Making ClearPath Forward®

relevant in the digital ageRudy Everaert, Enterprise Architect, ING Belgium

Introduced by David Howard, Unisys

2© 2018 Unisys Corporation. All rights reserved. |

Unisys Data Exchange

ClearPath Forward

Databases

Data ExchangeExtract, Transform and Load

ClearPath Forward

Applications

Digital

Applications and

Big Data

DMS II / RDMS / (DMS coming)

SQL Server / Oracle

(copy of the data)

KAFKA – enabling

publishing

of ‘events’

The changes happening to

the CPF database

Bulk Data Transfer – BDT

Change Data Transfer - CDT

Making ClearPath Forward® relevant in the digital age

ClearPath Future MattersBirmingham, September 11, 2019

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One ING experience built on one global foundation

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Infrastructure Layer (MCP…)(Dev, Test, Acceptance,

Production)

DMS IIMiddleware

(TACSy)

Business Applications

International Payment

MortgageLoans

Client Referential

AccountMgt

DomesticPayment Savings

EASY API

MCP Unisys eco-system at ING Belgium

Most of the ING Belgium core banking applications

are running on ClearPath platform

Our challenge

Unlock the value of the MCP business-critical applications in the digital era and be a facilitator in the realization of the thinkforward > unite strategy.

Core : 16 x Libra 8390 servers

Satellite Systems : Windows/linux

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API oriented and event driven architecture enables heritage applications to be relevant in the realization of the thinkforward > unite strategy

Core enterprise applications are managed using

enterprise application tools

Custom integrations use APIs in enterprise applications and custom

services

mutations and events are replicated using events on the eventbus

API management tools ensure consistency in security and access policies

Eventbus management tools ensure consistency in security

and access policies

Mobile and Web app requests are decoupled from enterprise applications

using APIs.

Enables independent development of personalized user experiences and

customized B2B opportunities

Enterprise AppImplementation

Enterprise App APIs

Too

ls

Enterprise App events

Event Bus

Discoverable APIs

Custom Service

IoTB2B omnichannel

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Making ClearPath Forward® relevant in the digital age

VirtualizedMCP

Steaming ETL

Near real time integration

Data masking

Standardization (ING Private cloud)Adapt to DevOps culture

MainframeOffloading

Availability &responsiveness

compliance

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MCP virtualization

Align and support DevOps culture

Standardization (ING Private cloud)

Shared mainframe, Any applicationClearPath® MCP Libra

Dedicated mainframe, Tribe application clusteringClearPath® MCP Software

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system of record

DMS II

domain eventstore

bounded context

global event store

Service

DMS II

*CDC

Shared model• a domain event contains all data which might be needed by all other bounded contexts• Interested bounded contexts are tolerant readers ignoring all data that is not relevant

Domain event sourcing payload strategy • state• domain event• domain event + state

Advantage• Immutable once persisted• Near real time streaming• Convey current state, and how this state has been reached. • Reconstruct any state by replaying the events up to a certain point in time • Support reconciliation restarting from a current state

MCP

Interested bounded context

Continuous near real time integration

Streaming ETL with change data transfer mode

*CDC : Change Data Capture (DataExchange)

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Solve the caching consistency data freshness problem with continuous streaming

system of record

DMS II

domain eventstore

bounded context

localevent store

Service

DMS II

*CDC

readstore

API

Client

commands queries

MCP

▪ Improve Customer Experience

▪ Increase responsiveness

▪ Increase availability (365/7/24)

▪ Improve time to market

Streaming ETL with change data transfer mode

Mainframe offloading

*CDC : Change Data Capture (DataExchange)

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Data masking

system of record

Service

DMS II

*CDC

Data masking service

Static data masking creating a structurally similar but inauthentic version of the data that can be used for purposes such as software testing and user training

Reuse the data masking service in the ING’s open world to protect sensitive, private information in DMS II data bases.

Ensure consistent data sets. Shared data masking policies to mask specific types of data. The policy describe the data that needs to be masked. A policy does not contain any data source.

Production

Acceptance, Test and development

Bulk data transfer mode to mask all data

proactively protect ING’s data to avoid security breaches and ensure compliance.

system of record

Service

DMS II

*CDC

MCP

MCP

*CDC : Change Data Capture (DataExchange)

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DataExchange 5.0 ic2 – performance

Record mutationsper second

DMS II table

Mode

DataExchange 5.0 ic2

Bulk Data transfer

Simple

15.000

Complex

7.500

Change Data Transfer

Simple

1500

Complex

750

Complex withwork-

around

1500with 2 shards

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Complexity of DMS II table

- 50% RMPS*

Grouping of record mutations to speed up publishing to Kafka

no atomic events

Single-threading

Maximum 1500 RMPS*in CDT mode

Observations with DataExchange in change data transfer (CDT) mode

* RMPS : record mutations per second

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Observations with DataExchange in change data transfer (CDT) mode

Performance issues (700 MPS) because of single-threaded implementation on complex tables

5000

3500

2500

700

excellent

good

average

fair

poor

low Current performance

With work-around

acceptable performance

expected performance

local/globalevent store

DMS II

…CDC*

*CDC : Change Data Capture * DEX: DataExchange

Ic2 work-around allows to scale-out

Need for a good sharding keys to balance over

Need for good sharding keys to balance over DEX* instances and to ensure completeness of the CDC!

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Key Takeaways

➢ Keep the domain event stores simple. Complex DMS II tables have an high impact on performance

➢ DataExchange 5.0 – ic2 work-around allows the improve Kafka provider performanceThough complex and at a high cost. Just a set of disconnected DataExchange instances

➢ No atomic event. Grouping mutations in one event is a CDC anti-pattern.Requires an integration service on the event bus to undo the grouping.

➢ DataExchange 6.0 should solves change data transfer (CDT) performance issues (single-threading – MS SQL – atomic events)