AWS Certified Solutions Architect - Associate
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A company has one million users that use its mobile app. The company must analyze the data usage in near-real time. The company also must encrypt the data in near-real time and must store the data in a centralized location in Apache Parquet format for further processing.
Which solution will meet these requirements with the LEAST operational overhead?
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A
Create an Amazon Kinesis data stream to store the data in Amazon S3. Create an Amazon Kinesis Data Analytics application to analyze the data. Invoke an AWS Lambda function to send the data to the Kinesis Data Analytics application.
B
Create an Amazon Kinesis data stream to store the data in Amazon S3. Create an Amazon EMR cluster to analyze the data. Invoke an AWS Lambda function to send the data to the EMR cluster.
C
Create an Amazon Kinesis Data Firehose delivery stream to store the data in Amazon S3. Create an Amazon EMR cluster to analyze the data.
D
Create an Amazon Kinesis Data Firehose delivery stream to store the data in Amazon S3. Create an Amazon Kinesis Data Analytics application to analyze the data.
Explanation:
Explanation
Correct Answer: D
Key Requirements Analysis:
- Near-real-time data analysis - Requires streaming analytics capability
- Encrypt data in near-real time - Kinesis Data Firehose supports encryption
- Store data in Apache Parquet format - Kinesis Data Firehose can convert to Parquet format
- Store in centralized location (S3) - Both Kinesis and Kinesis Data Firehose can deliver to S3
- LEAST operational overhead - This is the critical differentiator
Why Option D is Correct:
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Kinesis Data Firehose vs Kinesis Data Stream:
- Kinesis Data Firehose is a fully managed service that automatically scales, encrypts data, and converts formats (including to Parquet)
- Kinesis Data Stream requires more operational overhead for scaling, shard management, and data processing
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Kinesis Data Analytics vs EMR:
- Kinesis Data Analytics is a serverless, fully managed service for real-time analytics
- EMR requires cluster management, scaling, and operational overhead
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No Lambda Function Needed:
- Option D doesn't require Lambda functions for data transfer, reducing operational complexity
- Kinesis Data Firehose directly integrates with Kinesis Data Analytics
Why Other Options are Incorrect:
Option A: Uses Kinesis Data Stream (more operational overhead) and requires Lambda function for data transfer
Option B: Uses Kinesis Data Stream (more operational overhead), EMR (more operational overhead), and requires Lambda function
Option C: Uses Kinesis Data Firehose (good) but pairs it with EMR (high operational overhead for real-time analytics)
Key AWS Service Features:
- Kinesis Data Firehose: Automatically scales, encrypts data, converts to Parquet format, delivers to S3
- Kinesis Data Analytics: Serverless SQL queries on streaming data, integrates directly with Kinesis Data Firehose
- Together: Provide a complete serverless solution for real-time analytics with minimal operational overhead
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