AWS Certified Big Data – Specialty — Question 43

A large oil and gas company needs to provide near real-time alerts when peak thresholds are exceeded in its pipeline system. The company has developed a system to capture pipeline metrics such as flow rate, pressure, and temperature using millions of sensors. The sensors deliver to AWS IoT.
What is a cost-effective way to provide near real-time alerts on the pipeline metrics?

Answer options

• A. Create an AWS IoT rule to generate an Amazon SNS notification.
• B. Store the data points in an Amazon DynamoDB table and poll if for peak metrics data from an Amazon EC2 application.
• C. Create an Amazon Machine Learning model and invoke it with AWS Lambda.
• D. Use Amazon Kinesis Streams and a KCL-based application deployed on AWS Elastic Beanstalk.

Correct answer: C

Explanation

The correct answer is C because using an Amazon Machine Learning model with AWS Lambda allows for real-time processing and alerting based on the pipeline metrics. Options A and B are less efficient since they either rely on polling or don't leverage real-time analytics, while D, although capable of processing streams, might not be as cost-effective or straightforward for the immediate alerting need.