The document discusses Akka, a toolkit for building highly concurrent, distributed, and resilient message-driven applications on the JVM. It describes key components of Akka including actors for concurrency, clusters for location-transparent resilient applications, persistence for event sourcing, and HTTP for asynchronous reactive servers. It also discusses the actor model of concurrent computation and related topics like reactive streams and advantages of asynchronous messaging.

1. The Cloud-Natives
are RESTless

2. Konrad `@ktosopl` Malawski
Akka Core,
Akka Persistence,
Akka HTTP,
Reactive Streams

3. The concurrent & distributed applications toolkit
Akka is a toolkit and runtime for building highly
concurrent, distributed, and resilient message-driven
applications on the JVM

4. The concurrent & distributed applications toolkit
Akka is a toolkit and runtime for building highly
concurrent, distributed, and resilient message-driven
applications on the JVM

5. Actors – Concurrency / high perf. messaging
Cluster – Location transparent, resilient clusters
Persistence – EventSourcing support (many DBs)
HTTP – Fully Async & Reactive Http Server
and much more (kafka, cassandra, testing, …)

6. http://cidrdb.org/cidr2005/papers/P12.pdf
“Data on the Outside,
versus Data on the Inside”
Pat Helland

7. “Communication on the Outside,
versus Communication on the Inside”

8. ”The actor model in computer science is a
mathematical model of concurrent computation
that treats actors as the universal primitives of
concurrent computation. ”
Wikipedia
The Actor Model

9. An Actor
and acts on them by:
• Sending messages
• Changing its state / behaviour
• Creating more actors
receives messages

10. An Actor
A concurrency and distribution construct.
an addressable, location-transparent, entity
Show diagram showing people interacting with each other.

11. Not Only Server-Client

12. HTTP/2 “push” still needs a “pull”
https://blog.cloudflare.com/announcing-support-for-http-2-server-push-2

13. Clusters, direct, p2p communication

14. Clusters, direct, p2p communication

15. Clusters, direct, p2p communication

16. Clusters, direct, p2p communication

17. Not Only JSON
“The Internet is running in debug mode.”
— Rüdiger Möller
http://java-is-the-new-c.blogspot.de/2014/10/why-protocols-are-messy-concept.html

18. Not Only JSON: Example data
MediaContent {
media = Media {
uri = "http://javaone.com/keynote.mpg"
title = "Javaone Keynote"
width = 640
height = 480
format = "video/mpg4"
duration = 18000000
size = 58982400
bitrate = 262144
persons = ["Bill Gates", "Steve Jobs"]
player = JAVA
copyright = null
}
}
images = [
Image {
uri = "http://javaone.com/keynote_large.jpg"
title = "Javaone Keynote"
width = 1024
height = 768
size = LARGE
}
Image {
uri = "http://javaone.com/keynote_small.jpg"
title = "Javaone Keynote"
width = 320
height = 240
size = SMALL
}
]

19. Not Only JSON create ser deser total size
protostuff 68 433 634 1067ns 239bytes
protobuf 121 1173 719 1891 239
kryo-serializer 53 1480 1331 2810 286
thrift 95 1455 731 2186 349
. . .
json/jackson/manual 52 1039 1228 2267 468
json/jackson/databind 54 1164 1866 3030 485
json/gson/databind 56 4667 4403 9070 486
xml/xstream+c-aalto 54 3310 6732 10042 525
xml/JAXB 54 4354 141333 145686 719
java-built-in 53 5046 23279 28325 889
Slide only to illustrate order-of-magniture differences. Don’t over-focus on numbers.
All details here: https://github.com/eishay/jvm-serializers/wiki

20. Not Only JSON create ser deser total size
protostuff 68 433 634 1067ns 239bytes
protobuf 121 1173 719 1891 239
kryo-serializer 53 1480 1331 2810 286
thrift 95 1455 731 2186 349
. . .
json/jackson/manual 52 1039 1228 2267 468
json/jackson/databind 54 1164 1866 3030 485
json/gson/databind 56 4667 4403 9070 486
xml/xstream+c-aalto 54 3310 6732 10042 525
xml/JAXB 54 4354 141333 145686 719
java-built-in 53 5046 23279 28325 889
Slide only to illustrate order-of-magniture differences. Don’t over-focus on numbers.
All details here: https://github.com/eishay/jvm-serializers/wiki

21. Not Only JSON create ser deser total size
protostuff 68 433 634 1067ns 239bytes
protobuf 121 1173 719 1891 239
kryo-serializer 53 1480 1331 2810 286
thrift 95 1455 731 2186 349
. . .
json/jackson/manual 52 1039 1228 2267 468
json/jackson/databind 54 1164 1866 3030 485
json/gson/databind 56 4667 4403 9070 486
xml/xstream+c-aalto 54 3310 6732 10042 525
xml/JAXB 54 4354 141333 145686 719
java-built-in 53 5046 23279 28325 889
Slide only to illustrate order-of-magniture differences. Don’t over-focus on numbers.
All details here: https://github.com/eishay/jvm-serializers/wiki

22. Actually solving a real problem for fun and profit.
Reactive Streams

23. Reactive Streams – why it all started

24. Reactive Streams – why it all started

25. Reactive Streams – why it all started
~2013:
Reactive Programming
becoming widely adopted on JVM.
- Play introduced “Iteratees”
- Akka (2009) had Akka-IO (TCP etc.)
- Ben starts work on RxJava
http://blogs.msdn.com/b/rxteam/archive/2009/11/17/announcing-reactive-extensions-rx-for-net-silverlight.aspx
http://infoscience.epfl.ch/record/176887/files/DeprecatingObservers2012.pdf - Ingo Maier, Martin Odersky
https://github.com/ReactiveX/RxJava/graphs/contributors
https://github.com/reactor/reactor/graphs/contributors
https://medium.com/@viktorklang/reactive-streams-1-0-0-interview-faaca2c00bec#.69st3rndy
Teams discuss need for back-pressure
in simple user API.
Play’s Iteratee / Akka’s NACK in IO.
} }A lot more people join
discussions, Reactive Streams
are born.

26. Advantages of Async Messaging

27. Time holding Connection

28. Time holding Connection

29. Time holding Connection

30. Time holding Connection
AFAIK:
Addressed by HTTP/2,
since you can open “subStreams.”

31. Long running task, sync vs. async

32. Long running task, sync vs. async

33. Long running task, sync vs. async

34. Back-pressure in Action

35. Streaming from Akka HTTP

36. Streaming from Akka HTTP
No demand from TCP
=
No demand upstream
=
Source won’t generate tweets

37. Streaming from Akka HTTP
No demand from TCP
=
No demand upstream
=
Source won’t generate tweets
=>

38. Streaming from Akka HTTP
No demand from TCP
=
No demand upstream
=
Source won’t generate tweets
=>
Bounded memory
stream processing!

39. Only the tip of the iceberg

40. Akka Cluster
and cluster tools
Akka Streams
async & back-pressured
More tools in the toolbox

41. Further reading:
Reactive Streams: reactive-streams.org
Akka documentation: akka.io/docs
Free O’Reilly report – very out soon.
Get involved:
sources: github.com/akka/akka
mailing list: akka-user @ google groups
gitter channel: https://gitter.im/akka/akka
Contact:
Konrad ktoso@lightbend.com Malawski
http://kto.so / @ktosopl