While analyzing billions of web pages in a company, you have noticed some munging processes are exceeding SLAs even after using X1e instances suitable for HPC applications. After monitoring logs, trailing, and tracing data closely, you noticed that write operations involving S3 content pre-processing causing 80% of the bottleneck. In comparison, read operations for post-processing and LIST operations are together leading to the remaining 20% of congestion. Which two options are recommended to increase performance in this scenario? (Select TWO)

Answer options:

A.Migrate S3 files to an RDS database with write-optimized IOPS.
B.Using Amazon S3 Transfer Acceleration, Multipart upload, parallelized reading via byte-range fetches, and partitioned prefix for distributing key names as part of naming patterns.
C.Instead of LIST operations, you can scale storage connections horizontally since Amazon S3 is a very large distributed system similar to a decoupled parallel, single network endpoint. You can achieve the best performance by issuing multiple concurrent requests to Amazon S3.
D.Instead of LIST operations, you can build a search catalog to keep track of S3 metadata by using other AWS services like Amazon DynamoDB or Amazon OpenSearch Service.
E.Combining Amazon S3 and Amazon EC2 instances by migrating your current buckets to the region where the instances are available. This will help to reduce network latency and data transfer costs.

Answers: B and D
The problem description highlights write operations having 80% of the impact when compared to read operations. Amazon S3 Transfer Acceleration helps especially in this scenario along with multipart upload.
X1 and X1e instances are memory-optimized instances designed for running large-scale and in-memory applications in the AWS Cloud. 
Generally, it is a recommended practice to benefit from byte-range fetches and appropriate distributing key names. Another complex practice to avoid expensive LIST operations relies on a search framework to keep track of all objects in an S3 bucket. 
Lambda triggers are used to populate DynamoDB tables with object names and metadata when those objects are put into Amazon S3 then OpenSearch Service is used to search for specific assets, related metadata, and data classifications.
Option A is incorrect because this option is not applicable as you would need to migrate the data to a relational database in RDS.
Option C is incorrect because the phrase does not make sense, especially considering that the Amazon S3 service is exactly the opposite of a single network endpoint.
Option E is incorrect because you cannot migrate an existing S3 bucket into another AWS Region, rather create a new S3 bucket in the region and copy the data to it. However, the statement does not solve the problem description.
References:
https://aws.amazon.com/s3/transfer-acceleration/
https://docs.aws.amazon.com/whitepapers/latest/s3-optimizing-performance-best-practices/use-byte-range-fetches.html
https://docs.aws.amazon.com/whitepapers/latest/building-data-lakes/data-cataloging.html