AWS Transform Now Modernizes Codebases and SQL Server Without Live Links

The Core · TL;DR
- AWS Transform's continuous modernization went GA on August 3, 2026, scanning connected GitHub, GitLab, and Bitbucket repos and opening pull/merge requests with validated fixes.
- A separate offline source transformation feature converts Microsoft SQL Server databases to Amazon Aurora PostgreSQL using uploaded DDL files instead of a live database connection.
- Analysis and remediation run inside the customer's own AWS account with their credentials, and source code stays under customer control.
- Continuous modernization is available in all supported AWS Transform regions, while offline source transformation is currently limited to US East (N. Virginia).
AWS pushed two AWS Transform capabilities to general availability on August 3, 2026, expanding the agentic modernization service beyond one-off migrations into continuous, repository-wide code upkeep and offline database conversion.
The first, continuous modernization, lets engineering teams connect GitHub organizations, GitLab groups, and Bitbucket workspaces so AWS Transform can scan source repositories at scale. Analyses run on demand or on a recurring schedule, surfacing findings across technical debt, security, agentic readiness, modernization readiness, and custom criteria teams define themselves.
When a fix exists, the service does more than flag it. AWS Transform creates branches and opens pull or merge requests with validated code changes tied to specific findings, letting reviewers approve remediations through their normal git workflow rather than a separate console.
Crucially, analysis and remediation execute inside the customer's own AWS account under their own credentials, and source code never leaves their control. Teams get Kiro Power, agent plugins, and CLI tools to work from an IDE or terminal instead of being locked into a single web interface.
Offline SQL Server to Aurora conversion
The second release targets a narrower but common pain point: modernizing Microsoft SQL Server databases to Amazon Aurora PostgreSQL without a live connection to the source database. Customers instead upload SQL Server data design language (DDL) files.
AWS Transform then assesses database and stored procedure complexity and generates a transformation plan that engineers can customize before conversion begins. Storage objects are converted using AWS DMS, while code objects like stored procedures go through an agentic, interactive conversion experience.
The workflow validates functional equivalence before deploying the converted schema to Aurora PostgreSQL, and a separate synthetic data workflow populates the target database with test data for end-to-end validation. That combination lets teams check application behavior against realistic data before cutting over.
Availability
Both offline source transformation and the broader full-stack Windows modernization feature it belongs to are currently available in US East (N. Virginia). Continuous modernization, by contrast, is generally available across all AWS Regions where AWS Transform already operates.
The gap in regional footprint between the two launches is notable: enterprises outside Virginia can start automating pull-request-driven remediation immediately, but SQL Server-to-Aurora conversions without a live database link remain limited to a single region for now.
For engineering organizations sitting on large legacy Windows and SQL Server estates, the pairing addresses two distinct blockers at once: the ongoing grind of technical debt across sprawling codebases, and the operational risk of migrating databases that can't easily be connected to for a live assessment.
Original reporting and research used to synthesize this article.
WAKIB Editorial Team
This review was prepared and summarized by the WAKIB AI intelligence engine and vetted by our editorial board for accuracy and reliability.
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