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Hello nopainnogain,
Thanks for sharing your thoughts.
To understand it better, let’s break down the question into two parts.
1. The application’s workload requires a high-performance, parallel hot storage to process the training datasets concurrently
In the first requirement, you need to use a service for parallel hot storage.
– The keyword here is “parallel.” Based on this AWS FAQS, Amazon FSx for Lustre provides a parallel file system. Since the scenario also stated that the application consumes thousands of data sets to train its machine learning model. We can take a look at this part of the Amazon FSx for Lustre FAQs.
Q: What use cases does Amazon FSx for Lustre support?
A: Use Amazon FSx for Lustre for workloads where speed matters, such as machine learning, high-performance computing (HPC), video processing, financial modeling, genome sequencing, and electronic design automation (EDA).
Amazon FSx For Windows File Server is incorrect because it does not have a parallel file system, unlike Lustre.
https://aws.amazon.com/fsx/lustre/faqs/
2. It also needs cost-effective cold storage to archive those datasets that yield low profit.
– On the second requirement, we can use Amazon S3 for storing the cold data. Amazon S3 supports a cold storage system via Amazon S3 Glacier / Glacier Deep Archive.
Let us know if you need further assistance. The Tutorials Dojo team is dedicated to helping you pass your AWS exam on your first try!
Regards,
Gerome @ Tutorials Dojo
