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Legacy Migration & Modernization

Project Information

  • Project Name : Enterprise Legacy Migration & Modernization
  • Category : Modernization
  • Client : Fortune 100 Manufacturing Enterprise
  • Complete Date : October, 2023
  • Skills : Mainframe JCL jobs, COBOL, SAS, DB2, Oracle, Stored Procedures  Agile SCRUM | Azure DevOps | CI/CD Pipelines | GitHub Technologies: Java, Python, Data Warehouse, Data Marts, Informatica

Legacy Migration & Modernization

Project Description

Modernized a complex, undocumented legacy mainframe system through deep reverse engineering and Agile-driven execution.
Migrated workloads to a scalable, cloud-native architecture with APIs, microservices, and modern data platforms—ensuring zero disruption to operations.

Project Challenge 

  • •   Legacy mainframe ecosystem with no documentation and requirements
  • •   No clear system architecture, workflows, or data visibility
  • •   Complex dependencies across COBOL, JCL batch jobs, IMS, DB2, Oracle, and ETL pipelines
  • •   Need to modernize to the cloud without disrupting critical business operations

•   Legacy mainframe ecosystem with no documentation and requirements
•   No clear system architecture, workflows, or data visibility
•   Complex dependencies across COBOL, JCL batch jobs, IMS, DB2, Oracle, and ETL pipelines
•   Need to modernize to the cloud without disrupting critical business operations

Quadyster’s Approach Performed deep reverse engineering of legacy systems

  • • Analyzed extensive COBOL programs, JCL batch jobs, IMS transactions, and DB2 stored procedures
  • • Developed detailed pseudo-code and logical workflows to reconstruct business logic
  • • Defined requirements iteratively using Agile SCRUM methodology
  • • Established target architecture and phased migration strategy
  • • Executed an incremental delivery model to reduce risk and ensure continuity

Project Solution

  • • Converted legacy workloads into Java/Python-based APIs and microservices
  • • Migrated Legacy & Oracle (Dealer, Customer, AOR) data to AWS Cloud
  • • Transformed Informatica ETL into cloud-native pipelines
  • • Built modern Data Warehouses & Data Marts across key business domains
  • • Delivered UI/UX applications for improved accessibility

Results & Impact

  • • Delivered full modernization on time and within budget
  • • Reconstructed system knowledge through pseudo-code-driven reverse engineering
  • • Enabled scalable, cloud-native, API-driven architecture
  • • Improved performance, maintainability, and data accessibility
  • • Achieved zero disruption to mission-critical operations

Value to the Client

  • • Expertise in handling highly ambiguous, undocumented legacy environments
  • • Strong capability in mainframe-to-cloud transformation
  • • Proven ability to deliver cost-efficient, high-impact modernization solutions
  • • Realized significant cost savings by:
  • • Reducing dependency on expensive mainframe infrastructure
  • • Optimizing ETL and batch processing workloads
  • • Enabling efficient cloud resource utilization
  • • Lowering long-term maintenance and operational overhead