Scaling the Data Tier in AWS

Correct Answers - A and D.

AWS documentation mentions the following.

Amazon RDS Read Replicas provide enhanced performance and durability for database (DB) instances.

This replication feature makes it easy to elastically scale out beyond a single DB Instance's capacity constraints for read-heavy database workloads.

You can create one or more replicas of a given source DB Instance and serve high-volume application read traffic from multiple copies of your data, thereby increasing aggregate read throughput.

Read replicas can also be promoted when needed to become standalone DB instances.

For more information on AWS RDS Read Replica's, please visit the URL below:

https://aws.amazon.com/rds/details/read-replicas/

Amazon ElastiCache is a web service that makes it easy to deploy, operate, and scale an in-memory data store or cache in the cloud.

The service improves web applications' performance by allowing you to retrieve information from fast, managed, in-memory data stores instead of relying entirely on slower disk-based databases.

For more information on AWS ElastiCache, please visit the URL below.

https://aws.amazon.com/elasticache/

The given scenario involves a read-intensive application hosted in AWS, consisting of web servers and AWS RDS. It has been observed that the response time of the application increases due to the load on the RDS instance. In this case, the data tier can be scaled using the following measures:

A. Create Amazon DB Read Replicas: This solution involves creating read replicas of the RDS instance to offload the read traffic from the primary instance. Read replicas are asynchronous copies of the primary instance that can be used to serve read requests. By configuring the application layer to query the read replicas for read requests, the load on the primary instance can be reduced. This approach improves read scalability, availability, and reduces the response time. However, it doesn't help in scaling write operations.

D. Use ElastiCache in front of your Amazon RDS DB: ElastiCache is a fully managed in-memory data store that can be used to cache frequently accessed data. By using ElastiCache in front of the RDS instance, common queries can be cached, reducing the load on the RDS instance. This approach improves both read and write scalability, availability, and reduces the response time.

B. Use Auto Scaling to scale out the database tier: Auto Scaling can be used to add or remove RDS instances based on the demand. However, this approach may not be effective for read-intensive workloads as adding more RDS instances may not improve read performance. Also, it requires additional management overhead, and the cost may increase as the number of instances increases.

C. Use SQS to cache the database queries: SQS is a message queuing service that can be used to decouple and scale distributed systems. However, using SQS to cache the database queries may not be effective as it introduces additional latency and may not be suitable for real-time applications.

In summary, the most appropriate measures for scaling the data tier in a read-intensive application are creating Amazon DB read replicas and using ElastiCache in front of the RDS instance.