehecklers.com

Reactive Streams in Context

Publisher<T> Subscriber<T> Subscription Processor<T,R> Spring Cloud Stream parallel Source/Supplier Sink/Consumer (n/a) Processor/Function

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@mkheck www.thehecklers.com

Let’s code!

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@mkheck www.thehecklers.com

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@mkheck www.thehecklers.com

Resources

https://github.com/mkheck/building-reactive-pipelines-with-kotlin https://kotlinlang.org https://cloud.spring.io/spring-cloud-stream/ https://projectreactor.io mark@thehecklers.com, mheckler@pivotal.io @mkheck on Twitter

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#KotlinConf

THANK YOU AND PLEASE REMEMBER TO VOTE!

Mark Heckler @mkheck