Vous avez entendu parler des acteurs Akka et vous vous demandez quels types d’architectures vous pouvez mettre en place, ou comment les intégrer dans votre architecture ? Et quelle est la courbe d’apprentissage ? A travers un retour d’expérience, nous répondrons à ces questions et vous montrerons comment en trois mois nous avons mis en place une architecture basée sur Akka et Spray en Scala. Par Nicolas Jozwiak

1. Supervise your akka actors
Nicolas Jozwiak

2. Programmeur and agiliste!
!
@njozwiak

3. Contents
•Context
!
•Why Akka and
Scala ?
!
• Solution
!
•DevOps
!
• Issues and
knowledges
!
•Results

4. Context

5. FTP
Talend
offers
offer
s
Web Service
offers
syslog
Logstash ElasticSearch UI result

6. Talend
Web Service
offers
FTP
1 Read FTP
2
Translate
Xml in Jobs
offers
offer
s
3 Ask Web Service for diff
4 Save

7. • Not happy customers
• Lost process
• Difficult to replay
• Dashboard not
efficient

8. • Business logic
everywhere
• Talend processing
complex
and not known
• Approximate error
handling
• Slow integration

9. • Increase processing reliability
• Centralize business logic
• Enhance processing performance

10. Why Akka and Scala ?

11. Why Akka ?
• Isolate business code in actors
• Events to process
• Fault tolerance
• Supervision strategy
• Performance

12. Why Scala ?
• Team knows Scala (a little)
• Try Scala in the company
• Scala with Akka rocks !

13. Solution

14. Web Service
offers
FTP
1
2
3
4
Read FTP
Translate
Xml in Jobs
offers
Ask Web Service for diff
Save
TAakleknad
offer
s

15. Supervision
• Every single actor has a default supervisor
strategy
•Means manage Actors failures
• Send a notification to its supervisor
• Clean separation of processing and error
handling

16. Actor system
Actor1 Actor2
A D
B C
A
Exception B C

18. MasterSupervisor
FileSystem
Supervisor
FileCrawler
Xml
Supervisor
XmlReader
Posting Supervisor
DiffActor
Posting
Service
Syslog
DeadLetterListener
WorkStatus

19. DevOps

20. • No guarantee on message delivery
• Have some metrics :
‣ Logs
‣Metrics with Graphite
‣Ostrich (Twitter)
‣ Kamon IO

25. • Endpoints access with Spray :
‣ Statistics
‣HealthCheck
‣Workflow state

26. Issues & knowledges

27. • Actor system design
• An actor with lots of processing
• Unit testing
• Actors and Futures

28. •Mind shift
• Business events
• Delegate to actors
• Isolate business rules
• Behaviour testing

29. • Domain Driven Design applied
‣Make implicit concepts explicit
‣ Aggregates

30. MasterSupervisor
Xml
Supervisor
XmlReader
DeadLetterListener
Entry point
Never call !

31. Results

32. • In production
• Proactive way
• New dashboard
• Processing time
•Web Service to optimize
• FTP to remove

33. Conclusion

34. • Akka is very powerful
‣Complex underlying notions
‣Active ecosystem
• KISS

35. Thank you
for watching