Amazon Web Services SAA-C03 Exam With Confidence Using Practice Dumps

Amazon DynamoDB supports two read consistency models: eventually consistent reads and strongly consistent reads. By default, DynamoDB uses eventual consistency, which means reads might not immediately reflect the most recent writes. This behavior explains why the application is not always receiving the latest data.

Because latency and performance are acceptable, the problem is not throughput or response time—it is data consistency. Therefore, the correct design change is to enable strongly consistent reads, which guarantee that reads always return the most up-to-date data after a successful write.

Option C is correct because strongly consistent reads ensure that the application sees the latest committed value for an item. This is critical for use cases such as inventory systems, user profiles, or transactional workflows where stale data can cause incorrect behavior.

Option A is invalid because DynamoDB does not support traditional read replicas. Option B does not affect consistency; GSIs are used to query data by alternative keys. Option D would worsen the problem because eventual consistency already causes stale reads.

Therefore, C is the appropriate recommendation to ensure correctness of returned data without changing the table schema or introducing additional complexity.

Amazon EMR is the strongest fit here because AWS describes EMR as a service for processing, analyzing, transforming, and moving large amounts of data, and EMR supports running parallel steps for distributed processing. The question explicitly wantsparallel processingof large semistructured data in S3, which matches EMR well. AWS also documents a supported pattern forloading data from Amazon EMR to Amazon Redshift, and Redshift supports querying semistructured data, which makes EMR plus Redshift a natural enrichment workflow. Athena and Glue can be useful in some analytics patterns, but the requirement for parallel high-volume processing points most directly to EMR.

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Amazon CloudFront is a global content delivery network (CDN) that caches and distributes content to users with low latency. By setting the existing ALB as the origin, CloudFront can cache dynamic and static content closer to users worldwide, improving performance and reducing the load on the application servers. This is the most cost-optimized and AWS-recommended way to globally serve dynamic content for web applications.

Reference Extract:

" CloudFront accelerates delivery of both static and dynamic content, reducing latency and offloading origin resources by caching content at edge locations. "

Source: AWS Certified Solutions Architect – Official Study Guide, CloudFront and Global Application section.