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The client is a leading American brokerage and banking company.

Infosys has partnered with the client on trading platform modernization program. Key objective of the trading platform modernization program is to modernize the 40-year-old mainframe-based technology platform in order to simplify and improve flexibility, scalability and delivery.

An application with multiple logical layers created to decouple customer facing systems from mainframe and to enable faster response. Multiple transaction systems consolidated and applications which support key functionalities like entry, status, routing and posting were unified.

Key Challenges

  • Legacy systems written with elaborate COBOL code and processing use hundreds of legacy database structures
  • Systems have become overly complex and inflexible. Implementing new features were hence challenging
  • No ability to track transaction status from start to end and lack of auditing and tracking creates many risks
  • Application and data cache are tightly coupled on the same server box. Hence, cache and application cannot be scaled independently
  • Cache is deployed on virtual machines (VMs). It is a challenge to determine if all servers have exactly the same data at a given point in time

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The Solution

Leveraging Agile and Data Mining Approach

  • Open source NoSQL-based DB as data repository for all needs of the systems during trading time
  • Single and unified systems that will handle transactions from entry to execution, which will rely on NoSQL data
  • Suite of applications that will support risk management functionalities and rely on NoSQL data
  • DB2 as master data store that will be updated asynchronously
  • Developed various tools for data recovery from different data centers, compared data between data centers, error handling, and reprocessing to help business and operations support teams for quick resolution of customer complaints
  • Implemented SRE (Site Reliability Engineering) teams for supporting infrastructure and operational problems
  • Shadow mode development
    • Developed production parallel shadow system to compare results between current versus shadow data, benefitting in terms of lesser defects and deployments in production environment
    • Compare tools – Developed various data compare tools and techniques to compare between current versus shadow data
  • Agile / DevOps
    • Development and release in smaller parts to reduce business risks
    • Automated deployments
    • Integrated tools like Veracode / SonarQube to provide cleaner code and reduce risk of deploying erroneous code
    • Scriptless testing automation using TOSCA

Integrated Approach for Implementation Management

  • High performing REST services were written in Microsoft .NET platform and C#
  • Response time of services were reduced by:
    • Light weight services
    • NoSQL database
    • Customized business logic based on type of transactions
  • Developed libraries for common functionalities / logic which can be reused by several applications across the organization
  • All new functionalities and data were added to the modernized applications and DBs only. Business units requiring these changes were asked to migrate the specific set of customers to the new platform
  • In-flight / Regulatory projects / Production fixes changes were implemented in the legacy applications and DBs first. The changes were retrofitted to new applications and DBs once they were stabilized on the legacy side
  • Phased rollout approach to have a lesser impact on business
  • Thoroughly planned releases involving multiple teams and validation of systems during production rollouts to reduce risks during market open time
  • Blue-green deployments to reduce downtime and risk of the application by running two identical production environments
  • Integration with external tools like AppDynamics and Splunk to monitor and improve performance
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Benefits

System was simplified with the use of NoSQL data

System was simplified with the use of NoSQL data

Enabled running application in different data centers

Enabled running application in different data centers

Transaction processing system on distributed environment reduced mainframe resource utilization vastly

Transaction processing system on distributed environment reduced mainframe resource utilization vastly

Reduced mainframe server resources demand, especially during market open

Reduced mainframe server resources demand, especially during market open

Higher throughput and reduced latency, especially during market open with newer systems

Higher throughput and reduced latency, especially during market open with newer systems

Retirement of old system and data structure

Retirement of old system and data structure

Newer flexible and scalable system, which is more resilient to change and enables rollout of new functionality quicker than the earlier one

Newer flexible and scalable system, which is more resilient to change and enables rollout of new functionality quicker than the earlier one

The solution reduced the MIPS by approximately 20%, thus, reducing the operational cost

The solution reduced the MIPS by approximately 20%, thus, reducing the operational cost