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Amazon MLS-C01 Exam - Topic 3 Question 128 Discussion

[Modeling]An aircraft engine manufacturing company is measuring 200 performance metrics in a time-series. Engineerswant to detect critical manufacturing defects in near-real time during testing. All of the data needs to be storedfor offline analysis.What approach would be the MOST effective to perform near-real time defect detection?
D) Use Amazon Kinesis Data Firehose for ingestion and Amazon Kinesis Data Analytics Random Cut Forest(RCF) to perform anomaly detection. Use Kinesis Data Firehose to store data in Amazon S3 for furtheranalysis.
A) Use AWS IoT Analytics for ingestion, storage, and further analysis. Use Jupyter notebooks from withinAWS IoT Analytics to carry out analysis for anomalies.
B) Use Amazon S3 for ingestion, storage, and further analysis. Use an Amazon EMR cluster to carry outApache Spark ML k-means clustering to determine anomalies.
C) Use Amazon S3 for ingestion, storage, and further analysis. Use the Amazon SageMaker Random CutForest (RCF) algorithm to determine anomalies.

Amazon MLS-C01 Exam - Topic 3 Question 128 Discussion

Actual exam question for Amazon's MLS-C01 exam
Question #: 128
Topic #: 3
[All MLS-C01 Questions]

[Modeling]

An aircraft engine manufacturing company is measuring 200 performance metrics in a time-series. Engineers

want to detect critical manufacturing defects in near-real time during testing. All of the data needs to be stored

for offline analysis.

What approach would be the MOST effective to perform near-real time defect detection?

Show Suggested Answer Hide Answer
Suggested Answer: D

by Tyisha at Apr 04, 2026, 11:47 PM

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Olive
8 days ago
But A has Jupyter notebooks, which are great for analysis later.
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Tamie
13 days ago
I agree, D seems efficient for near-real time.
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Glynda
18 days ago
I think option D is the best. Real-time processing is key.
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Joanna
23 days ago
Not sure if Kinesis is the right choice for this scale.
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Izetta
29 days ago
C is great for offline analysis, but not for near-real time.
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Lisbeth
1 month ago
Surprised that no one mentioned the cost implications!
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Lili
3 months ago
I think A is solid too, but not as fast as D.
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Galen
3 months ago
Option D seems the best for real-time processing!
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Johnson
4 months ago
I’m a bit confused about the differences between Kinesis and IoT Analytics. I feel like both could work, but I’m leaning towards Kinesis for real-time needs.
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Ammie
4 months ago
I think we practiced a question similar to this, and I remember that Kinesis was highlighted for its streaming capabilities. That might be the way to go.
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Lauran
4 months ago
I'm not entirely sure, but I feel like using SageMaker with RCF could be effective too. It seems like a solid choice for anomaly detection.
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Aja
4 months ago
I remember we discussed the importance of real-time data processing in our last class. I think Kinesis might be the best option for that.
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