Amazon BDS-C00 Exam - 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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Merlyn

5 months ago

B sounds inefficient, why store data if you just need alerts?

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Benedict

5 months ago

Surprised they didn't mention using Kinesis, it's great for streaming data!

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Hubert

5 months ago

Not sure about A, what if the volume of alerts is too high?

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Lottie

5 months ago

I agree, SNS notifications are quick and cost-effective!

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Rebecka

6 months ago

Option A seems the simplest for real-time alerts.

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Vashti

6 months ago

I recall we practiced a similar question where we used SNS for alerts. Option A seems like the best fit for quick notifications based on the metrics.

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Junita

6 months ago

I feel like storing data in DynamoDB (option B) could work, but it might not be the most cost-effective for real-time alerts. I need to think more about that.

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Dan

6 months ago

I'm not entirely sure, but I remember something about using Kinesis for real-time data processing. Option D might be the right choice, but it feels a bit complex.

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Viola

6 months ago

I think option A sounds familiar since we discussed using AWS IoT rules for notifications in class. It seems like a straightforward approach.

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Anika

6 months ago

Option A looks like the simplest solution - using an AWS IoT rule to generate an SNS notification. That could be a good way to get near real-time alerts without too much overhead. I'll make sure to read the details carefully.

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Glennis

6 months ago

Hmm, I'm a bit unsure about this one. There are a few options presented, and I'm not sure which one would be the most cost-effective. I'll need to think through the pros and cons of each approach.

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Jamal

6 months ago

This seems like a straightforward question about real-time alerting on pipeline metrics. I think the key is to identify the most cost-effective solution that can provide near real-time alerts.

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Rolland

7 months ago

The DynamoDB and EC2 option (B) seems interesting, but I'm not sure how that would compare in cost and performance to the other choices. I'll need to do some research on the tradeoffs between the different approaches.

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Trinidad

7 months ago

I leaned towards option B during the study sessions, but now I'm questioning if there might be aspects related to service restoration as well.

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Oren

12 months ago

Option A is the way to go. Anything else is just gilding the lily. Although, I do wonder if the sensors are made by BP - they seem to have a knack for leaks.

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Terry

10 months ago

D) Use Amazon Kinesis Streams and a KCL-based application deployed on AWS Elastic Beanstalk

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Halina

10 months ago

Option A is the way to go. Anything else is just gilding the lily.

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Blythe

10 months ago

B) Store the data points in an Amazon DynamoDB table and polite peak metrics data from an Amazon EC2 application

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Elbert

11 months ago

A) Create an AWS IoT rule to generate an Amazon SNS notification

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Roslyn

12 months 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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Jesse

10 months 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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Clare

10 months ago

C) Create an Amazon Machine Learning model and invoke with AWS Lambda

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Benton

10 months ago

B) Store the data points in an Amazon DynamoDB table and polite peak metrics data from an Amazon EC2 application

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Benedict

10 months ago

A) Create an AWS IoT rule to generate an Amazon SNS notification

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Adelina

1 year 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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Ronna

12 months ago

B) Store the data points in an Amazon DynamoDB table and polite peak metrics data from an Amazon EC2 application

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Tu

12 months ago

A) Create an AWS IoT rule to generate an Amazon SNS notification

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Tran

1 year 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

1 year ago

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

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Freeman

1 year ago

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

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Melissa

1 year 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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