SPIN Meetup Data Driven part 1

1. Bas van Oudenaarde, axonX.ai (by RubiX)
Mic Hussey, Confluent
axonX.ai
SPIN Meetup 11 okt 2018

2. • 17.15hr - axonX.ai by Rubix
• 17.20hr -Introductie Data Driven
• 18.00hr - Kafka Platform
• 18.45hr - Dinner
• 19.30hr - Smart Mapper
• 20.00hr - Discussie / Borrel
• 21.00hr - Einde

3. axonX.ai
• Focus op nieuwe drivers rond integratie
• Start-up (Lean Start-up)
• Studio model (olievlek principe)
• 2 Start-ups:

4. axonX.ai
BB (Building Blocks):
v Streaming data platform -> Operational (Cloud), self-service
v Event Sourcing, IoT, analytics with Machine Learning (ML)
v Confluent Kafka (consulting/engineering)
v Automation / ML Scan
v Bring your ML challenge
“Data-centric-focus over Integration-centric”

5. axonX.ai
Streaming Data context, why?

6. axonX.ai
Team helping our Customer Use Cases:
Schiphol, IoT Streaming platform
Politie, classified J
Enexis, Digital transformation “techie-parts”
IT/OT, next generation Integration

7. axonX.ai

10. DevOps
Architectuur
µ-services
Cloud platform
Infra as Code –> No Infra
Culture/
Proces

11. µ-services Cloud platform
Infra as Code –> No Infra

14. Indirect in: Agile Teams, µ-services !!!

17. De structuur veranderd meer dan gedrag!
Purchase
Order
Line Items
Shipping Info
Cart
created
Item Item Item
Shipping
info
Events in time
Structuur met relations:
Events:

18. DB
Event Sourcing
Graph DB
Stream
processing
OLAP
Reporting
“Single point of Truth”
Iedere structuur / state te
maken

19. DevOps
Architectuur
µ-services
Cloud platform
Infra as Code –> No Infra
Cultuur/
Proces
Reactive
Architectuur
Event Driven
Event platform
DDD
Event Sourcing

20. Architectuur
µ-services
Cloud platform
Infra as Code –> No Infra
Cultuur/ Proces
Architectuur
Event Driven
Event platform
DDD
Event Sourcing
DevOps
Automation -> ML
Reactive

21. Cart
created
Item Item Item
Shipping
info
Events in time
Event Sourcing Implementation:
Hoeveel Items met boeken? Hoeveel items < 10 euro ?
Load all events in memory
Aggregate
Bepaal # boeken in items
Bepaal # items < 10 euro
Mhhh, niet praktisch!
Dat kan beter J

22. Vb. Web-based application, Object Relational Mapper (ORM) database
client database
application
Domain
model

23. CQRS pattern
Command Query Responsibility Segregation
client database
application
command
model
Query
model

24. CQRS met Event Sourcing (must)
Command Query Responsibility Segregation
client
database
application
command
model
Query
model
Event Store
state
events

25. CQRS met Event Sourcing
Command Query Responsibility Segregation
client
application
command
model
Query
model
Event Store
state
events
“De structuur veranderd meer dan gedrag!”

26. + Performance
Low latency write
High Volume
+ Scalable
! Eventually consistent - Delayed Reads
- No Acid Transactions
+ Delete everything
Robuust tegen data corruptie
+High read-to-write scenario
+Present/support different formats
(Q part optimized use case)
! Exactly once
- Complex query part
+ distributed systems
(microservices)
+ Out-of-order processing
IoT, Mobile C-part

27. Mic Hussey, Confluent