Q34 — AWS SAA-C03 Ch.17

Question 34 of 89 | ← Chapter 17

Q1334. A company has concerns about its Amazon RDS database. The workload is unpredictable, and periodic floods of new user registrations can cause the company to run out of storage. The database runs on a general purpose instance with 300 GiB of storage.What should a solutions architect recommend to the company?

Correct Answer: A. Enable RDS storage autoscaling.

Explanation

Let's analyze each option to determine the best recommendation for the company facing unpredictable workloads and periodic floods of new user registrations that cause it to run out of storage on its Amazon RDS database:Option A: Enable RDS storage autoscalingAmazon RDS storage autoscaling allows the storage capacity of a DB instance to scale automatically based on the actual storage usage. When the storage is approaching its limit, RDS can automatically add more storage to the instance. This is an ideal solution for unpredictable workloads where the storage requirements can vary significantly over time. It eliminates the need for manual intervention to increase storage and ensures that the database has sufficient storage to handle sudden spikes in user registrations and data growth. So, this option is a strong candidate.Option B: Schedule vertical instance scalingVertical instance scaling involves changing the instance type to one with more resources (such as more CPU, memory, or storage). However, scheduling vertical scaling is not practical for unpredictable workloads. Since the company does not know when the floods of new user registrations will occur, it cannot accurately schedule the scaling events. If the scaling is not done at the right time, the database may still run out of storage, leading to performance issues or downtime. Therefore, this option is not suitable. Option C: Change to a storage optimized instance type and vertically scale the database While a storage-optimized instance type may provide better storage performance and capacity, simply changing the instance type and vertically scaling the database does not address the issue of unpredictable workloads. The company would still need to manually monitor the storage usage and scale the database when necessary. This approach is not scalable and can lead to the same problem of running out of storage if the scaling is not done in a timely manner. Hence, this option is not the best solution. Option D: Configure an AWS Lambda function to increase RDS storage by 1 GiB when storage space is lowAlthough using an AWS Lambda function to monitor storage and increase it when necessary is a possible approach, it requires more complex setup and maintenance compared to RDS storage autoscaling. The company would need to write and manage the Lambda function, set up appropriate triggers, and handle error cases. RDS storage autoscaling is a built-in feature that is easier to configure and manage, and it provides a more reliable and automated solution for handling storage growth. So, this option is not as good as Option A.Based on the above analysis, the solutions architect should recommend enabling RDS storage autoscaling.