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Real-world mainframe modernization with AI: A safe, scalable path from mainframe to cloud
Google Cloud proposes an AI-driven, iterative strategy for modernizing legacy mainframe applications to the cloud, addressing real-world complexity through four pillars: assessment, modernization, de-risking, and data migration.
Why it matters
Enterprises with mainframes face high-stakes choices between maintenance and risky 'big bang' migrations. Google Cloud's approach offers a safer, scalable path that reduces migration risk and can enable regulatory approvals, potentially accelerating modernization for global enterprises running critical systems.
The details
- The strategy includes Mainframe Assessment Tool, modernization agents, Dual Run, and Mainframe Connector.
- Dual Run compares live production outputs between mainframe and cloud until equivalence is achieved.
- Customers can choose rewrite/reimagine or deterministic like-to-like modernization based on workload needs.
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In this article
Key connections
Gemini uses Artificial Intelligence
Gemini uses artificial intelligence to assist students
Google owns Mainframe Assessment Tool
Google Cloud offers the Mainframe Assessment Tool for codebase reverse engineering.
Google owns Google Cloud Dual Run
Google Cloud provides Dual Run for parallel validation of mainframe workloads.
Google owns Google Cloud Mainframe Connector
Google Cloud provides Mainframe Connector for mainframe data offloading.
Mainframe Assessment Tool uses Model Context Protocol
Mainframe Assessment Tool integrates outputs into agentic modernization workflows through MCP.
Google Cloud Dual Run uses COBOL
Dual Run validates modernized applications against legacy COBOL mainframe workloads.
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Google Antigravity uses Java
Google Antigravity serves as the harness for transforming legacy mainframe code into Java.
Mainframe Assessment Tool is related to Google Antigravity
Mainframe Assessment Tool extracts business rules used by Google Antigravity in agentic modernization workflows.
Google Cloud Mainframe Connector uses BigQuery
Mainframe Connector copies and converts mainframe data into BigQuery.
Google Cloud Mainframe Connector uses Spanner
Mainframe Connector copies and converts mainframe data into Spanner.
Google Cloud Mainframe Connector uses Cloud SQL
Mainframe Connector copies and converts mainframe data into Cloud SQL.
Google Cloud Mainframe Connector uses Cloud Storage
Mainframe Connector copies and converts mainframe data into Cloud Storage.
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