A company is working on migrating a large Oracle database schema with 3,500 stored procedures to Amazon Aurora PostgreSQL. An application developer is using the AWS Schema Conversion Tool (AWS SCT) to

The "balance speed with memory consumption" option aims for a middle ground, which might not be sufficient for a large schema with 3,500 stored procedures experiencing significant performance issues.

Provisioning a higher instance class for the target Aurora PostgreSQL database does not directly impact the performance of the AWS SCT client-side schema and code conversion process, as SCT performs the conversion logic on the client before applying it to the target.

The "fast conversion with large memory consumption" performance option in AWS SCT is designed to optimize the conversion process for large and complex schemas by leveraging more available memory on the client machine. Allocating more memory to the client machine running SCT further supports this option, allowing SCT to process more data in memory and reduce I/O operations, thereby accelerating the conversion of numerous stored procedures.

While provisioning a client EC2 machine with more CPU and memory resources can help, it's not the most direct or complete solution without also configuring AWS SCT to utilize those resources optimally through its performance options.