The document compares two reactive approaches for scalable, message-driven backend applications in Java Spring Boot and Akka. It discusses the principles of the reactive manifesto, the actor model, and highlights the advantages and challenges of using Akka for microservices. Key points include the use of asynchronous messaging, the importance of non-blocking operations, and considerations for failure handling.

1. Two Reactive approaches to scale
1
Comparing two approaches
for scalable, message-driven, backend applications
in Java
Spring Boot μServices and Akka
Lorenzo Nicora Lorenzo.nicora@opencredo.com

2. 2
“Reactive” is…
Reactive
Semantically overloaded term
adj. “Readily responsive to stimulus” [Merrian-Webster dictionary]
From Latin “reagere”: act in return

3. • Reactive as Responsive
Quickly prompt to user actions
Reactive as…
• Reactive as Data binding
Declarative, as opposed to Imperative
a=b+3
e.g. Spreadsheets
• Reactive streams as Asynchronous Data Streams
• Reactive as Reactive Manifesto

4. ü Responsive à Low latency
ü Resilient à Stay responsive on failure
ü Elastic à Scale as needed
ü Message-Driven
• Async messages as only communication between components
Reactive Manifesto

5. ✗ No Blocking operation
✗ No Synchronization
✗ No Resource hogging
Decoupling and isolation in…
ü Time à Allow concurrency
ü Space à Components location decoupling
Reactive Manifesto promotes

6. Top-down approach: from Macro
(at μService boundaries)
o Message based communication between services
o Isolation at service level
Bottom-Up approach: from Micro
(within the service)
o Message based communication between components
o Non-blocking processing
o Isolation at component level
Macro and Micro approaches

7. Two real world projects
Spring Boot
μService
Akka

8. Spring Boot μService application
ü Message-based communication between services
ü Non-blocking (where possible)
o Java 8 CompletableFutures
o Http non-blocking Servlets
o Fast-returning API endpoints
ü Event sourcing persistence
o Concursus forerunner
ü Spring Boot and Spring Cloud Config
Spring Boot μService

9. Java application using Akka, Cluster
ü Akka Actor programming model
ü Event-sourcing by Akka Persistence
ü Akka Cluster
ü Deployed using ConductR [Commercial]
ü Akka Http server (no container), non blocking
ü TypeSafe Config
✗ not Lagom framework
✗ not Akka Streams
Akka Cluster

10. TL;DR
“The actor model in computer science is a mathematical model of
concurrent computation that treats "actors" as the universal primitives of
concurrent computation.
In response to a message that it receives, an actor can: make local
decisions, create more actors, send more messages, and determine how to
respond to the next message received. Actors may modify private state, but
can only affect each other through messages (avoiding the need for any
locks).”
[Wikipedia]
Actor model
Actor
Actor
Actor
Mailbox Mailbox
Mailbox
ü Article by Carl Hewitt (1973)
ü Erlang (1986)
ü Akka framework (2009)

11. A different way to concurrency
Actors, !Threads
Actor is the primary computational entity
o In Java, still a mixed world of Objects and Actors
Actors interact exclusively via asynchronous messages
o As opposed to Objects interacting through method calls
o Actors REACT on receiving a message
o No synchronisation; no lock
Actor model for dummies
Actor
Actor
Actor
Mailbox Mailbox
Mailbox

12. Actor handles one message a time
o Message handling code is intrinsically thread safe
o May have simple state: Instance properties in Java
Actor is lightweight
o Little overhead over creating an object
o May be used to hold request context
• Per-request Actors: a common pattern
Actor model

13. Collaborating Actors
≠ Dependency Injection
o Akka: Actor Refs (location/lifecycle transparent) ≠ object refs
Actors are created by Actors (…then may be passed around)
Parent à Children
Supervision hierarchy
Failure handling
Supervision

14. Implementing Reactive principles
Implementing Reactive principles
from Macro and from Micro
Plain Java/Spring or Akka

15. Never block threads waiting
Macro
o Asynchronous messaging protocols between services
Micro
Plain Java
o CompletableFuture
o Non-blocking Servlets
o Low level NIO (!)
Akka
o Actors REACT to messages: never blocks waiting.
o Have to use some discipline not to block
e.g. waiting for a response from a synchronous resource
Non-blocking

16. Handle timeouts,
for resiliency
Macro (at service boundaries)
o Outbound connection timeouts (client)
o Inbound request/response (ack) handling timeouts (server)
Micro
Plain Java
o Not easy to handle timeouts consistently à ...unhandled or use default
Akka
o Everything has an explicit timeout à impossible to forget
o Actor message receiving timeout handler
Timeouts handlings

17. Asynchronous Failure handling
Java CompletableFuture à handle exceptional completion
o Error prone; easily forgotten
o No way to separate Error and Failure handling
Actors à failure handled by Supervisor
Akka: Supervisor is notified when an Actor throws an Exception
• Failure : handled externally from message flow
• Error: part of message handling behaviour
Handling Failure, Asynchronously

18. Event/Command sourcing
natural persistence patterns
for distributed, asynchronous applications
Plain Java/Spring
o Write your own Event Sourcing à Concursus
Event Sourcing naturally fits Actors
o Actors may be stateful
o Events and Commands are messages
• When received à Actor change its state
• May be saved and replayed
o Actors may represent Aggregate Root (DDD) or Command Processor
ü Akka Persistence: Command and Event Sourcing out of the box
Persistence: Event-sourcing

19. Conclusions

20. Keep in mind Reactive principles
…even when not using “reactive” technologies
à Scalable and resilient applications
Many implications behind the generic principles
Reactive principles

21. Does a “Reactive” technology like Akka help?
at Micro
ü Simpler, more testable concurrent code
ü Requires less discipline then plain Java 8
✗ A new programming model to learn
Does Akka help?

22. Does a “Reactive” technology like Akka help?
at Macro
• Still requires discipline at architectural level
✗ Akka forces to reinvent a lot of wheels on integration
✗ Akka doesn’t integrate with Spring
Does Akka help?

23. Akka/Actor model
μServices:
NOT mutually exclusive
Consider adopting Akka for some services
• The most business-critical (+resilient)
• Highest concurrency
Akka and μServices

24. Reactive Manifesto
http://www.reactivemanifesto.org/
à Glossary: http://www.reactivemanifesto.org/glossary
Concurrency in Erlang & Scala: The Actor Model
https://rocketeer.be/articles/concurrency-in-erlang-scala/
Introducing Actors (Akka)
http://rerun.me/2014/09/11/introducing-actors-akka-notes-part-1/
DDD and Actor model (Vaughn Vernon, DDD eXchange 2013)
https://skillsmatter.com/skillscasts/4185-vaughn-vernon
Akka project
https://github.com/akka/akka
More…

25. Thanks!
Questions?