This document discusses Rakuten Card's migration of its core credit card processing systems from an aging mainframe architecture to a new architecture based on Oracle Exadata, Exalogic, and Oracle Cloud Machine. The migration involved converting terabytes of data from legacy formats to Oracle Database, reimplementing software from Japanese COBOL to Java EE, and deploying the new systems with no downtime or issues. The new standardized architecture provides improved performance, scalability, portability, and security compared to the old vendor-locked mainframe systems. Overall the migration was completed on schedule and the new systems have been successfully operating in production.

1. Case Study: Credit Card Core System with
Exalogic, Exadata, Oracle Cloud Machine
[CON4994]
Oct 3, 2017
Hirofumi Iwasaki
Ville Misaki
System Strategy Department,
Rakuten Card Co., Ltd.

2. 2
Speaker Biography
 Hirofumi Iwasaki
 Group Manager
 Technology Strategy Group, System Strategy Department,
Rakuten Card Co., Ltd.
 Career
 Planning, designing & implementation of huge enterprise systems for
financial, manufacturing and public systems with Java EE in Japan over
18 years.
 Opus, Lectures, etc.
 Conferences: OOW 2014, JavaOne 2015, 2014, Java Day Tokyo 2014-
2015, Rakuten Tech Conference 2013-2016, etc.

3. 3
Agenda
1. About Rakuten Card
2. Background of the Old Systems
3. New Architecture Design Overview
 Exadata for database
 Exalogic for app server
 OCM for unlimited scale-out execution platform, with security
4. Data Migration
5. Software Migration
6. Extra Performance with Apache Spark
7. Results
8. Into the Future
3

4. 4
1. About Rakuten Card

5. 5
About Rakuten Group
 Unified brand, ecosystems around the world.

6. FC Barcelona partnership
kicked off on July 1, 2017

7. Warriors and Rakuten
Form Jersey Partnership
in the 2017-18 NBA season

8. 8
About Rakuten Card
 Top-level credit card
company in Japan
 Core of Rakuten
ecosystems.
 3rd position of total
transaction volume in 2016.
Growing rapidly.

9. 9
Conference session on Oracle OpenWorld 2014
 Shared with web front end
systems improvement
activities
 Based on Java EE 6
 On WebLogic server 12c
 With Oracle Exadata X3-2
 In-house development
 Great success

10. 10
2. Background of the Old Systems

11. 11
Card processing systems
Core Systems
Web Systems
External Systems
Intra Systems

12. 12
Old core systems - Mainframe
Mainframe
 Old architecture – over 20 years
 High cost structure
 Capacity and performance
limitation – no scale out
 Low maintainability with piled
programs and old architecture
database "NDB"
 Risk against vendor locked-in
 Limitation of the security for the
significant data

13. 13
Limitation of old mainframe systems – Areas
Business
Operations
Development

14. 14
Limitation of old mainframe systems – Business
Old New
 Cannot scale-out  Apply scale-out enabled
architecture, with Oracle RAC
and clustered WebLogic server.
 Low connectivity to other
systems
 Apply Java EE and latest
protocol.
 Less security management on
data
 Apply Oracle database
security options.
 No latest auto testing
environment
 Introduce latest auto testing
environment.

15. 15
Limitation of old mainframe systems – Development
Old New
 No local development  Apply Java EE and Oracle DB
for local dev.
 Hard to understand because
of its old architecture
 Apply latest Java EE for its
basement.
 Poor version control systems  Introduce git server and issue
track systems.
 No development community  Apply Java EE and join open
community.

16. 16
Limitation of old mainframe systems – Operation
Old New
 Poor automated operations  Introduce Jenkins and
automations.
 Manual error monitoring  Include Zabbix monitoring to
cover the new core system.
 Difficult to pin-point cause of
error
 Use standard Java tools: stack
traces, Flight Recorder, etc.
 Tons of unused codes  Apply automated source code
analyzing tool.

17. 17
3. New Architecture Design Overview

18. 18
Phase of the improvement – 3.0
1.0
Initial phase
2.0 In-house
development
3.0
Standardization
4.0
Data Optimized
Outsource based,
just started.
Vendor locked-in.
In-house
development,
differentiate with
lower costs and
faster delivery.
Standardized
system
architecture, both
for hardware and
software.
Overwhelming
differentiation,
with enabling
architecture for
customer centric
service.
Achieved Next
Current Standard
Architecture

19. Horizontal expansion from web systems
19
2013 2017
Web systems
Core
Systems
Expand

20. Oracle Exalogic
+ Exadata + ZFS Servers
Big Improvement - Functionality: Hardware 1/2
20
Mainframe
Old New
Core
Systems

21. Big Improvement - Functionality: Hardware 2/2
21
Oracle Exalogic
+ Exadata + ZFS Servers
Oracle Cloud Machine
(On premise private cloud)
For temporarily
request spiking
Low-Cost
Temp
Resource
New
Core
Systems

22. 22
Big Improvement - Reliability: Software Platform
 Financial de-facto standard
 Java EE compliant.
 Matured, from 1997.
 Financial de-facto standard
 ISO/IEC 9075 SQL compliant
 Matured, from 1983.
COBOL
Network
DB
App Server
Database
Old New
WebLogic Server
Oracle Database

23. 23
Big Improvement - Portability: Platform independent
Hardware, OS, app
server independent,
vendor free.
Mainframe,
Japanese COBOL,
vendor locked-in
Old New
Widfly
Payara
WebLogic
hp-ux
AIXSolaris
LinuxWindows
macOS
WebSphere

24. 24
Part 2

25. 25
Speaker Biography
 Ville Misaki
 Senior Software Engineer
 Technology Strategy Group,
System Strategy Department,
Rakuten Card Co., Ltd
 Career
 15+ years; 3 years at Rakuten
 In Finland, the Netherlands, Japan
 Java (EE), Perl, C++, web systems, relational
databases, performance optimization & security

26. 26
Agenda
1. About Rakuten Card
2. Background of the Old Systems
3. New Architecture Design Overview
 Exadata for database
 Exalogic for app server
 OCM for unlimited scale-out execution platform, with security
4. Data Migration
5. Software Migration
6. Extra Performance with Apache Spark
7. Results
8. Into the Future
26

27. 27
4. Data Migration

28. 28
Data Migration – Outline
ISAM
VSAM
NDB Oracle Database
Copy & Convert

29. 29
Data Migration – Outline
 Data Conversion
 Network database to relational database
 ISAM/VSAM data to relational database
 Legacy Japanese character set to Unicode
 Fix data inconsistencies
 Scale
 Terabytes of live production data
 Less than 24 hours time

30. 30
Data Migration – Minimize Downtime
 Offline migration
 Freeze data during migration
 Full migration – not incremental
 Customers mostly unaffected
 Data & System migration
 At the same time
 Cannot be split into phases
Cached

31. 31
Data Migration – Rehearsals
ISAM
VSAM
NDB Oracle DatabaseISAM
VSAM
NDB
Mirror
Copy & Convert
Replication

32. 32
5. Software Migration

33. 33
Software Migration – Outline
Req.
Source
code
Appliction
Platform
Hardware
Reimplement
Convert
Emulate

34. 34
Software Migration – Outline
Reimplement Emulate Convert
Pro
• Optimal performance
• Low maintenance cost
• Development unchanged
• Easy to test
• Easy to migrate
• Flexible cost vs. schedule
• Case-by-case fixes
• Easy to test
Con
• Expensive
• Takes a long time
• Risky
• Difficult to test
• Development unchanged
• Low performance
• Future questionable
• Legacy code remains
• Low performance points
need to be addressed
Requirements?

35. 35
Software Migration – Outline
Reimplement Emulate Convert
Pro
• Optimal performance
• Low maintenance cost
• Development unchanged
• Easy to test
• Easy to migrate
• Flexible cost vs. schedule
• Case-by-case fixes
• Easy to test
Con
• Expensive
• Takes a long time
• Risky
• Difficult migration
• Development unchanged
• Low performance
• Future questionable
• Legacy code remains
• Low performance points
need to be addressed
2x Performance No regression Minimal downtime

36. 36
Software Migration – Outline
Reimplement Emulate Convert
Pro
• Optimal performance
• Low maintenance cost
• Development unchanged
• Easy to test
• Easy to migrate
• Flexible cost vs. schedule
• Case-by-case fixes
• Easy to test
Con
• Expensive
• Takes a long time
• Risky
• Difficult migration
• Development unchanged
• Low performance
• Future questionable
• Legacy code remains
• Low performance points
need to be addressed
2x Performance No regression Minimal downtime

37. 37
Software Migration – Conversion
Japanese COBOL
Source code
Source code
Custom made
source code
converter
 Convert from Japanese
COBOL to Java EE
 Keep original core
business logic

38. 38
Software Migration – Conversion: Dual Source
From Web Systems,
For New Logic
COBOL
From Old System,
converted to Java
 Ease of migration, resource re-use
 Introduce power of Java EE
 Introduce converter from YPS to Java
“Dual Source Architecture”
Japanese
COBOL
 Japanese source code
 Almost abandoned
 No books, no community
Old New

39. 39
Software Migration – Conversion: Single Binary
New Logic
(Java EE)
Application Server
(Java EE)
Legacy Logic
(Mainframe)
Build
Deploy
Japanese
COBOL
Convert to
COBOL
Convert
to Java
COBOL
Java
Compile
WAR
Converter
 Two sources,
single binary
 Easy to operate
Java
Byte Code
Compile
Java

40. 40
Software Migration – New Architecture
BIG-IP
Real-time Servers
(WebLogic)
Batch Servers
(Spark & Java)
Façade
Rich clients Façade
Façade
Intranet
External
Intra
Exadata
Mail
Form
BIG-IP
Façade
BIG-IP
External
customers
Scheduler
CoreBusinessLogicAPIs
Operation
terminal
Web
browser
Old New

41. 41
Auto testing environment
3. Run tests
on staging environment
2. Execute auto testing
on several times
1. Register auto test scenarios
 Automatic testing
using latest IBM
Rational test software
 Regression tests
triggered when
something changed
 Reduce possibility of
errors in production Testing
Server

42. 42
6. Extra Performance with Apache Spark

43. 43
Performance – Issues
Start
Slow
Slow
 Batches are run as networks
 Hierarchical
 Critical path
 Time window

44. 44
Performance – Run in Parallel
Time
Sequential
Parallel

45. Big Improvement – Performance: Apache Spark
45
Cluster Node
Cluster Node
Cluster Node
Cluster Node
Cluster Node
Cluster Node
Bootstrap
New
SharedMemory
Scheduler
Ultra-fast
batch execution

46. 46
7. Results

47. Ready for Migration
47

48. 48
Migration Plan – Data
ISAM
VSAM
NDB Oracle DatabaseISAM
VSAM
NDB
Mirror
Replication
Copy & Convert

49. 49
Migration Plan – Schedule
321
321Data
Saturday Sunday Monday
Check CheckCheck

50. 50
Result
 Live in production
 On schedule
 Lightning fast
 No critical issues

51. 51
8. Into the Future

52. 52
Into the Future
1.0
Initial phase
2.0 In-house
development
3.0
Standardization
4.0
Data Optimized
Outsource based,
just started.
Vendor locked-in.
In-house
development,
differentiate with
lower costs and
faster delivery.
Standardized
system
architecture, both
for hardware and
software.
Overwhelming
differentiation,
with enabling
architecture for
customer centric
service.
Achieved Next
Current Standard
Architecture

53. THANK YOU