A telecommunications company collects network usage data throughout each day at a rate of several thousand data points each second. The company runs…

The requirement is for real-time processing with the least latency to detect sudden drops in network usage. Amazon Kinesis Data Streams is designed for high-throughput, real-time data ingestion. Amazon Managed Service for Apache Flink (formerly Kinesis Data Analytics) is purpose-built for complex, stateful stream processing with sub-second latencies. This combination provides a serverless, highly scalable architecture ideal for real-time anomaly detection on streaming data, directly meeting the low-latency requirement.

A. Polling an Aurora database every minute introduces significant latency (up to 60 seconds) and is not a real-time streaming solution.
C. This solution still relies on polling every minute, which does not meet the low-latency requirement. DAX is a cache and does not change the polling architecture.
D. Aurora Database Activity Streams are for auditing database events (like logins or queries), not for analyzing the application data being written into the tables.

1. Amazon Kinesis Data Analytics for Apache Flink Developer Guide. (2023). What Is Amazon Kinesis Data Analytics for Apache Flink? AWS Documentation. "You can use Kinesis Data Analytics for real-time analytics. You can process streaming data in real time and with sub-second latencies..."

2. Amazon Web Services. (2021). Streaming Data Solutions on AWS with Amazon Kinesis. AWS Whitepaper, p. 10. "Amazon Kinesis Data Analytics is the easiest way to analyze streaming data, gain actionable insights, and respond to your business and customer needs in real time."

3. Amazon Aurora User Guide. (2023). Using Database Activity Streams. AWS Documentation. "Use database activity streams to audit the activity of your DB cluster."