Amazon Exam BDS-C00 Topic 3 Question 105 Discussion

Actual exam question for Amazon's BDS-C00 exam

Question #: 105
Topic #: 3

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?

ACreate an AWS IoT rule to generate an Amazon SNS notification

BStore the data points in an Amazon DynamoDB table and polite peak metrics data from an Amazon EC2 application

CCreate an Amazon Machine Learning model and invoke with AWS Lambda

DUse Amazon Kinesis Streams and a KCL-based application deployed on AWS Elastic Beanstalk

Show Suggested Answer

Suggested Answer: B

by Melda at Sep 14, 2024, 03:03 PM

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Roslyn

3 days ago

Kinesis Streams and Elastic Beanstalk could work, but it's probably more elaborate than necessary. Why not go with the simpler IoT-based solution?

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Adelina

14 days ago

Creating a machine learning model and invoking it with Lambda might be overkill for this use case. The problem doesn't seem to require advanced analytics.

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Tran

14 days ago

Storing the data in DynamoDB and polling for peak metrics from an EC2 instance seems like an overly complex approach. Why not just use the built-in alerting capabilities of AWS IoT?

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Lakeesha

15 days ago

I prefer option B because storing data in DynamoDB and using EC2 application seems more reliable.

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Freeman

18 days ago

I disagree, I believe option D using Amazon Kinesis Streams is more efficient.

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Melissa

19 days ago

Option A is the most straightforward and cost-effective solution. Using an AWS IoT rule to generate an Amazon SNS notification is a simple and reliable way to get real-time alerts.

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Zona

24 days ago

I think option A is the most cost-effective way to provide near real-time alerts.

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