Amazon-DEA-C01 Exam - Topic 4 Question 10 Discussion

Actual exam question for Amazon's Amazon-DEA-C01 exam

Question #: 10
Topic #: 4

A mobile gaming company wants to capture data from its gaming app. The company wants to make the data available to three internal consumers of the data. The data records are approximately 20 KB in size.

The company wants to achieve optimal throughput from each device that runs the gaming app. Additionally, the company wants to develop an application to process data streams. The stream-processing application must have dedicated throughput for each internal consumer.

Which solution will meet these requirements?

AConfigure the mobile app to call the PutRecords API operation to send data to Amazon Kinesis Data Streams. Use the enhanced fan-out feature with a stream for each internal consumer.

BConfigure the mobile app to call the PutRecordBatch API operation to send data to Amazon Data Firehose. Submit an AWS Support case to turn on dedicated throughput for the company's AWS account. Allow each internal consumer to access the stream.

CConfigure the mobile app to use the Amazon Kinesis Producer Library (KPL) to send data to Amazon Data Firehose. Use the enhanced fan-out feature with a stream for each internal consumer.

DConfigure the mobile app to call the PutRecords API operation to send data to Amazon Kinesis Data Streams. Host the stream-processing application for each internal consumer on Amazon EC2 instances. Configure auto scaling for the EC2 instances.

Show Suggested Answer

Suggested Answer: A

Problem Analysis:

Input Requirements: Gaming app generates approximately 20 KB data records, which must be ingested and made available to three internal consumers with dedicated throughput.

Key Requirements:

High throughput for ingestion from each device.

Dedicated processing bandwidth for each consumer.

Key Considerations:

Amazon Kinesis Data Streams supports high-throughput ingestion with PutRecords API for batch writes.

The Enhanced Fan-Out feature provides dedicated throughput to each consumer, avoiding bandwidth contention.

This solution avoids bottlenecks and ensures optimal throughput for the gaming application and consumers.

Solution Analysis:

Option A: Kinesis Data Streams + Enhanced Fan-Out

PutRecords API is designed for batch writes, improving ingestion performance.

Enhanced Fan-Out allows each consumer to process the stream independently with dedicated throughput.

Option B: Data Firehose + Dedicated Throughput Request

Firehose is not designed for real-time stream processing or fan-out. It delivers data to destinations like S3, Redshift, or OpenSearch, not multiple independent consumers.

Option C: Data Firehose + Enhanced Fan-Out

Firehose does not support enhanced fan-out. This option is invalid.

Option D: Kinesis Data Streams + EC2 Instances

Hosting stream-processing applications on EC2 increases operational overhead compared to native enhanced fan-out.

Final Recommendation:

Use Kinesis Data Streams with Enhanced Fan-Out for high-throughput ingestion and dedicated consumer bandwidth.

Kinesis Data Streams Enhanced Fan-Out

PutRecords API for Batch Writes

by Evangelina at Jan 28, 2025, 03:32 PM

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Jonell

3 months ago

I’m leaning towards A, but not sure about the Kinesis Data Streams part.

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Skye

3 months ago

D is a good choice too, especially with auto scaling.

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Wade

3 months ago

Wait, can you really get dedicated throughput just by asking AWS?

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Albina

4 months ago

I think B is better for dedicated throughput.

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Odette

4 months ago

Option A seems solid with the enhanced fan-out feature!

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Earleen

4 months ago

I recall that using the Kinesis Producer Library can help with batching, but I’m not clear on how it compares to the PutRecords API in terms of throughput for multiple consumers.

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Arlean

4 months ago

I practiced a similar question where we had to choose between Kinesis and Firehose, and I think Kinesis is better for real-time processing, but I’m not certain about the enhanced fan-out feature.

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Chi

4 months ago

I think the PutRecords API is the right choice for sending data, but I’m a bit confused about whether to use Data Streams or Data Firehose for processing.

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Ora

5 months ago

I remember studying Kinesis Data Streams and how it can handle high throughput, but I'm not sure if enhanced fan-out is necessary for this scenario.

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Cammy

5 months ago

I'm leaning towards option C. Using the Kinesis Producer Library to send data to Firehose and then leveraging the enhanced fan-out feature sounds like it could work well. I'll need to double-check the details, but I think that's the way to go.

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Deandrea

5 months ago

Okay, I've got a strategy. I'll focus on the enhanced fan-out feature of Kinesis Data Streams to provide the dedicated throughput for each internal consumer. That seems like the most straightforward solution.

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Lindsay

5 months ago

Hmm, I'm a bit confused about the difference between Kinesis Data Streams and Kinesis Data Firehose. I'll need to review the details of each service to determine the best fit.

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Adell

5 months ago

This looks like a tricky question, but I think I can break it down. I'll need to carefully consider the requirements around throughput and dedicated streams for each internal consumer.

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Audra

1 year ago

I'm surprised they didn't consider going serverless with AWS Lambda and Amazon API Gateway. That could have been a cost-effective solution too. But I guess Kinesis is the way to go here.

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Gilma

11 months ago

C) Configure the mobile app to use the Amazon Kinesis Producer Library (KPL) to send data to Amazon Data Firehose. Use the enhanced fan-out feature with a stream for each internal consumer.

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Brendan

11 months ago

A) Configure the mobile app to call the PutRecords API operation to send data to Amazon Kinesis Data Streams. Use the enhanced fan-out feature with a stream for each internal consumer.

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Owen

1 year ago

Option A all the way! I love how it streamlines the data processing for each internal consumer. It's like a buffet for data, with each consumer getting their own plate!

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Roxane

1 year ago

I'm not sure, but option D also sounds like a good choice. Hosting the stream-processing application on Amazon EC2 instances with auto scaling could be beneficial.

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Keneth

1 year ago

I'm a bit worried about the size of the data records. 20 KB might be a bit heavy for a mobile app to handle. But overall, I think Option A is the best solution.

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Telma

1 year ago

Hmm, I don't know. Option B with Firehose and dedicated throughput might work too. But I think the Kinesis Data Streams approach is more flexible and scalable.

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Gary

1 year ago

I agree, Option A is the way to go. The enhanced fan-out feature will ensure that each internal consumer gets the data they need without any bottlenecks.

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Aleisha

11 months ago

Option A with Amazon Kinesis Data Streams and enhanced fan-out feature is the way to go for optimal throughput and dedicated streams.

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Alfred

11 months ago

Agreed, Option A seems like the most effective way to meet the company's requirements.

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Zona

11 months ago

I think Option A is the most efficient solution. Having a stream for each internal consumer will optimize data availability.

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Darrin

11 months ago

Option A is definitely the best choice. The enhanced fan-out feature will provide dedicated throughput for each internal consumer.

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Tiera

1 year ago

I agree with Queenie. Using Amazon Kinesis Data Streams with enhanced fan-out seems like the most efficient way to achieve optimal throughput.

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Queenie

1 year ago

I think option A is the best solution.

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Dwight

1 year ago

Option A seems like the best solution to me. Using Amazon Kinesis Data Streams with the enhanced fan-out feature will give each internal consumer a dedicated throughput, which is exactly what the company wants.

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