A company that runs its application on AWS uses an Amazon Aurora DB cluster as its database. During peak usage hours when multiple users access and read the data, the monitoring system shows degradation of database performance for the write queries. The company wants to increase the scalability of the application to meet peak usage demands.
Which solution will meet these requirements MOST cost-effectively?
To increase the scalability of the application during peak usage hours and address the degradation of database performance for write queries, the most cost-effective solution involves reducing the load on the primary instance by offloading read operations to a read replica. Creating an Aurora read replica in the existing Aurora DB cluster allows the application to distribute read queries to the read replica while write queries continue to go to the primary cluster. This improves the overall performance and scalability without incurring significant additional costs.
Answer C, wording is that read queries are slowing down write queries -> we need to optimize for read queries -> we need to add read replicas. https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.Managing.Performance.html#Aurora.Managing.Performance.ReadScaling
Read Replica for multiple users access and read the data
AnswerC A - We can create only RO replica of DB hence this is not possible. D - Redshift is not for a DB from my understanding but more like analitics tools B - Could be a thinkg but there is no point of Read-Only from DAX and write to DB cluster. beside it is hard to say if it would be cost effective as we are paying per hour not R/W requests as it is with replica. Hence I would go with C
write queries=>High performance of read & Write Dynamo, I think DAX is a better solution.
Dynamo is NoSQL...