(Joseph deBuzna + Zulfikar Quereshi, HVR) Kafka Summit SF 2018 This presentation is a customer story about France-based regional airline HOP! and their need to make better use of data that was contained in various applications. They also needed this information to be available in real time. As one can imagine, airlines manage a wide variety of information such as weather, customer information, flight plans, sensor data from planes and much more. In this presentation, Joe will discuss how HOP! was delivering their data before and the limitations associated with delivering this data. Joe will then talk about HOP!’s selection of Kafka and HVR as a solution to enabling data availability and real-time information for analysis and action. In this session, attendees will learn: -How Kafka was selected and chosen as a solution for HOP!’s complex challenges -Architecture and capabilities implemented that enabled data feeding from multiple sources to Kafka -Considerations and challenges with this approach -Business results and future plans

1. 1
Hop! Airlines Jets to Real-Time
@HVR_Software

2. 2
Joe deBuzna
VP Field Engineering HVR
Dad, surfer, piano player
Former GoldenGate and Shareplex product manager
Started as a C programmer turned DBA
Who am I?

3. 3
Agenda
• Why This Matters
• HOP!
• Business Challenge
• Technical Requirements
• Why Not Just Add More Databases?
• From Databases to Events
• The Solution
• Q&A

4. 4
Perspective:
A story of two encounters
Who am I?
Why This
Matters

5. 5
Title
Subtitle
• Subsidiary of Air France
• Launched March 2013
• Fleet of 107
• €775MM in Sales, 2017

6. 6
Business Challenge
• Flight crew personnel had to laboriously check the
operation application for scheduling updates.
• IT tasked with providing better service to flight crew
with push notifications for scheduling updates.
• This must not negatively affect existing operations,
cannot be expensive, and needs to be implemented
as soon as possible.

7. 7
Scalable
Real-Time
Technical
Requirements

8. 8
Architecture: In the Beginning
Core Business Operations
SQL Server SybaseOracle
• Standard legacy monolithic
architecture
• Greater capacity means lengthy
and expensive hardware
architecture upgrades

9. 9
Push Notifications: Take One
Core Business Operations
SQL Server SybaseOracle
Scheduling
Services
• Tremendous effort in trying to
squeeze more capabilities out of
existing system
• Results: Goals not achieved. Either
overload the system or send
updates a couple times a day

10. 10
Why Not Just Add More Databases?
More MonolithMonolith

11. 11
Because You End Up With This
• Explosion of specialized, fragmented
data systems
• Data is constantly diversifying (e.g.
event data, unstructured data, more
flavors of databases)
• Too many integration products, too
much to manage
• ETL misses is slow and misses
changes
Data
Warehouse
Hadoop
NoSQL
Oracle
SFDC
Logging
Bloomberg
OLTP ActiveMQ
App App
Caches
OLTP OLTPAppAppApp
Web Custom Apps Microservices Monitoring Analytics

12. 12
A Better Way
Monolith Microservices
But how do you get there?

13. 13
Getting to Event Driven Services
• Convert legacy databases into events
• Broadcast events
• Retain them in the event log
• Evolve the event-stream with services built as
streaming functions
• Recast into views when you need to query

14. 14
GUI
UI Service Orders Returns
Pay Fulfilment Stock
Microservices Take One: REST Interconnect
D i a g r a m b y C o n f l u e n t

15. 15
GUI
UI
Service
Orders
Service
Returns
Service
Fulfilment
Service
Payment
Service
Stock
Service
D i a g r a m b y C o n f l u e n t
Microservices Take Two: Now with Kafka!

16. 16
D i a g r a m b y C o n f l u e n t
Event Streams are the Key to Scalable Service Ecosystems
Sender has no knowledge of
who consumes the event.
Orders
Service

17. 17
Learning
To Fly
(learned requirements)
Log-Based CDC
Architecture
Additional Features

18. 18
From Database to Events
• How do you convert database
transactions to event streams?
• What about deletes and transient
updates?
• When did it happen?
• In what order did it happen?
?

19. 19
From Database to Events
• Source commit timestamp
• Operation type
• Unique sequence ID
• Data quality/coercion
?

20. 20
HVR and Kafka
The Answer?

21. 21
HVR’s Role
HVR’s log-based change data capture provided the right
combination of light touch with performance required to tap
into the various source systems without affecting existing
operations.
The ability to replicate changes to multiple locations with
the flexibly to enrich and convert all changes into a time
series allowed Kafka to seamlessly integrate with the
legacy architecture unleashing a new era in innovation.

22. 22
Kafka’s Role
The premier stream processing platform, Kafka is at the
core of the new microservices implementation.
Data sent by HVR is processed in real-time and the
enriched results are instantly read by the services and
delivered to the flight crew.
Implementing Kafka today sets the stage for the next
generation of scalable microservices for tomorrow.

23. 23
• Exceeded Customer Service
goals; notification sent to phones
in seconds instead of hourly
• Innovative new micro services
currently being implemented
• A world of new possibilities now
being discussed
Kafka
}
Presentation
lookups
Core Business Operations
Scheduling
Services
Additional
Services
SQL Server SybaseOracle
The Result: Innovation Unleashed
HVR
HVRHVR

24. 24
What’s Next
• HRIS - Integrate into Kafka flow the HR Info System
(ERP done today)
• Financial System Integration
• Maintenance
The Sky’s the Limit . . .

25. 25
Title
Subtitle
Q & A

26. 26
Joseph deBuzna
joseph.debuzna@hvr-software.com
@HVR_Software
hvr-software.com