Discover how to effectively reduce costs and manage resources with AWS DynamoDB for high traffic applications.
Table of Contents
Question
A company operates quick-service restaurants. The restaurants follow a predictable model with high sales traffic for 4 hours daily. Sales traffic is lower outside of those peak hours.
The point of sale and management platform is deployed in the AWS Cloud and has a backend that is based on Amazon DynamoDB. The database table uses provisioned throughput mode with 100,000 RCUs and 80,000 WCUs to match known peak resource consumption.
The company wants to reduce its DynamoDB cost and minimize the operational overhead for the IT staff.
Which solution meets these requirements MOST cost-effectively?
A. Reduce the provisioned RCUs and WCUs.
B. Change the DynamoDB table to use on-demand capacity.
C. Enable Dynamo DB auto scaling for the table.
D. Purchase 1-year reserved capacity that is sufficient to cover the peak load for 4 hours each day.
Answer
C. Enable Dynamo DB auto scaling for the table.
Explanation
The most cost-effective solution for this scenario is Option C: Enable DynamoDB auto scaling for the table.
Auto Scaling in DynamoDB is a feature that automatically adjusts the provisioned throughput capacity of your tables based on the actual traffic patterns. This feature helps you manage throughput capacity more efficiently and helps reduce the cost by dynamically adjusting capacity in response to traffic changes.
In this case, since the high traffic is predictable and lasts for only 4 hours daily, DynamoDB auto scaling can scale up the provisioned RCUs and WCUs during the peak hours and scale them down when the demand is low. This ensures that the provisioned throughput is closely aligned with the traffic pattern, thus reducing the cost.
On the other hand, options A, B, and D are not as cost-effective:
- Option A: Reducing the provisioned RCUs and WCUs might save cost during non-peak hours, but it could lead to throttling during peak hours when the demand is high.
- Option B: While on-demand capacity can handle unpredictable workloads, it is generally more expensive than provisioned capacity for predictable workloads.
- Option D: Purchasing 1-year reserved capacity might not be cost-effective because it doesn’t account for the variability in usage. It would be paying for peak capacity even during non-peak hours.
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