AI powered code conversion

AI code conversion (or AI-powered code conversion) strengthens the migration process by using AI agents to convert more objects through automated functional validation of converted database code. It uses synthetic data generation, AI-driven unit testing, and AI-driven resolution of errors identified in the deterministic code conversion step, where error warnings and issues (EWIs) and functional difference messages (FDMs) flag conversion issues—along with an intelligent layer in the Snowflake Service that proactively converts code, verifies correctness, resolves errors, and accelerates confidence.

During migration, deterministic logic is first used to translate the source code, surfacing EWIs and FDMs when it cannot automatically resolve certain patterns. Then, AI code conversion is used to reduce manual remediation effort, identify and resolve issues earlier in the process, and provide assurance to users that the converted objects behave as expected.

Key features of AI code conversion

  • AI 유효성 검사 가속화: 수동 테스트에 소요되는 시간과 리소스를 대폭 줄일 수 있습니다.

  • 테스트 생성 자동화: 에이전트는 기존 쿼리와 비즈니스 논리를 기반으로 테스트 사례를 자동으로 생성합니다.

  • 에이전트 복구 제안: 에이전트는 기존 코드에 대한 패치를 제안하여 레거시 시스템과 Snowflake 간에 일관된 결과를 생성합니다.

Prerequisites for AI code conversion

Before you get started with AI code conversion, complete the following steps:

  1. SnowConvertAI를 다운로드하여 설치합니다.

  2. [권장] SnowConvert AI를 사용하여 레거시 SQL Server 코드를 변환합니다.

  3. 테스트 및 개발 전용 계정을 연결하고 프로덕션 계정은 사용하지 마세요.

    Some objects will be created as part of the AI code conversion process.

  4. 연결하는 계정의 PUBLIC 역할에 프로덕션 데이터에 대한 액세스 권한이 없고 CREATE USER 명령과 같은 민감한 작업을 실행할 수 있는 권한이 없는지 확인합니다.

  5. Ensure that the role used for AI code conversion has the following privileges on the account:

    • CREATE DATABASE

    • CREATE MIGRATION

  6. 해당 계정에서 Cortex AI SQL 함수, 특히 claude-4-sonnet 모델을 활성화합니다.

    • 해당 리전에서 모델을 사용할 수 없는 경우 모델을 활성화하려면 리전 간 추론을 참조하세요.

Getting started with AI code conversion

마이그레이션 유효성 검사 프로젝트를 시작하려면 다음 단계를 완료합니다.

  1. Execute the code conversion of SnowConvert AI on your SQL Server database.

  2. After the code conversion is complete, select GO TO AI code conversion from the Results page.

    (i) 모든 AI 처리는 연결하는 Snowflake 계정에서 이루어지며 Snowflake 요금이 부과됩니다.

  3. You will be redirected to the Connect to Snowflake page to enter the connection parameters of a testing account. This is necessary to ensure that the AI code conversion process creates objects and executes queries in the test database and avoids unintended changes to the production database. Select Continue.

  4. Acknowledge and confirm the AI disclaimers and select Continue.

  5. The Select objects page displays the current conversion status of each database object under the Conversion column. Select the required objects for AI code conversion. You can also run an AI code conversion process with source-system verification by selecting Upload custom instructions.

    SnowConvert는 다음 작업을 자동으로 수행합니다.

    1. 선택한 오브젝트와 종속 오브젝트가 연결되면 자동으로 종속 오브젝트를 선택하고 유효성을 검사합니다.

    2. 선택한 오브젝트, 해당 종속성, 예상 시간 및 Snowflake 크레딧 비용에 대한 요약을 검토합니다.

    3. Confirms the selection to proceed with code conversion.

  6. Select AI Convert. SnowConvert AI connects to your Snowflake account, where it relies on Cortex AI Functions to review your code and suggest resolutions to any problems. AI code conversion might take a few minutes to start, and it might run for several minutes or hours depending on the complexity of the code being verified.

  7. The AI Results page shows the status for the AI code conversion of selected objects. The Status column indicates the AI code conversion outcomes. Select Details to review the test code and test results, source code, and converted code.

    (i) 배포하기 전에 AI에서 생성한 코드를 검토합니다. AI에서 생성한 코드가 올바르지 않을 수 있습니다.

    • Status of the AI code conversion:

      • AI에서 수정됨

      • 확인할 수 없음

      • 확인됨

      • 원본 오브젝트에 오류 발생

    • OPEN CODE:

      • By default, this option opens and compares your original source code and the code generated by the AI code conversion process in VS Code.

      • OPEN CODE 옆의 화살표를 클릭하여 VS Code에서 열고 비교할 수도 있습니다.

        • The converted code from SnowConvert and the code converted by AI.

  8. Select VERIFIED BY USER for all objects for which you have accepted the AI code conversion. Only objects that are verified by the user can be deployed.

Billing and cost considerations with SnowConvert AI code conversion

AI code conversion consumes Snowflake credits based on the compute resources it uses in your Snowflake account. The following features contribute to the cost:

  • AI SQL - AI code conversion uses Cortex AI SQL.

  • 웨어하우스 - 테스트 쿼리는 웨어하우스에서 실행됩니다.

  • Snowflake stages - Input and outputs for AI code conversion are stored in a stage, which incurs storage costs.

  • SPCS - AI code conversion might consume a small amount of credits to use Snowpark Container Services. To find the costs associated with AI code conversion, look for compute pools with names that start with AI_MIGRATOR. For more information, see Snowpark Container Services costs.

자세한 내용은 Snowflake Service Consumption Table을 참조하세요.

Limitations of AI powered code conversion

The initial version is optimized for standard SQL Server migrations. While migration process can handle many query types, all the changes generated by SnowConvert AI code conversion must be reviewed by the customer before they can be deployed to any account.