Q5 — AWS DVA-C02 Ch.1

Question 5 of 100 | ← Chapter 1

A company has deployed smart meters at all customer locations. Smart meters measure electricity usage every minute and send usage readings to an endpoint for collection. The company needs to create an endpoint to receive smart meter readings and store them in a database. The company wants to store location ID and timestamp information. The company requires low-latency access to both current and historical usage data for customers. The company expects demand to increase significantly. The solution must not impact availability or include downtime during scaling. Which solution meets these requirements most cost-effectively?

Correct Answer: B. Store smart meter readings in an Amazon DynamoDB table. Create a composite key using location ID as the partition key and timestamp as the sort key. Use these keys to filter customer data.

Explanation

Amazon DynamoDB is a highly scalable NoSQL database service ideal for handling large volumes of read/write operations without performance degradation during scale-out. Its auto-scaling capability ensures zero-downtime scaling, satisfying high-availability requirements. Composite key design: Using location ID as the partition key and timestamp as the sort key enables efficient querying and sorting by location and time—fulfilling low-latency access to current and historical usage. Cost efficiency: DynamoDB’s pay-per-use pricing model aligns with variable workloads and controls costs effectively. Comparison: Option A (RDS) lacks DynamoDB’s elasticity and low-latency query performance at scale. Option C (ElastiCache for Redis) prioritizes caching speed over persistent, scalable storage. Option D (S3 + Athena) introduces latency unsuitable for real-time access. Thus, Option B is optimal.