Exam AWS Certified Database - Specialty topic 1 question 284 discussion

A. Probably won't help B. Increasing the size of the Aurora instance will not improve the performance of AWS SCT. C. "Use one of these methods to control the memory usage and performance of the AWS SCT tool." D. "It's a best practice to install the AWS SCT on a separate machine that's in the same network as your source. This allows for better performance in the code conversion and data migration phases"

Key factor would be the performance of the SCT running env. https://repost.aws/knowledge-center/dms-optimize-aws-sct-performance Fast conversion, but large memory consumption - This optimizes the speed of the conversion. But, it might need more memory for the object reference cache. + Java In the JavaOptions section, set the minimum and maximum memory available to the AWS SCT. This example sets a minimum of 4GB and a maximum of 40GB:

Definitely option C. check this link to validate - https://repost.aws/knowledge-center/dms-optimize-aws-sct-performance. The goal is to improve performance and not memory consumption so, option A must be ruled out as balanced setting will compromise performance and option A doesn't even mention Java memory setting which is another key mechanism to improve SCT performance. Remaining options are distractors so, option C is the best.

The answer is C Refer to the link below, the compute power of the target database does not matter. "The performance of the AWS SCT depends on the memory that's available on the local machine that it's installed on. If you increase the memory that's available to the AWS SCT, then you also speed up the performance of your conversion. But this means that the AWS SCT also consumes more memory resources on your local machine." Furthermore fast conversion tells SCT to use optimise speed at the expense of memory

To resolve the performance issues of the AWS SCT conversion, the database specialist should provision the target Aurora PostgreSQL database with a higher instance class and turn on the balance speed with memory consumption performance option in AWS SCT. Option B is the correct answer because increasing the instance class of the target Aurora PostgreSQL database will improve its processing power and memory, which will allow it to handle the AWS SCT conversion more efficiently. Additionally, turning on the balance speed with memory consumption performance option in AWS SCT will optimize the conversion process for performance and memory usage.