In the first meetup of the Kafka Utrecht community we talked about Rabobank implementing an event driven architecture using Apache Kafka. This presentation tells the story the led up to the Business Event Bus platform and illustrates its use with a few business use cases. More information on the meeting can be foud here: https://www.meetup.com/Kafka-Meetup-Utrecht/events/232443728/

1. Real-Time Relevance
Rabobank’s Event-driven Architecture
using Apache Kafka
Jeroen van Disseldorp
Dizzit

2. Dizzit &Who am I
Personal
• 41 years, married, father of two
• Living in Raamsdonksveer
• Fanatic squash player
Education
• 1997 MSc Computer Science,
Utrecht
• 2008 MBA Rotterdam School of
Management, Erasmus University
Career
• Started developing at age 9
• 19 years in large corporations
• Online, Open Source, Architecture
• Passion for Product Development
• Started Dizzit in 2014
• 3 FTE today, looking for new devs

3. Dizzit &Rabobank Senses
Personal Dialogue
Proactive and help out
Every journey is a
positive experience

4. Dizzit &Rabobank Mobile Banking
A personal financial environment
• Manage your payments, personal
finance and bookkeeping
intuitively and easily
• Notifies you, at the right moment,
thinks along
Your financial network close
• Rabobank advisors ‘one touch
away’
• Always connected to your
financial network
• Collaborate and share with
whomever you want
Using your preferred device
• Mobile, tablet, laptop, desktop
• Brain or touch operation
• Car

5. Dizzit &Being relevant
Functionality
Alerting
Extra Inzicht 2.0
Up-to-date customer
info
Customer Journey
Analytics

6. Dizzit &Alerting
Case
Customers want to be in control
of their finances. This requires
notifying them in situations that
require action.
For instance:
• Balance below threshold
• Salary received
• Energy bill could not be paid
• You spent more on groceries
than you should have
Challenge
Rabobank allows customers to
define custom notification rules.
But the entire IT landscape is
undergoing renewal. How to
detect and process the relevant
financial events?

7. Dizzit &
Time-driven
Request-driven
Event-driven
Initiator: Time
Participants: specified systems
Initiator: Client
Participants: Client and Server
Initiator: Event
Participants: open-ended
Data logistics mechanisms

8. Dizzit &Time-driven: Digestion
“Data warehouses”
Typically 3 times per day
Batches
Fixed process
Slow but predictable

9. Dizzit &
“SOA”
Millions of times per day
Individual commands
Two involved parties
Requires specific intent
Request-driven: Movement

10. Dizzit &Event-driven: Nervous system
Millions of times per day
Observations, signals
Context-dependant process
Autonomous microservices
“Business Event Bus”
Millions of messages per day
Individual observations and signals
Context-dependent processing
Network of systems

11. Dizzit &
Business Event
An event that is important for a customer
and/or business expert

12. Dizzit &
Business Event Bus
Rabobank’s application integration platform
that enables real-time business

13. Dizzit &
Business Event Bus
central nervous system
Rabobank’s application integration platform
that enables real-time business

14. Dizzit &Before Business Event Bus
Producer 1 Producer 2 Producer 3
Consumer 1 Consumer 2 Consumer 3 Consumer 4

15. Dizzit &Using Business Event Bus
Producer 1 Producer 2 Producer 3
Consumer 1 Consumer 2 Consumer 3 Consumer 4
Business Event Bus

16. Dizzit &Features
Functionality
Event Messaging
Publish / subscribe model
Schema registry for corporate
data governance
Strict security model
Characteristics
Extremely scalable, up to
billions of messages per day
Producers and consumers
don’t know each other
Producers and consumers
don’t have to be available at
the same time
Allows both real-time and
batch processing
Producer 1 Producer 2 Producer 3
Consumer 1 Consumer 2 Consumer 3 Consumer 4
Business Event Bus

17. Dizzit &Being relevant
Functionality
Alerting
Extra Inzicht 2.0
Up-to-date customer
info
Customer Journey
Analytics

18. Dizzit &Extra Inzicht 2.0
Case
Rabobank’s personal finance
manager categorizes income and
expenditures.
Examples:
• Mortgage
• Groceries
• Clothing
Challenge
The current solution processes
transactions in nightly batches,
so results are visible the next day
only. This decreases the service’s
value.
The current IT solution is too
expensive. A cheaper solution
must be found, or the service
will be discontinued entirely.

19. Dizzit &Being relevant
Functionality
Alerting
Extra Inzicht 2.0
Up-to-date customer
info
Customer Journey
Analytics

20. Dizzit &Up-to-date customer info
Case
Banking customers are given
self-service pages with which
they update their personal
contact information.
For instance:
• Address
• Email
• Mobile phone number
Challenge
CRM contains the master
customer data, but does not
support high-volume queries.
Therefore other systems store
personal information as well.
These systems must be notified
of any change a customer makes
to his/her personal information.

21. Dizzit &Being relevant
Functionality
Alerting
Extra Inzicht 2.0
Up-to-date customer
info
Customer Journey
Analytics

22. Dizzit &Customer Journey Analytics
Case
Rabobank monitors visitors and
customers across website and
app to track effectiveness and
ease of use.
Examples:
• Product pages visited
• Sales processes started
• Services used
Challenge
The current solution supports
only web-based channels. This
means customers are not
tracked across other internal
channels (eg. bank offices, call
centers, chats, API) and external
channels (eg. Facebook, Twitter,
external websites).

23. Dizzit &Making Rabobank relevant
Alerting
200M+ rules / day
20M alerts / month
Extra Inzicht 2.0
25M entries / day
10M categorizations / day
Up-to-date customer info
150k+ updates / day
Customer Journey
Analytics
1M+ sessions / day

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