AI Verification with Source-System Verification¶

AI verification with source-system verification improves the accuracy of the conversion process. It runs the generated test case against both the converted code in Snowflake and the original source code in the source database. It then checks that both the source code and converted code produce equivalent results.

Compared to the default AI verification where SnowConvert only verifies that the converted code is running successfully on Snowflake, AI verification with source-system verification ensures functional parity, higher confidence and overall better conversion quality.

Overview of AI verification with source-system verification¶

AI verification with source-system verification currently requires an instance of SQL Server hosted in Snowpark Container Services. This SQL Server instance acts as a host for the test cases that will be executed by the source-system verification process. The test results from this instance will be used as a baseline to compare against the test results generated by executing the test cases on the converted Snowflake SQL code.

Prerequisites for AI verification with source-system verification¶

An instance of SQL Server should be running in your SPCS environment. Refer to SnowPark Container Services for more information.
Understand and agree to the legal responsibilities of using the AI verification with source-system verification on your source data platform code inside the SPCS environment.
Create a custom specification file (for example, spec.yaml). This file contains the connection parameters for the SQL Server instance running inside SPCS.

Sample for spec.yaml
```
mode: "TWO_SIDED"
source_test_database:
  connection_params:
  hostname: "mssql-server-demo-service.n4yw.svc.spcs.internal"
  port: 1433
  username: "sa"
  password: "StrongPassw0rd"
connection_metadata:
  type: "SPCS"
  spcs_service:
    name: "MSSQL_SERVER_DEMO_SERVICE"
    database: "SNOWCONVERT_AI"
    schema: "PUBLIC"
```
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- The mode “TWO_SIDED” indicates that the AI verification with source-system verification process will run on both source database code and target database code.
- The host name, port number, and credentials for the SQL Server database running in SPCS is specified under source\_test\_database.
- The name of the container service, database name and the schema name where the test cases for the source will be executed is specified under connection\_metadata.

Steps to run AI verification with source-system verification¶

From the AI verification page, connect to Snowflake using a valid connection string. SnowConvert currently supports programmatic access tokens, in addition to the standard authentication methods for AI verification.
Accept the disclaimers and confirm your account identifier. Select Continue to proceed to the Select objects to verify with AI.
Select See custom instructions on the top left of the Select objects to verify with AI page.
Select the latest version of the yaml file you created as a prerequisite and select Save.

You have now configured AI verification process to run in two-sided mode. This will compare test results from the source SQL Server database to the converted Snowflake SQL code.
Proceed with the AI verification steps to complete the source-system verification process.

Impact on costs and dependencies¶

The costs for running AI verification with source-system verification may be different from the default AI verification, depending on your Snowflake credits consumption for Snowpark container services and Cortex AI. A summary of the estimated costs and number of objects impacted for the source-system verification process can be found in the Selection Summary. We recommend reviewing the Selection Summary before proceeding to Verify.