An alpaca is like a camel, but is Alpakka like Apache Camel? Can we use the reactive approach in the area of integration as well, instead of the blocking approach that Camel usually offers? In this live coding session we’re going to explore the possibilities that Alpakka - a set of connectors for Akka Streams - offers to fetch data from various data sources and send it to different destinations. Using those, you’re going to learn, on a working example, how to build a reactive integration layer with the help of Akka Streams - one of the most popular Reactive Streams implementation.

1. REACTIVE INTEGRATION
WITH AKKA STREAMS
AND ALPAKKA
JACEK KUNICKI
@rucek

2. @rucekREACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA
ENTERPRISE INTEGRATION
data in data out

3. @rucekREACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA
YESTERDAY
▸ SOA / WebServices
▸ ESB - single point of failure
▸ Enterprise Integration Patterns (2003)
▸ Apache Camel (2007)

5. @rucekREACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA
APACHE CAMEL
▸ de facto standard for integration
▸ a lot of connectors (~200)
▸ but:
▸ synchronous and blocking
▸ stringly typed

6. @rucekREACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA
TODAY
▸ streaming
▸ flow control (don’t flood the consumer)
▸ easier programming model

7. @rucekREACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA
ENTERPRISE INTEGRATION
data in data out

8. @rucekREACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA
ENTERPRISE INTEGRATION
data in data outf(x)

9. @rucekREACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA
TODAY
▸ streaming
▸ flow control (don’t flood the consumer)
▸ easier programming model
▸ FP, expressing integration patterns with function
composition

11. @rucekREACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA
ALPAKKA
▸ set of connectors for Akka Streams
▸ not so widely known
▸ less connectors than in Camel (~30)
▸ but:
▸ non-blocking, first-class Reactive Streams support
▸ type safety

12. @rucekREACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA
STREAM PROCESSING
PRODUCER CONSUMERPROCESSING
STAGE 1
PROCESSING
STAGE N
DATA
BACKPRESSURE
request(n)

13. @rucekREACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA
REACTIVE STREAMS
▸ asynchronous
▸ non-blocking backpressure
▸ reuse threads whenever possible
▸ slow consumers are represented in the domain model, e.g.
▸ Twitter API can tell you that you’re consuming too slow
▸ conflate() in Akka Streams - aggregates when the
downstream is slow

14. @rucekREACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA
AKKA STREAMS
▸ reusable building blocks form a graph
▸ a graph is lazy until actually run
Source[A]
A
Flow[A, B]
A B
Sink[B]
B

15. @rucek
USE CASE
1,foo
2,bar
3,baz
...
PARTITION BY ID
CASSANDRA
HTTP
TAIL EVEN/ODD
VALUES FOR EVEN ID’S
VALUES FOR ODD ID’S
REACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA

16. @rucekREACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA

17. @rucek
AND MORE…
▸ graph DSL for non-trivial graphs
▸ Akka Streams for Java
▸ https://sml.io/reactive-streams-for-java-developers
▸ build your own flow
▸ https://sml.io/custom-akka-streams-graph-stage
▸ perfect time to become a contributor!
REACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA

18. @rucek
THANK YOU!
@rucek
REACTIVE INTEGRATION WITH AKKA STREAMS AND ALPAKKA
rucek/reactive-integration-with-akka-streams-and-alpakka