Use of HPC-Techniques for Large-Scale Data Migration

Any re-design of a distributed legacy system requires a migration which involves numerous complex data replication and transformation steps. Migration procedures can become quite difficult and time-consuming, especially when the setup (i.e., the employed databases, encodings, formats etc.) of the legacy and the target system fundamentally differ, which is often the case with finance data, grown over decades. We report on experiences from a real-world project: the recent migration of a customer loyalty system from a COBOL-operated mainframe to a modern service-oriented architecture. In this context, we present our easy-to-adopt solution for running most replication steps in a high-performance manner: the

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HPC-software which helps minimizing the replication time, and, thereby, the overall

downtime

of the migration. Business processes can be kept up and running most of the time, while pre-extracted data already pass a variety of platforms and representations toward the target system. We combine the advantages of traditional migration approaches: transformations, which require the interruption of business processes are performed with static data only, they can be made undone in case of a failure and terminate quickly, due to the use of parallel processing.