Business-critical data pipelines, a hard shutdown date, and a system that never stops. Moving an on-premises Hadoop estate without pausing the business or hand-migrating the pipelines.
Data processing jobs migrated to cloud
Faster migration
Ahead of the delivery deadline
An on-premises Hadoop estate was being shut down, with thousands of processing jobs needing to move to Google Cloud before the date. Migrating pipelines by hand is slow and error-prone at that scale, and the existing architecture was fragmented across siloed on-premises systems with limited cloud-native skills in-house. The data foundation had to modernize without slowing the business or introducing risk into a live payments environment.
Synapt Data Transformation, deployed as a GenAI migration accelerator that turned a fixed deadline into a controlled, repeatable process.
Legacy code translated into Google Cloud-native form automatically, with minimal manual rework
Accuracy checks running as part of the pipeline, not as a separate review step
Monitored cutover with a hyper-care period to surface issues early
Engineers migrating faster with less dependence on scarce SMEs
Automated code conversion
Legacy pipelines translated to Google Cloud-native form without hand-rewriting
Built-in validation
Accuracy checks running automatically across every migrated job
Governed cutover
Monitored transition with security, compliance, and data accuracy held constant
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