Amazon Web Services Updated SAA-C03 Exam Questions and Answers by zayaan

Amazon EFS offers an Infrequent Access (IA) storage class, which can be managed via EFS lifecycle policies. Frequently accessed files remain in the Standard storage class, while infrequently accessed files are automatically moved to the IA class, significantly reducing storage costs with minimal effort and no application changes.

Reference Extract:

"EFS lifecycle management automatically transitions files that are not accessed for a set period to the EFS Infrequent Access (IA) storage class, reducing storage costs."

Source: AWS Certified Solutions Architect – Official Study Guide, EFS and Lifecycle Management section.

Amazon RDS Performance Insights is a “database performance tuning and monitoring feature” that can be enabled with a few clicks and “helps you quickly assess the load on your database” and identify bottlenecks. It surfaces key metrics, including DB load, top SQL, waits, and host metrics such as CPU utilization, which are commonly used indicators for right-sizing (up or down). This provides the lowest operational effort compared to building log pipelines or querying CloudTrail (which does not capture SQL workload characteristics). AWS X-Ray traces application requests, not database internals, and CloudWatch Logs aggregation requires custom ingestion and analysis. Enabling Performance Insights directly on the RDS instance provides actionable utilization data to right-size with minimal setup.

Amazon Timestreamis purpose-built for storing and analyzing time-series data like telemetry.

Option Aleverages Timestream, SageMaker for ML, and QuickSight for visualization, meeting all requirements with minimal complexity.

Option Binvolves more complex DynamoDB-EMR integration.

Option Cuses Neptune, which is designed for graph databases, not telemetry data.

Option Dincorrectly uses Athena for visualization instead of QuickSight.

The most scalable and managed solution for streaming ingestion, real-time transformation, and delivery to Amazon S3 is Amazon Kinesis Data Streams, Amazon Managed Service for Apache Flink, and Amazon Kinesis Data Firehose.

From AWS Documentation:

“Amazon Kinesis Data Streams enables real-time processing of streaming data at massive scale. With Apache Flink on Kinesis Data Analytics, you can process data streams in near real-time, then use Amazon Kinesis Data Firehose to reliably deliver that data to S3.”

(Source: Amazon Kinesis Developer Guide)

Why A is correct:

Fully managed: All services involved are serverless and managed.

Real-time ingestion: Kinesis Data Streams supports sub-second latency and can handle high-throughput workloads like 100,000+ devices.

Near real-time processing: Apache Flink is designed for continuous stream processing with complex event handling.

Efficient delivery: Kinesis Firehose delivers processed data directly to S3 with retry and backup capability.

Why other options are incorrect:

Option B: SQS is not optimized for real-time streaming at high volume.

Option C: EC2 + Kafka + EMR adds high operational overhead and cost.

Option D: EventBridge is event-driven, not designed for high-throughput streaming; AWS Batch is unsuitable for near real-time processing.